Semi-Automated Shoe Cleaning Machine: Comprehensive Engineering Design, Customer Needs QFD, SolidWorks 3D CAD Modeling, ANSYS FEA Structural Simulation, Material Selection, and Manufacturing Cost Analysis Report

Fuad, Md. Muqtadir; Al Mazid, Abdullah; Noor, Md. Ashiqur Rahman; Haque, Md Sadiqul; Halder, Ananya; Noor, Yashna

Report Page Cover PDF Page 1 / 151

BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY

DEPARTMENT OF INDUSTRIAL AND PRODUCTION ENGINEERING

IPE 304

A Report On

Semi-Automated Shoe Cleaning Machine

Report Page Title & Faculty PDF Page 2 / 151

A Report On

Semi-Automated Shoe Cleaning Machine

Course No: IPE 304 | Course Title: Product Design-II Sessional

Date of Submission: 15-12-2024

Submitted To

Dr Shuva Ghosh
Associate Professor
Dr A.B.M. Mainul Bari
Associate Professor
Nafisa Anzum Sristi
Lecturer
Zahin Ar Rafi
Lecturer

Department of Industrial and Production Engineering, BUET

Submitted By: Group- B14

Md. Muqtadir Fuad
Student ID: 2008079
Abdullah Al Mazid
Student ID: 2008080
Md. Ashiqur Rahman Noor
Student ID: 2008081
Md Sadiqul Haque
Student ID: 2008082
Ananya Halder
Student ID: 2008083
Yashna Noor
Student ID: 2008084

Department of Industrial and Production Engineering, BUET

Report Page I PDF Page 3 / 151

COPYRIGHT NOTICE

All rights reserved. This document is protected by copyright. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without prior written permission of the authors and the Department of Industrial and Production Engineering, BUET.

Report Page II PDF Page 4 / 151

FORWARDING LETTER

Date: December 15, 2024

Dr. Shuva Ghosh, Associate Professor

Dr. A.B.M. Mainul Bari, Associate Professor

Nafisa Anzum Sristi, Lecturer

Zahin Ar Rafi, Lecturer

Department of Industrial and Production Engineering, BUET

Subject: Report on “Semi-Automated Shoe Cleaning Machine”

Honorable Teachers,

It is our great pleasure to present the report entitled “Semi-Automated Shoe Cleaning Machine” to you. We are very thankful to you for your kind help to accomplish this product design project.

The semi-automated shoe cleaning machine is a unique innovation that combines traditional cleaning methods with modern technology to deliver an efficient and user-friendly experience. By incorporating semi-automated mechanisms, the machine allows users to control the cleaning process, ensuring thorough cleaning and polishing of shoes with minimal effort. In this report, we showcased the functions, working principles, manufacturing processes, and overall costing of the Semi-Automated Shoe Cleaning Machine.

We would like to thank you for your cooperation in completing this project. We solemnly apologize for the involuntary mistakes, if there are any.

Sincerely yours,

Md. Muqtadir Fuad
Student ID: 2008079

Abdullah Al Mazid
Student ID: 2008080

Md. Ashiqur Rahman Noor
Student ID: 2008081

Md Sadiqul Haque
Student ID: 2008082

Ananya Halder
Student ID: 2008083

Yashna Noor
Student ID: 2008084

Level-3, Term-2 • Department of Industrial and Production Engineering, BUET

Report Page III PDF Page 5 / 151

PREFACE

Engineering design is a creative and systematic process of developing a product or system to meet specific needs. It is an iterative process involving repeated problem-solving, testing, and refinement cycles. This report presents the design of a semi-automated shoe-cleaning machine. The machine can clean, and polish, making it a versatile tool for personal and commercial use.

The report begins by discussing the need for the machine and the target market. It then describes the design process, including the problem definition, concept generation, and evaluation. The report also discusses the manufacturing process and cost analysis. The goal of this report is to share the design process for the semi-automated shoe-cleaning machine and to encourage students to engage in creative product design.

The need for a semi-automated shoe-cleaning machine is evident in households and commercial spaces such as hotels and offices. Users need a machine that can perform a variety of tasks, such as cleaning, polishing, and sanitizing shoes efficiently. Current methods on the market are either too labor-intensive or lack versatility. The target market for the semi-automated shoe-cleaning machine is individuals and organizations that value convenience and efficiency in shoe care. The machine is user-friendly and can be utilized by people with varying levels of technical expertise.

The design process for the semi-automated shoe-cleaning machine began with a problem definition. We identified the needs of users and the shortcomings of current solutions available on the market. We then generated a variety of concepts for the machine. These concepts were evaluated based on their functionality, manufacturability, and cost. The final design of the machine was chosen for its ease of use, versatility, and cost-effectiveness. The machine is made of durable materials, ensuring longevity and easy maintenance. It is also equipped with safety features to protect the user during operation.

We hope that this report will be informative and helpful to students who are interested in product design. We also hope that this report will inspire students to engage in creative and innovative product development.

Report Page IV PDF Page 6 / 151

ABSTRACT

Executive Abstract | BUET Capstone Engineering Design Report

The “Semi-Automated Shoe Cleaning Machine” report presents a comprehensive study conducted in the context of Bangladesh, focusing on the development and evaluation of an innovative cleaning solution that combines traditional cleaning methods with semi-automated technology. In a country where efficient and hygienic cleaning solutions are becoming increasingly necessary, this product is designed to cater to individuals and small businesses seeking an affordable and user-friendly shoe cleaning solution.

Based on the market survey results, we determined the customer requirements and technical specifications, along with their relationships and correlations. We then conducted qualitative analysis of material, manufacturing processes, and joining process selections. Following this, we performed quantitative analyses by calculating relative emphasis coefficients using the Digital Logic Method and performance indices. Additionally, we conducted equivalent (von Mises) stress, total deformation, fatigue life, and fatigue safety factor analyses using Ansys. Finally, we performed cost, breakeven, and sensitivity analyses for our product.

Hopefully, this report will encourage students to design and analyze their own innovative products.

Keywords: Semi-Automated Shoe Cleaning Customer Needs Survey QFD House of Quality SolidWorks 3D CAD ANSYS FEA Simulation Digital Logic Method Break-Even & Sensitivity Analysis

Report Page V PDF Page 7 / 151

ACKNOWLEDGEMENT

Faculty Mentorship & Guidance

We want to express our sincere appreciation to our esteemed faculty members, Dr. Shuva Ghosh, Dr. A. B. M. Mainul Bari, Zahin Ar Rafi, and Nafisa Anzum Sristi for their unwavering patience, invaluable guidance, and unwavering support in the creation of this report and throughout the course. We are truly fortunate to have had the opportunity to engage in a real-world project, developing new product ideas, and honing our skill sets under their mentorship. Their insightful suggestions and the time they dedicated to mentoring us throughout the course were instrumental in the successful completion of this project, especially within the stipulated timeframe.

Industry & Field Survey Contributors

We would also like to express our deep appreciation to people from different corporate offices whose generous support made our field research possible. Their provision of valuable market insights and encouragement was instrumental in propelling our project forward. While preparing this report, we encountered and surmounted significant challenges, and we cherished every moment of the journey.

Team Dedication & Collaboration

Lastly, we emphasize that this report is the culmination of collective effort and could not have been accomplished without the equal and vital contributions of each team member. We extend our heartfelt gratitude to our esteemed faculty members and everyone who collaborated with us on this endeavor.

Report Page i PDF Page 8 / 151

List of Tables

Table 2. 1: Time period of cleaning shoes 7

Table 2. 2: Current cleaning methods 8

Table 2. 3: Cost of single shoe cleaning 9

Table 2. 4: Challenges of cleaning shoes 10

Table 2. 5: Satisfaction of current cleaning method 11

Table 2. 6: Interest in Automatic Cleaning Machine 12

Table 2. 7: Important features of machine 13

Table 2. 8: Portability or non-portability of the machine 14

Table 2. 9: Factors influence to purchase a new cleaning device 15

Table 2. 10: Availability of similar product 16

Table 2. 11: Additional features to make machine more appealing 17

Table 2. 12 : Usable environment for shoe cleaning machine 18

Table 2. 13: Maintenance period of machine 19

Table 2. 14: Concern of cross-contamination & hygiene in common areas 20

Table 2. 15: Importance of having environmentally friendly features 21

Table 2. 16: Concern of noise level 22

Table 2. 17: Recommendations to other organizations 23

Table 2. 18: Relative importance of customer requirements 24

Table 3. 1: Relationship Explanation 27

Table 5. 1: Load Applied of Base 46

Table 5. 2 Total deformation of Base 47

Table 5. 3: Equivalent Strain of Base 48

Table 5. 4: Equivalent Elastic Stress of Base 49

Table 5. 5: Safety Factor of base 50

Table 5. 6: Fatigue Life of Base 51

Table 5. 7: Load Applied of Frame 52

Table 5. 8:Total deformation of Frame 53

Report Page viii PDF Page 15 / 151

Table 5. 9: Equivalent Strain of Frame 54

Table 5. 10: Equivalent Elastic Stress of Base 55

Table 5. 11: Safety Factor of Frame 56

Table 5. 12: Fatigue Life of Frame 57

Table 5. 13: Load Applied of Shaft 58

Table 5. 14: Total deformation of Shaft 59

Table 5. 15: Equivalent Strain of Shaft 60

Table 5. 16: Equivalent Elastic Stress of Shaft 61

Table 5. 17: Safety Factor of Shaft 62

Table 5. 18: Fatigue Life of Shaft 63

Table 5. 19: Load Applied of Worm-Gear Connector 64

Table 5. 20: Total deformation of Worm-Gear Connector 65

Table 5. 21: Equivalent Strain of Worm-Gear Connector 66

Table 5. 22: Equivalent Elastic Stress of Worm-Gear Connector 67

Table 5. 23:Safety Factor of Worm-Gear Connector 68

Table 5. 24:Fatigue Life of Worm-Gear Connector 69

Table 5. 25: Load Applied to Side-Brush-Support 70

Table 5. 26: Total deformation of Side-Brush-Support 71

Table 5. 27: Equivalent Strain of Side-Brush-Support 72

Table 5. 28: Equivalent Elastic Stress of Side-Brush-Support 73

Table 5. 29:Safety Factor of Side-Brush-Support 74

Table 5. 30: Fatigue Life of Side-Brush-Support 75

Table 6. 1: Qualitative Analysis of Material Selection for Different Sections 76

Table 6. 2: Qualitative Analysis of Manufacturing Process Selection 78

Table 6. 3: Qualitative Analysis of Parts Joining Method Selection 79

Table 7. 1: Likert Chart for comparing material selection 83

Table 7. 2: List of material properties selected for roller shaft 83

Table 7. 3: Lists of selection criteria with values from Likert scale 84

Table 7. 4: Determination of Relative Importance of Goals Using Digital Logic Method 85

Report Page ix PDF Page 16 / 151

Table 7. 5: Calculation of the Performance Index 86

Table 7. 6: Material Properties Comparison for frame and base 87

Table 7. 7: Likert Scale for Non-Numeric Properties 87

Table 7. 8: Determination of Relative Importance of Goals Using Digital Logic Method 88

Table 7. 9: Calculation of the Performance Index 89

Table 7. 10: List of material properties selected for lower sole cleaner brush fiber 90

Table 7. 11: Determination of Relative Importance of Goals Using Digital Logic Method 90

Table 7. 12: Calculation of the Performance Index 90

Table 7. 13: List of properties for comparing manufacturing process for AISI 347 Annealed Stainless Steel

used in roller shaft 92

Table 7. 14: Determination of Relative Importance of Goals Using Digital Logic Method 92

Table 7. 15: Calculation of the Performance Index 93

Table 7. 16: List of properties for Stainless Steel (AISI 304) used in base and frame of the structure 94

Table 7. 17: Determination of Relative Importance of Goals Using Digital Logic Method 94

Table 7. 18: Calculation of the Performance Index 95

Table 7. 19: List of properties for comparing manufacturing process for AISI 347 Annealed Stainless Steel

used in roller shaft 96

Table 7. 20: Determination of Relative Importance of Goals Using Digital Logic Method 96

Table 7. 21: Calculation of the Performance Index 97

Table 7. 22: List of properties for permanent joining process of machine parts 98

Table 7. 23: Determination of Relative Importance of Goals Using Digital Logic Method 98

Table 7. 24: Calculation of the Performance Index 99

Table 7. 25: List of properties for temporary joining process of machine parts 100

Table 7. 26: Determination of Relative Importance of Goals Using Digital Logic Method 100

Table 7. 27: Calculation of the Performance Index 101

Table 7. 28: List of properties for Finishing operation of the parts 102

Table 7. 29: Determination of Relative Importance of Goals Using Digital Logic Method 102

Table 7. 30: Calculation of the Performance Index 103

Table 7. 31: List of properties for coloring and aesthetic finish 103

Table 7. 32: Determination of Relative Importance of Goals Using Digital Logic Method 104

Table 7. 33: Calculation of the Performance Index 104

Report Page x PDF Page 17 / 151

Table 8. 1: Purchasing cost per unit 109

Table 8. 2: Manufacturing Overhead Cost 110

Table 8. 3: Total Manufacturing Cost 111

Table 8. 4: Administrative cost of administrative personnel per month 111

Table 8. 5: Total Non-Manufacturing Cost (per year) 112

Table 8. 6: Total Yearly Cost 113

Table 8. 7: Direct Material Cost 115

Report Page xi PDF Page 18 / 151

List of Illustrations

Figure 2. 1: Time period of cleaning shoes 7

Figure 2. 2: Current cleaning methods 8

Figure 2. 3: Cost of single shoe cleaning 9

Figure 2. 4: Challenges of cleaning shoes 10

Figure 2. 5: Satisfaction of current cleaning method 11

Figure 2. 6: Interest in Automatic Cleaning Machine 12

Figure 2. 7: Important features of machine 13

Figure 2. 8: Portability or non-portability of the machine 14

Figure 2. 9: Factors influence to purchase a new cleaning device 15

Figure 2. 10: Availability of similar product 16

Figure 2. 11: Additional features to make machine more appealing 17

Figure 2. 12 : Usable environment for shoe cleaning machine 18

Figure 2. 13: Maintenance period of machine 19

Figure 2. 14: Concern of cross-contamination & hygiene in common areas 20

Figure 2. 15: Importance of having environmentally friendly features 21

Figure 2. 16: Concern of noise level 22

Figure 2. 17: Recommendations to other organizations 23

Figure 3. 1: House of Quality 33

Figure 4. 1: Black Box Model of the Semi-automated shoe cleaning machine 36

Figure 4. 2: Component Hierarchy of Semi-automated shoe cleaning machine 37

Figure 4. 3: Cluster function of energy flow of Semi-automated shoe cleaning machine 38

Figure 4. 4: Cluster function of energy flow of Semi-automated shoe cleaning machine 38

Figure 4. 5: Cluster function of energy flow of Semi-automated shoe cleaning machine 39

Figure 5. 1: Base Plate 40

Figure 5. 2: Rotating Brush with Nylon fiber Bristle 41

Figure 5. 3: Polishing Foam of Polyurethane material 41

Report Page xii PDF Page 19 / 151

Figure 5. 4: Frame 42

Figure 5. 5: DC motor(24volt) 42

Figure 5. 6: Side Brush Supporter 43

Figure 5. 7: Worm Wheel 43

Figure 5. 8: Worm Thread 44

Figure 5. 9: Worm Gear Connector 44

Figure 5. 10: Semi-Automated Shoe Cleaner 45

Figure 5. 11: Base 46

Figure 5. 12: Total Deformation of Base 47

Figure 5. 13: Equivalent Strain 48

Figure 5. 14: Equivalent Elastic Stress 49

Figure 5. 15: Safety Factor of Base 50

Figure 5. 16: Fatigue Life 51

Figure 5. 17: Forces on Frame 52

Figure 5. 18: Total Deformation 53

Figure 5. 19: Equivalent Strain 54

Figure 5. 20: Equivalent Elastic Stress 55

Figure 5. 21: Safety Factor 56

Figure 5. 22: Fatigue Life 57

Figure 5. 23: Applied load 58

Figure 5. 24: Total Deformation 59

Figure 5. 25: Equivalent Strain 60

Figure 5. 26: Equivalent Elastic Stress 61

Figure 5. 27: Safety Factor 62

Figure 5. 28: Fatigue Life 63

Figure 5. 29: Forces on Worm-Gear Connector 64

Figure 5. 30: Total Deformation 65

Figure 5. 31: Equivalent strain 66

Figure 5. 32: Equivalent Elastic Stress 67

Figure 5. 33: Safety Factor 68

Figure 5. 34: Fatigue Life of Worm-Gear Connector 69

Report Page xiii PDF Page 20 / 151

Figure 5. 35: Load Applied to Side-Brush-Support 70

Figure 5. 36: Total deformation of Side-Brush-Support 71

Figure 5. 37: Equivalent Strain of Side-Brush-Support 72

Figure 5. 38: Equivalent Elastic Stress of Side-Brush-Support 73

Figure 5. 39: Safety Factor of Side-Brush-Support 74

Figure 5. 40: Fatigue Life of Side-Brush-Support 75

Figure 8. 1: Break-Even Analysis 114

Report Pages 1-5 PDF Pages 21-25 / 151

Chapter 01

Introduction

1.1Product Design

Product design is the process of creating new products or services, or improving existing ones, through strategic and tactical activities focused on customer needs and market demand. A design must balance its goals and constraints while accounting for aesthetic, functional, economic, and social considerations.

Effective product design combines ergonomics, usability, and manufacturing feasibility. It uses analysis and problem-solving to translate user needs into an engineered solution, balancing the factors that shape how a product looks, works, is produced, and interacts with its environment.

Ergonomics

Usability

Manufacturing feasibility

1.2Proposed Product Ideas

The team initially proposed four product concepts for Product Design Sessional-I.

01

Proposal 01

Multifunctional Canal & River Cleaning Machine

Product concept

This concept removes waste from rivers, canals, and drainage systems to reduce water pollution, protect aquatic life, prevent blockages and flooding, and support safer water supplies.

Main components

Waste-carrying conveyor
Disinfectant sprayer
Carrier vehicle

Notable features

Collects solid and semi-solid waste floating on the water.
Automates the waste-collection conveyor.
Stores collected waste in an ejectable, transportable basket.
Uses a remotely controlled carrier vehicle.
Allows the sprayer, conveyor, and carrier vehicle to operate independently.

Target market

Government organizations such as city corporations, municipalities, and water-management authorities, as well as non-government organizations working to prevent water pollution and maintain ecological balance.

02

Proposal 02

Multi-Functional Cleaner

Product concept

A single machine designed to handle several cleaning operations, reducing the need to purchase and store separate devices for different household cleaning tasks.

Main components

Motors and rotating shafts
Brush rollers
Polishing and mopping pad
Detergent sprayer
Water tank
Suction nozzle
Vacuum chamber with exhaust port
Power source

Notable features

Versatility: Performs several cleaning operations with one machine.
Wet and dry cleaning: Adapts to the cleaning method required by the situation.
Ergonomics: Supports comfortable operation.
Accessories: Uses detachable parts for easier handling and task-specific setup.

Target market

Busy households, working professionals, elderly users seeking convenience, apartment residents with limited storage, and pet owners who need frequent floor-cleaning solutions.

03

Proposal 03

Pedal-Powered Dishwasher

Product concept

A manually operated dishwasher that cleans dishes without electricity by using two counter-rotating discs around a stationary rack.

Pedal motion is transferred through a rack-and-pinion mechanism to a vertical shaft. The shaft rotates the internal and external discs in opposite directions, creating water jets around dishes held in a rack that exposes most surfaces to the flow.

Main components

Container
Internal and external rotating discs
Rack
Shaft
Gear system
Pedal and sprockets

Notable features

Uses a simple mechanical system.
Provides a low-cost design.
Can use pedal power, with an optional motor.
Targets a capacity of at least 30 dishes or plates in approximately 10 minutes.

Target market

Households and restaurants, particularly busy restaurants that need to clean dishes quickly and consistently between service cycles.

04

Proposal 04

Semi-Automated Shoe Cleaning Machine

Selected proposal

A faster and more convenient way to clean and polish shoes at building entrances or designated cleaning zones, helping prevent dirt transfer and reducing manual cleaning effort.

An adjustable drawer-like sole-cleaning chamber uses high-speed roller brushes to remove debris. Multi-axis synthetic brushes clean the shoe upper, while a spring-mounted sponge on a vibrating plate follows the shoe surface during polishing.

Main components

Shoe-sole cleaning chamber
Brush-cleaning chamber
Shoe-shining chamber

Notable features

Provides adjustable brushes for cleaning and polishing.
Applies polishing spray automatically.
Reduces manual shoe-cleaning effort.
Cleans and shines both the upper and sole.
Removes dry or wet dirt from the sole.
Supports a cleaner and more hygienic environment.

Target market

Corporate offices, hotels, transportation hubs, healthcare facilities, retail spaces, luxury residences, government buildings, and event venues where cleanliness, convenience, and a professional appearance matter.

1.3Selected Proposal

Final concept

Semi-Automated Shoe Cleaning Machine

Proposal 04

After reviewing the four ideas with the course teachers, the fourth proposal was approved as the team project.

1.3.1Reasons for Selection

The selected concept serves corporate offices, hotels, transportation hubs, and other high-traffic facilities where clean footwear supports a professional appearance and better hygiene. It saves time for staff, visitors, and guests by cleaning and polishing footwear with minimal manual effort. The combination of convenience, cleanliness, and a distinctive product concept gives the machine strong potential to attract customer and market interest.

Report Pages 6-25 PDF Pages 26-45 / 151

Chapter 02

Understanding Customer Needs Through Survey

2.1Introduction

Clean shoes support a professional appearance, but manual cleaning can be inconvenient during a busy day and difficult to arrange at short notice. Rain, dust, and daily travel can soil footwear quickly, creating demand for a fast and accessible cleaning solution.

The survey explored cleaning habits, pain points, desired product features, workplace placement, maintenance expectations, hygiene, sustainability, noise, and willingness to recommend a semi-automated shoe-cleaning machine.

Corporate officers Teachers, doctors, and busy professionals Bank and transport-station personnel

2.2Survey Locations

01

Bangladesh University of Engineering and Technology (BUET)

Palashi, Dhaka-1000, Bangladesh

02

Bright River Bangladesh Ltd.

Al-Razi Complex, 3rd Floor, Purana Paltan, Dhaka-1000, Bangladesh

03

Rural Development Project of Jamalpur

Level 03, REDC Building, LGED Headquarters, Agargaon, Dhaka-1207, Bangladesh

04

BRAC Bank PLC, Anik Tower

220/B, Tejgaon-Gulshan Link Road, Tejgaon, Dhaka-1208, Bangladesh

05

University of Dhaka

Nilkhet Road, Dhaka-1000, Bangladesh

06

Pridesys IT Ltd.

R&D Center, Level 11, Software Technology Park, Vision 2021 Tower, Dhaka-1215, Bangladesh

2.3Survey Results

The survey collected responses from 34 participants. Each question below includes the original response table and the corresponding chart from the report.

34

Participants

62%

Interested in automatic cleaning

76%

Prefer a portable machine

79%

Have not seen a similar product

68%

Want quiet operation

94%

Likely to recommend

A

Current behavior and pain points

Q1

How often do you clean your shoes?

Leading response: Weekly - 38%

Response options Daily Weekly Monthly Quarterly

Table 2. 1: Time period of cleaning shoes

Table 2. 1: Time period of cleaning shoes
Option	Responses	Percent
Daily	6	18%
Weekly	13	38%
Monthly	10	29%
Quarterly	5	15%

Pie chart for survey question 1: Time period of cleaning shoes — Figure 2. 1: Time period of cleaning shoes

Q2

How do you currently clean your shoes?

Leading response: Hand wash - 47%

Response options Hand wash Wet wipes Professional cleaning

Table 2. 2: Current cleaning methods

Table 2. 2: Current cleaning methods
Option	Responses	Percent
Hand wash	16	47%
Wet wipes	14	41%
Professional cleaning	4	12%

Pie chart for survey question 2: Current cleaning methods — Figure 2. 2: Current cleaning methods

Q3

How much do you spend on a single shoe cleaning?

Leading response: Under 50/= - 79%

Response options Under 50/= 50-100/= 100-150/= 150-200/= Over 200/=

Table 2. 3: Cost of single shoe cleaning

Table 2. 3: Cost of single shoe cleaning
Option	Responses	Percent
Under 50/=	27	79%
50-100/=	5	15%
100-150/=	1	3%
150-200/=	1	3%
Over 200/=	0	0%

Pie chart for survey question 3: Cost of single shoe cleaning — Figure 2. 3: Cost of single shoe cleaning

Q4

What challenges do you face when cleaning your shoes?

Leading response: Time-consuming - 62%

Response options Time-consuming Ineffective Unavailability

Table 2. 4: Challenges of cleaning shoes

Table 2. 4: Challenges of cleaning shoes
Option	Responses	Percent
Time-consuming	21	62%
Ineffective	9	26%
Unavailability	4	12%

Pie chart for survey question 4: Challenges of cleaning shoes — Figure 2. 4: Challenges of cleaning shoes

Q5

How satisfied are you with your current shoe cleaning method?

Leading response: Neutral - 64%

Response options Very satisfied Satisfied Neutral Dissatisfied Very dissatisfied

Table 2. 5: Satisfaction with current cleaning method

Table 2. 5: Satisfaction with current cleaning method
Option	Responses	Percent
Very satisfied	1	3%
Satisfied	5	15%
Neutral	22	64%
Dissatisfied	4	12%
Very dissatisfied	2	6%

Pie chart for survey question 5: Satisfaction with current cleaning method — Figure 2. 5: Satisfaction with current cleaning method

B

Product interest and purchase preferences

Q6

Would you be interested in a machine that cleans your shoes automatically?

Leading response: Yes - 62%

Response options Yes No Maybe

Table 2. 6: Interest in an automatic cleaning machine

Table 2. 6: Interest in an automatic cleaning machine
Option	Responses	Percent
Yes	21	62%
No	1	3%
Maybe	12	35%

Pie chart for survey question 6: Interest in an automatic cleaning machine — Figure 2. 6: Interest in an automatic cleaning machine

Q7

What features would be most important to you in a shoe cleaning machine?

Leading response: Effectiveness - 29%

Response options Speed of cleaning Effectiveness Ease of use Eco-friendliness

Table 2. 7: Important machine features

Table 2. 7: Important machine features
Option	Responses	Percent
Speed of cleaning	9	27%
Effectiveness	10	29%
Ease of use	9	26%
Eco-friendliness	6	18%

Pie chart for survey question 7: Important machine features — Figure 2. 7: Important machine features

Q8

Would you prefer a portable machine or one that stays in one place?

Leading response: Portable - 76%

Response options Portable Stationary No preference

Table 2. 8: Portability preference

Table 2. 8: Portability preference
Option	Responses	Percent
Portable	26	76%
Stationary	4	12%
No preference	4	12%

Pie chart for survey question 8: Portability preference — Figure 2. 8: Portability preference

Q9

What factors influence your decision to purchase a new cleaning device?

Leading response: Reviews - 65%

Response options Reviews Brand reputation Recommendations

Table 2. 9: Factors influencing a purchase decision

Table 2. 9: Factors influencing a purchase decision
Option	Responses	Percent
Reviews	22	65%
Brand reputation	5	15%
Recommendations	7	20%

Pie chart for survey question 9: Factors influencing a purchase decision — Figure 2. 9: Factors influencing a purchase decision

Q10

Have you seen similar products on the market?

Leading response: No - 79%

Response options Yes No

Table 2. 10: Availability of similar products

Table 2. 10: Availability of similar products
Option	Responses	Percent
Yes	7	21%
No	27	79%

Pie chart for survey question 10: Availability of similar products — Figure 2. 10: Availability of similar products

Q11

What additional features would make a shoe cleaning machine more appealing to you?

Leading response: Easy to operate - 47%

Response options Automation Disinfectant Shiner Easy to operate

Table 2. 11: Additional features that increase product appeal

Table 2. 11: Additional features that increase product appeal
Option	Responses	Percent
Automation	11	32%
Disinfectant	7	21%
Shiner	0	0%
Easy to operate	16	47%

Pie chart for survey question 11: Additional features that increase product appeal — Figure 2. 11: Additional features that increase product appeal

C

Workplace deployment and advocacy

Q12

In which workplace environment would the shoe cleaning machine be used most?

Leading response: Staff changing rooms - 50%

Response options Office lobby Staff changing rooms Warehouse/factory Hospital entryway

Table 2. 12: Likely workplace environment

Table 2. 12: Likely workplace environment
Option	Responses	Percent
Office lobby	14	41%
Staff changing rooms	17	50%
Warehouse/factory	1	3%
Hospital entryway	2	6%

Pie chart for survey question 12: Likely workplace environment — Figure 2. 12: Likely workplace environment

Q13

How often would you expect to perform maintenance on such a machine?

Leading response: Quarterly - 35%

Response options Weekly Monthly Quarterly Yearly

Table 2. 13: Expected maintenance period

Table 2. 13: Expected maintenance period
Option	Responses	Percent
Weekly	6	18%
Monthly	8	23%
Quarterly	12	35%
Yearly	8	24%

Pie chart for survey question 13: Expected maintenance period — Figure 2. 13: Expected maintenance period

Q14

How concerned are you about cross-contamination and hygiene in common areas where the machine might be placed?

Leading response: Very concerned - 53%

Response options Very concerned Somewhat concerned Not concerned

Table 2. 14: Concern about cross-contamination and hygiene

Table 2. 14: Concern about cross-contamination and hygiene
Option	Responses	Percent
Very concerned	18	53%
Somewhat concerned	13	38%
Not concerned	3	9%

Pie chart for survey question 14: Concern about cross-contamination and hygiene — Figure 2. 14: Concern about cross-contamination and hygiene

Q15

How important are environmentally friendly features such as energy efficiency or low water consumption?

Leading response: Important - 53%

Response options Extremely important Important Neutral Not important

Table 2. 15: Importance of environmentally friendly features

Table 2. 15: Importance of environmentally friendly features
Option	Responses	Percent
Extremely important	13	38%
Important	18	53%
Neutral	3	9%
Not important	0	0%

Pie chart for survey question 15: Importance of environmentally friendly features — Figure 2. 15: Importance of environmentally friendly features

Q16

Would noise levels be a concern in an area with frequent foot traffic?

Leading response: Yes, it should be quiet - 68%

Response options Yes, it should be quiet Noise is acceptable if it is efficient No preference

Table 2. 16: Concern about noise level

Table 2. 16: Concern about noise level
Option	Responses	Percent
Yes, it should be quiet	23	68%
Noise is acceptable if it is efficient	9	26%
No preference	2	6%

Pie chart for survey question 16: Concern about noise level — Figure 2. 16: Concern about noise level

Q17

How likely are you to recommend such a machine to other organizations if it meets your expectations?

Leading response: Very likely / Likely - 47%

Response options Very likely Likely Neutral Unlikely

Table 2. 17: Likelihood of recommending the machine

Table 2. 17: Likelihood of recommending the machine
Option	Responses	Percent
Very likely	16	47%
Likely	16	47%
Neutral	2	6%
Unlikely	0	0%

Pie chart for survey question 17: Likelihood of recommending the machine — Figure 2. 17: Likelihood of recommending the machine

2.4Customer Requirement Evaluation

The survey findings were consolidated into eight customer requirements and evaluated on a ten-point importance scale.

Table 2. 18: Relative importance of customer requirements

Table 2. 18: Relative importance of customer requirements
Customer requirement	Score / 10	Relative importance
Easy to operate	10
Portability	8
Automation	7
Eco-friendly	8
Operating speed	9
Effectiveness	8
Low cost	9
Good stability	8

Priority signal: Easy operation received the maximum score of 10, followed by operating speed and low cost at 9. Portability, eco-friendliness, effectiveness, and stability each scored 8, while automation scored 7.

2.5Conclusion

The Google Forms survey produced a varied but consistent set of customer priorities. Respondents favored an easy-to-operate, portable, quiet, hygienic, and affordable machine with effective cleaning performance. These findings establish the customer requirements that guide the product design and the quality-function-deployment analysis in the following chapter.

Report Page 26 PDF Page 46 / 151

Chapter 03

Incorporating the Voice of Customer in Product Design with Quality Function Deployment (QFD)

3.1Introduction

According to the Japanese, Quality Function Deployment (QFD) is "Listen to the voice of the market (customers)," which refers to understanding the design problem to create a high-quality product. One must comprehend the design problem thoroughly. The process of turning user requests and requirements into a technical description of what has to be created is known as Quality Function Deployment, or QFD. The goal of QFD is to create a product that meets the customer's exact needs, rather than focusing on the builder's existing skills or knowledge.

In QFD, multi-skilled teams work together to understand customer needs and define technical requirements for each stage. The key benefits of QFD include a strong focus on customer needs, ensuring that products are developed based on what the customer values rather than depending solely on technical expertise. QFD promotes teamwork by bringing together multi-skilled teams, which enhances a deeper understanding of the project requirements. This approach also improves production efficiency and helps reduce development time and costs. The QFD process emphasizes listening to customers, refining specifications, and assessing how well both the company and competitors meet customer expectations.

Since we have already collected customer needs by conducting the customer survey, the next step in the QFD technique is to evaluate the importance of each of the customers' requirements (out of a 10 scale). This is accomplished by generating a weighting factor.

Report Page 27 PDF Page 47 / 151

3.2Customer Requirement and Engineering Requirement

In order to meet the customer requirements, the necessary engineering requirements and their relationship is depicted in the following table:

Table 3. 1: Relationship Explanation

Customer Requirement	Engineering Requirement	Relationship	Explanation
Easy to Operate	Chamber Assembly	Strong	Three different chambers allow us to operate the cleaning process more precisely.
Easy to Operate	Vibrating Plate	Moderate	This segment ensures the shining process more significantly.
Portability	Chamber Assembly	Strong	Chamber assembly has made the product more compacted which enhances the product portability.
Portability	Manufacturing Cost	Moderate	The presence of separate chamber for separate process increases the manufacturing cost slightly.
Automation	Cleaning Design	Strong	An improved cleaning design ensures effective automation of the process.
	Roller Brush	Strong	Proper functionality of roller brush improves the process automation significantly.
	Vibrating Plate	Strong	Improved functionality of vibrating plate improves the process automation significantly.
	Operational Cost	Weak	Ensuring self-automated process slightly increases the operational cost.
	Manufacturing Cost	Strong	Implementing automated processes tends to raise manufacturing cost.
Eco-Friendly	Brush Material	Strong	Selecting eco-friendly materials for brushes reduces environmental impact.
Eco-Friendly	Shiner	Moderate	Choosing eco-friendly materials for shiner promotes sustainability while maintaining effective performance.
Operating Speed	Strength of Body	Weak	A higher operating speed can slightly strain body's strength.
	Manufacturing Cost	Moderate	Increasing operating speed may raise manufacturing cost.
	Operational Cost	Moderate	Increasing operating speed may raise operational cost.
	Roller Brush	Moderate	Operating speed of roller brush influences its cleaning efficiency.
	Cleaning Design	Moderate	The design of a cleaning system is optimized for operational speed to maximize efficiency.
	Shiner	Moderate	The operating speed of a shiner affects its polishing effectiveness.
Effectiveness	Brush Material	Strong	The choice of brush material significantly impacts its effectiveness, influencing durability, compatibility.
	Manufacturing Cost	Moderate	Enhancing effectiveness typically results in increased manufacturing cost.
	Operational Cost	Moderate	Improving effectiveness typically results in increased operational cost.
	Roller Brush	Strong	Different types of roller brush enhance effectiveness by catering to specific cleaning needs.
	Cleaning Design	Strong	Different cleaning design ensures effectiveness while minimizing time and effort.
	Shiner	Strong	A shiner provides effectiveness by utilizing specialized ingredients that create a protective layer, enhance shine and repel dirt.
Low Cost	Brush Material	Moderate	Using lower cost material reduces overall expenses.
	Manufacturing Cost	Strong	Manufacturing cost can be minimized through efficient process and the use of lower cost material.
	Operational Cost	Moderate	Minimizing operational cost leads to lower overall cost.
	Cleaning Design	Strong	An effective cleaning design minimizes resource consumption which ensures lowering of overall costs.
	Chamber Assembly	Moderate	Chamber assembly can lead to lower cost by reducing number of components needed and minimizing assembly time.
Good Stability	Strength of Body	Strong	The strength of body ensures good stability by providing necessary support and resistance to external forces.
	Vibrating Plate	Strong	A vibrating plate contributes to good stability by distributing weight evenly.
	Roller Brush	Moderate	A roller brush partially provides good stability by maintaining consistent contact with surfaces.
	Chamber Assembly	Moderate	Chamber assembly contributes to good stability by securely integrating components.

Report Pages 28–33 PDF Pages 48–53 / 151

3.3Quality Function Deployment's House of Quality

QFD Matrix Relationships

Defines the impact of engineering specifications on customer requirements.

Relationship Level	Weight Value
Strong	9
Moderate	3
Weak	1
No Relationship	0

Roof Technical Correlations

Inter-parameter correlations between engineering requirements.

Symbol	Correlation Type
+ +	Strongly Positive
+	Positive
—	No Relation
-	Negative
- -	Strongly Negative

Report Page 34 PDF Page 54 / 151

3.4Conclusion

QFD gives a deeper understanding of the problem. It helps to build up consensus within an organization on the measurement systems and performance specifications that represent the demands of the customers. Strategically designed to enhance competitiveness for a company, QFD also identifies and prioritizes actions needed to satisfy the expressed and implied needs of the customer. We were able to develop our QFD process in relatively quick fashion because we were under a very tight schedule—normally, QFD is a very involved, lengthy process. Although this apparently slows down the design phase, time utilized at the front end in gathering information saves time further down the process.

Report Pages 35-39 PDF Pages 55-59 / 151

Chapter 04

Functional Decomposition

From a single system boundary to three coordinated machine assemblies.

4.1Introduction

Functional decomposition is an analytical approach that breaks a complex system into manageable component functions and processes. It provides a top-down view of increasingly detailed functionality, helping designers understand how each part contributes to the product's overall purpose.

01

Identify the primary function

Distill the design's core purpose into a simple statement. Represent the system as a black box whose boundary is defined by energy, material, and information inputs and outputs.

02

Develop sub-functions

Break the primary function into the specific sub-functions needed to support the system's purpose, ensuring that each component contributes to the main goal.

03

Organize sub-functions

Arrange the sub-functions in a logical sequence so that the process flow remains clear, especially when several elements interact.

04

Refine sub-functions

Examine each sub-function for further decomposition so every aspect of the function is addressed and the overall system remains coherent.

4.2Black Box Model

A black box model represents a system through its energy, material, and information inputs and outputs without exposing internal details. It gives a high-level account of what the machine does before the design is decomposed into individual mechanisms.

Figure 4.1: Black Box Model of the Semi-Automated Shoe Cleaning Machine The black box model summarizes the machine's energy input and its dust and kinetic-energy outputs. Open full-resolution diagram

4.3Component Hierarchy

A component hierarchy separates the product into major subassemblies and then lists the components within each one. When the functions of the subassemblies are satisfied, the primary system function is satisfied. Repeating this process creates a function tree that is quick to understand, although it does not fully describe interactions among subassemblies.

Figure 4.2: Component Hierarchy of the Semi-Automated Shoe Cleaning Machine The hierarchy groups the machine into brush-cleaning, shining, and shoe-sole-cleaning subassemblies. Open full-resolution diagram

4.4Cluster Function Structure

The cluster function structure expands the hierarchy into functional flows. The diagrams below trace how energy and material pass through the brush-cleaning, shining, and shoe-sole-cleaning assemblies.

Flow legend: thin arrows show energy; bold arrows show material.

Figure 4.3: Energy Flow for the Brush-Cleaning Assembly Electrical energy drives the upper motor and produces the linear and rotary motion used by the brush fibers. Open full-resolution diagram

Figure 4.4: Energy and Material Flow for the Shining Assembly Mechanical and electrical inputs coordinate the mold sponge, vibrating plate, and shiner dispenser. Open full-resolution diagram

Figure 4.5: Energy Flow for the Shoe-Sole-Cleaning Assembly Electrical energy is converted into the roller-brush motion used to clean the shoe sole. Open full-resolution diagram

4.5Conclusion

Together, the black box model, component hierarchy, and cluster function structure provide a complete functional view of the semi-automated shoe cleaning machine. The black box defines the system boundary, the hierarchy identifies each part's role, and the cluster diagrams show how material and energy move through the assemblies.

This progression from system-level purpose to component-level flow supports a well-structured, efficient, functional, and user-friendly design.

Report Page 40 PDF Page 60 / 151

Chapter 05

Design Analysis

5.1Introduction

The systematic process of designing, which includes tasks such as gathering information, planning, and effective communication, is often referred to as design analysis. Product development is typically divided into several stages, each involving specific activities. These stages frequently require different analyses, such as market research to understand consumer behavior or financial evaluations to identify risks and investment opportunities. In the case of the “Automated Shoe Cleaner,” certain design evaluations are essential to transform the concept into a tangible product.

A critical phase in product development is design analysis, which helps minimize or eliminate reliance on extensive physical prototyping and testing. Through detailed research into customer needs, material selection, manufacturing methods, and assembly processes, a prototype for the “Automated Shoe Cleaner” has been developed. This section will provide an overview of the “Automated Shoe Cleaner” components skillfully designed using SolidWorks software. Additionally, a detailed stress analysis, conducted using Ansys software, will be presented to ensure the product's design is both robust and reliable.

5.2Final Design and Parts of "Semi-Automated Shoe Cleaner"

5.2.1Parts of "Automated Shoe Cleaner"

Report Page 41 PDF Page 61 / 151

Figure 5. 2: Rotating Brush with Nylon fiber Bristle

Figure 5. 3: Polishing Foam of Polyurethane material

Report Page 42 PDF Page 62 / 151

Report Page 43 PDF Page 63 / 151

Report Page 44 PDF Page 64 / 151

Report Page 45 PDF Page 65 / 151

5.2.2Final Design of "semi-Automated shoe Cleaner"

Figure 5. 10: Semi-Automated Shoe Cleaner

Report Page 46 PDF Page 66 / 151

5.3Static Structural Analysis (Ansys) for the proposed design

5.3.1Static Structural Analysis for Base

Table 5. 1: Load Applied of Base

Types	Force
X component	0N
Y component	-100N
Z component	0N

Report Page 47 PDF Page 67 / 151

5.3.1.1Total deformation

Table 5. 2 Total deformation of Base

Name of the Extremity	Total Deformation (mm)
Maximum	4.9853E-5
Minimum	0

Report Page 48 PDF Page 68 / 151

5.3.1.2Equivalent Strain of Base

Table 5. 3: Equivalent Strain of Base

Name of the Extremity	Equivalent Strain (mm/mm)
Maximum	4.6213E-7
Minimum	1.3409E-8

Report Page 49 PDF Page 69 / 151

5.3.1.3Elastic Stress (von-Mises Stress) of Base

Table 5. 4: Equivalent Elastic Stress of Base

Name of the Extremity	Equivalent Stress (MPa)
Maximum	0.00011553
Minimum	2.2203E-6

Report Page 50 PDF Page 70 / 151

5.3.1.4Safety Factor

Table 5. 5: Safety Factor of base

Name of the Extremity	Safety Factor
Maximum	15
Minimum	15

Report Page 51 PDF Page 71 / 151

5.3.1.5Fatigue Life

Table 5. 6: Fatigue Life of Base

Name of the Extremity	Fatigue Life
Maximum	1E+12
Minimum	1E+12

Report Page 52 PDF Page 72 / 151

5.3.2Static Structural Analysis for Frame

Table 5. 7: Load Applied of Frame

Types	Force
X component	0N
Y component	-120N
Z component	0N

Report Page 53 PDF Page 73 / 151

5.3.2.1Total deformation

Table 5. 8:Total deformation of Frame

Name of the Extremity	Total Deformation (mm)
Maximum	43.597
Minimum	0

Report Page 54 PDF Page 74 / 151

5.3.2.2Equivalent Strain of Frame

Table 5. 9: Equivalent Strain of Frame

Name of the Extremity	Equivalent Strain (mm/mm)
Maximum	0.032277
Minimum	7.0703E-7

Report Page 55 PDF Page 75 / 151

5.3.2.3Equivalent Elastic Stress (von Mises Stress)

Table 5. 10: Equivalent Elastic Stress of Base

Name of the Extremity	Equivalent Stress (MPa)
Maximum	7.7409
Minimum	6.6195E-5

Report Page 56 PDF Page 76 / 151

5.3.2.4Safety Factor

Table 5. 11: Safety Factor of Frame

Name of the Extremity	Safety Factor
Maximum	15
Minimum	15

Report Page 57 PDF Page 77 / 151

5.3.2.5Fatigue Life

Table 5. 12: Fatigue Life of Frame

Name of the Extremity	Fatigue Life
Maximum	1E+12
Minimum	1E+12

Report Page 58 PDF Page 78 / 151

5.3.3Static Structural Analysis for Shaft

Table 5. 13: Load Applied of Shaft

Types	Force(N)/ Moment (N.mm)
X component	100N.mm
Y component	-100N
Z component	0N

Report Page 59 PDF Page 79 / 151

5.3.3.1Total deformation

Table 5. 14: Total deformation of Shaft

Name of the Extremity	Total Deformation (mm)
Maximum	0.039718
Minimum	0

Report Page 60 PDF Page 80 / 151

5.3.3.2Equivalent Strain

Table 5. 15: Equivalent Strain of Shaft

Name of the Extremity	Equivalent Strain (mm/mm)
Maximum	5.4159E-5
Minimum	2.2399E-7

Report Page 61 PDF Page 81 / 151

5.3.3.3Equivalent Elastic Stress (von Mises Stress)

Table 5. 16: Equivalent Elastic Stress of Shaft

Name of the Extremity	Equivalent Stress (MPa)
Maximum	9.6063
Minimum	0.022431

Report Page 62 PDF Page 82 / 151

5.3.3.4Safety Factor

Table 5. 17: Safety Factor of Shaft

Name of the Extremity	Safety Factor
Maximum	15
Minimum	15

Report Page 63 PDF Page 83 / 151

5.3.3.5Fatigue Life

Table 5. 18: Fatigue Life of Shaft

Name of the Extremity	Fatigue Life
Maximum	10000
Minimum	10000

Report Page 64 PDF Page 84 / 151

5.3.4Static Structural Analysis for Worm-Gear Connector

Figure 5. 29: Forces on Worm-Gear Connector

Table 5. 19: Load Applied of Worm-Gear Connector

Types	Force(N)/ Moment (N.mm)
X component	1000N.mm
Y component	0N
Z component	0N

Report Page 65 PDF Page 85 / 151

5.3.4.1Total deformation

Table 5. 20: Total deformation of Worm-Gear Connector

Name of the Extremity	Total Deformation (mm)
Maximum	0.013015
Minimum	0

Report Page 66 PDF Page 86 / 151

5.3.4.2Equivalent Strain

Table 5. 21: Equivalent Strain of Worm-Gear Connector

Name of the Extremity	Equivalent Strain (mm/mm)
Maximum	6.7292E-5
Minimum	3.4339E-6

Report Page 67 PDF Page 87 / 151

5.3.4.3Equivalent Elastic Stress (von Mises Stress)

Table 5. 22: Equivalent Elastic Stress of Worm-Gear Connector

Name of the Extremity	Equivalent Stress (MPa)
Maximum	12.42
Minimum	0.22798

Report Page 68 PDF Page 88 / 151

5.3.4.4Safety Factor

Table 5. 23:Safety Factor of Worm-Gear Connector

Name of the Extremity	Safety Factor
Maximum	15
Minimum	15

Report Page 69 PDF Page 89 / 151

5.3.4.5Fatigue Life

Figure 5. 34: Fatigue Life of Worm-Gear Connector

Table 5. 24:Fatigue Life of Worm-Gear Connector

Name of the Extremity	Fatigue Life
Maximum	10000
Minimum	10000

Report Page 70 PDF Page 90 / 151

5.3.5Static Structural Analysis for Side-Brush-Support

Figure 5. 35: Load Applied to Side-Brush-Support

Table 5. 25: Load Applied to Side-Brush-Support

Types	Force
X component	-20N
Y component	-20N
Z component	0N

Report Page 71 PDF Page 91 / 151

5.3.5.1Total deformation

Figure 5. 36: Total deformation of Side-Brush-Support

Table 5. 26: Total deformation of Side-Brush-Support

Name of the Extremity	Total Deformation (mm)
Maximum	0.2057
Minimum	0

Report Page 72 PDF Page 92 / 151

5.3.5.2Equivalent Strain

Figure 5. 37: Equivalent Strain of Side-Brush-Support

Table 5. 27: Equivalent Strain of Side-Brush-Support

Name of the Extremity	Equivalent Strain (mm/mm)
Maximum	0.013683
Minimum	2.6385E-5

Report Page 73 PDF Page 93 / 151

5.3.5.3Equivalent Elastic Stress (von Mises Stress)

Figure 5. 38: Equivalent Elastic Stress of Side-Brush-Support

Table 5. 28: Equivalent Elastic Stress of Side-Brush-Support

Name of the Extremity	Equivalent Stress (MPa)
Maximum	3.412
Minimum	0.005077

Report Page 74 PDF Page 94 / 151

5.3.5.4Safety Factor

Figure 5. 39: Safety Factor of Side-Brush-Support

Table 5. 29:Safety Factor of Side-Brush-Support

Name of the Extremity	Safety Factor
Maximum	15
Minimum	15

Report Page 75 PDF Page 95 / 151

5.3.5.5Fatigue Life

Figure 5. 40: Fatigue Life of Side-Brush-Support

Table 5. 30: Fatigue Life of Side-Brush-Support

Name of the Extremity	Fatigue Life
Maximum	1E+12
Minimum	1E+12

The ANSYS analysis showed insignificant deformation, thus supporting our choice of materials.

Report Page 76 PDF Page 96 / 151

Chapter 06

Qualitative Analysis of Material, Manufacturing Process, and Joining Process Selection

6.1Introduction

When developing a product, choosing the right material is one of the key decisions. This selection has a direct impact on performance, durability, appearance, cost, and environmental footprint. While quantitative methods focus on measurable traits like strength, density, and heat conductivity, qualitative approaches take a broader and more subjective view. They consider factors that are not easily measured but still play a crucial role in the product's overall success.

Qualitative analysis assesses the non-technical aspects of choosing materials. This includes factors like user experience, manufacturing limitations, sustainability, and aesthetic choices. Designers evaluate how the material fits the product's intended use. They also consider whether it matches the brand's identity. Additionally, the material's appeal to the end-users is considered.

6.2Qualitative Analysis of Material Selection for Different Sections

In product design, the selection of materials is one of the most critical decisions that will ultimately determine the product's performance, cost, and manufacturability. However, material selection cannot be approached uniformly across the entire product. Different sections or components of a product often have different requirements in terms of strength, durability, weight, thermal behavior, and environmental resistance.

The qualitative analysis of material selection for different sections of a product involves evaluating the specific demands of each part of the design, rather than choosing a single material for the entire product. This approach ensures that the materials selected optimize the performance of each section while considering factors such as design complexity, manufacturability, environmental impact, and cost-effectiveness.

Report Page 77 PDF Page 97 / 151

Table 6. 1: Qualitative Analysis of Material Selection for Different Sections

Section	Sub-section	Parts	Material Selection	Other Material Options	Reasons Behind Selection
Brush Cleaning Part	Base	Base	Nylon	Polycarbonate, ABS	Impact resistance, lightweight
	Brush	Nylon Brush Fiber	Nylon 6	Polypropylene, Polyester (PET)	Durability, flexibility, water resistance
	Motor	DC Motor	Gear Motor	Brushed DC Motor	High torque, speed regulation
	Mechanism	Worm Gear	Mild Steel	High-Speed Steel, Alloy Steel	Cost-effective, durability
Shiner Part	Shiner Mechanism	Vibrating Plate	Stainless Steel	Mild Steel, Aluminum Alloy	Easy to clean, high durability
	Shiner Mechanism	Mold Sponge	Polyurethane Foam	Rubber, Felt	Good cushioning, lightweight
	Shiner Mechanism	Dispenser	Mild Steel	Cast Iron, Mild	Lightweight, chemical resistance
Shoe Sole Cleaning Part	Roller Mechanism	Roller Brush	Nylon Bristle	Polypropylene, PVC	Abrasion resistance, flexibility
Shoe Sole Cleaning Part	Base	Base	Stainless Steel	High-Density Polyethylene	Durability, strength

Report Page 78 PDF Page 98 / 151

6.3Qualitative Analysis of Manufacturing Process Selection

The process of selecting materials must be closely aligned with the intended manufacturing process to optimize overall efficiency and quality. Each manufacturing process, whether it's injection molding, casting, forging, or additive manufacturing, has specific material requirements and constraints. These requirements include material form (e.g., solid, powder, sheet), thermal properties, machinability, and ease of processing, all of which influence the final design and production methods.

Table 6. 2: Qualitative Analysis of Manufacturing Process Selection

Section	Sub-section	Parts	Possible Manufacturing Process	Make / Outsource	Process Selection	Reasons Behind Selection
Brush Cleaning Part	Base	Base	Injection Molding, Casting	Make	Injection Molding	Uniformity, cost-effective for complex shapes
	Brush	Nylon Brush Fiber	Extrusion, Injection Molding	Outsource	Extrusion	Better control over fiber thickness
	Motor	DC Motor	Assembly	Outsource	Assembly	More convenient to buy pre-assembled
	Mechanism	Spur Gear	Gear Cutting, Hobbing	Make	Gear Cutting	Achieves high dimensional accuracy
Shiner Part	Shiner Mechanism	Mold Sponge	Die Cutting	Make	Die Cutting	Cost-effective for soft materials
Shiner Part	Motor	Motor	Assembly	Outsource	Assembly	More convenient to buy pre-assembled
Shoe Sole Cleaning Part	Roller Mechanism	Roller Brush	Extrusion, Milling	Outsource	Extrusion	Cost-effective for brush production
Shoe Sole Cleaning Part	Base	Base	Bending, Welding	Make	Bending	Durability, easy to form

Report Page 79 PDF Page 99 / 151

6.4Qualitative Analysis of Parts Joining Method Selection

In product design, selecting an appropriate part joining method is crucial for influencing both performance and manufacturability of the final product. The way in which components are joined—whether through welding, adhesive bonding, mechanical fastening, or another technique—affects not only the product's strength and durability but also its cost, assembly time, and overall functionality.

Table 6. 3: Qualitative Analysis of Parts Joining Method Selection

Parts	Type of Joint	Joining Method Options	Joint Selected	Reasons Behind Selection
Base and Casing	Permanent	Brazing, Soldering, Explosion Welding, Friction Stir Welding	Brazing	Cheap, highly available
Base and Bearing	Permanent	Shrink Fitting, Press Fitting, Adhesive Bonding, Welding	Arc Welding	Cost-effective, no requirement of high precision
Motor and Shaft	Temporary	Threaded Connection, Welding, Tapered Connection with Locking Nut	Threaded Connection	Flexibility, easily removable
Bearing and Shaft	Temporary	Shrink Fitting, Press Fitting, Adhesive Bonding, Set Screw, Locking Collars	Press Fitting	Ease of maintenance, good for high-speed applications
Shaft and Gear	Permanent	Welding, Brazing, Adhesive Bonding, Tapered Shaft and Gear	Brazing	Cheap, highly available
Shaft and Wheel	Permanent	Bolted Joint, Adhesive Bonding, Keyed Joint, Welding	Brazing	Cost-effective, simple to execute
Wheel and Crank Shaft	Temporary	Bolted Flange Connection, Spline Connection, Welding	Bolted Flange Connection	High strength, ease of disassembly

Report Page 80 PDF Page 100 / 151

6.5Conclusion

In order to arrive at competent design decisions that balance performance, cost, and manufacturability, qualitative study of material selection, manufacturing procedures, and joining techniques is crucial. We can make sure that every part of the product is optimized for its particular function by assessing elements including functional needs, material compatibility, production capability, environmental impact, and design flexibility.

This rigorous process ensures the product satisfies technical requirements. It is also very environmentally friendly and efficient. It also continues to be affordable for the duration of its life. The design is better balanced when qualitative insights are included in the decision-making process. This reduces possible production and assembly risks while simultaneously increasing overall product quality and manufacturing convenience.

Report Page 81 PDF Page 101 / 151

Chapter 07

Quantitative Analysis of Material Selection with Weighted Average Method

7.1Introduction

The choice and application of materials have a significant impact on the price, performance, and quality while designing a product. We can cut waste, save money, and improve customer happiness by selecting the proper materials, methods and by using them efficiently.

Material selection procedure has a direct impact on the finished product's price, functionality, and sustainability. While developing or designing completely a new or modified product, an engineer has to be more considerate about the properties, aesthetics, functionality, and regulatory compliance. Besides, engineers and designers in the production team have to meet both customer requirements and technical requirements.

To assist decision makers in considering a variety of selection criteria and their interactions and in reaching the best conclusions, straightforward, methodical, and logical techniques or mathematical tools are required. Therefore, quantitative analysis for selection criteria is imperative to manufacture a good product.

There are several methods for quantifying the properties of a material or manufacturing process. Here, in this chapter, we are using the "Digital Logic Method" and "Weighted Average Method" for selecting material based on their performance indices.

Product design is steeped in research, strategy, and business. It considers the end users' needs and goals, as well as market trends and opportunities. It's not just about creating a better-looking product but also the perfect balance between form and function. In this chapter, we will discuss and analyze about:

•Manufacturing process
•Joining process
•Finishing process
•Coloring and aesthetics

Every component has unique properties, design, and requirements. All manufacturing processes are not optimized for AISI 440C Stainless Steel or 1060 mild steel. Different manufacturing processes have their own advantages, disadvantages, and cost effectiveness. The process which is suitable for metallic components won't be suitable for PVC-made components. So, by analyzing the selected process, we have to determine the most optimized process for manufacturing.

Report Page 82 PDF Page 102 / 151

After manufacturing different components, we have to join them. Some components are joined permanently. In that case we will choose the best permanent joining process, and there are some movable components like the slider, for which we have to use a temporary joining process.

Surface finishes and coloring not only make products look presentable and unique, but they also play an important role in ensuring products perform as they are intended to perform and last longer. Finishes provide protection from outside elements, corrosion, wear, and rust. Surface finishes can be applied in a variety of ways: painting and rolling, spraying, electroplating, adhesives, sandblasting, etc.

In this analysis, we will use the weighted average method. Firstly, we will define the properties of process for certain materials, and then the digital logic method will be used for calculating performance index to find out proper processes.

7.2Structural Parts of Semi-automated Shoe Cleaner

Components List

1. Brush Cleaning Part

Base
Nylon Brush Fiber
DC Motor
Shaft
Spur Gear
Worm Gear

2. Shiner Part

Mold Sponge
Shiner
Motor

3. Shoe Sole Cleaning Part

Motor
Roller and Brush
Base

Report Page 83 PDF Page 103 / 151

7.3Equations

a) Equation 7.1: Relative Emphasis Coefficient $$\alpha = \frac{\text{Number of positive decisions acquired by a criterion}}{\text{Total number of positive decisions}}$$

b) Equation 7.2: Scaled Property (Properties to be Maximized) $$\beta_{\text{max}} = \left( \frac{\text{Numerical value of the property}}{\text{Maximum value in the list}} \right) \times 100$$

c) Equation 7.3: Scaled Property (Properties to be Minimized) $$\beta_{\text{min}} = \left( \frac{\text{Minimum value in the list}}{\text{Numerical value of the property}} \right) \times 100$$

d) Equation 7.4: Weighted Score $$\text{Weighted Score} = \text{Relative Emphasis Coefficient } (\alpha) \times \text{Scaled Property } (\beta)$$

e) Equation 7.5: Performance Index $$\text{Performance Index } (\gamma) = \sum_{i=1}^{n} (\alpha_i \cdot \beta_i)$$

7.4Likert Scale

Likert scale was introduced to survey research in 1930. Likert scale is a bipolar scale with interval levels that measure respondent attitudes and opinions. The Likert scale (typically) provides five possible answers to a statement or question that allows respondents to indicate their positive-to-negative strength of agreement or strength of feeling regarding the question or statement.

In this section, we will employ the Likert scale to assess criteria that lack numerical assignments. The scale is provided below:

Table 7. 1: Likert Chart for comparing material selection

Qualitative Rating	Numerical Value
Very Good	5
Good	4
Moderate	3
Poor	2
Very Poor	1

7.5Quantitative Analysis of Material Selection

7.5.1Material Selection for roller shaft

Table 7. 2: List of material properties selected for roller shaft

Property	AISI 316 Stainless Steel	AISI 347 Annealed Stainless Steel	1045 Carbon Steel (Cold Drawn)
Elastic Modulus (GPa)	193	200	205
Shear Modulus (GPa)	77	78	80
Mass Density (kg/m³)	8000	8000	7850
Coefficient of Thermal Expansion (/K)	16.0 x 10⁻⁶	15.6 x 10⁻⁶	11.7 x 10⁻⁶
Compressive Strength (MPa)	1700	1724	310
Approximate Cost (BDT/kg)	500-600	600-700	150-250

Report Page 84 PDF Page 104 / 151

Table 7. 3: Lists of selection criteria with values from Likert scale

Property	AISI 316 Stainless Steel	AISI 347 Annealed Stainless Steel	1045 Carbon Steel (Cold Drawn)
Weldability	5	4	3
Corrosion Resistance	5	5	2
Appearance	5	5	2
Availability	5	4	5

Report Page 85 PDF Page 105 / 151

Table 7. 4: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{10(10-1)}{2} = 45$																																													Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	Positive Decisions	Relative Emphasis ($\alpha$)
Elastic Mod.	1	1	1	1	1	1	1	1	1	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	9	0.2
Shear Mod.	0	−	−	−	−	−	−	−	−	1	1	1	1	1	1	1	1	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	8	0.178
Mass Density	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	−	1	1	1	1	1	1	1	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	7	0.156
Coefficient of Ther. Ex.	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	−	0	1	1	1	1	1	−	−	−	−	−	−	−	−	−	−	−	−	−	−	−	5	0.111
Comp. Stren.	−	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	1	−	−	−	−	−	1	1	1	1	1	−	−	−	−	−	−	−	−	−	−	6	0.133
Cost	−	−	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	0	−	−	−	−	0	−	−	−	−	0	0	1	1	−	−	−	−	−	−	2	0.044
Weldability	−	−	−	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	0	−	−	−	−	0	−	−	−	1	−	−	−	0	1	1	−	−	−	3	0.067
Corr. Resistance	−	−	−	−	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	0	−	−	−	−	0	−	−	−	1	−	−	1	−	−	1	1	−	4	0.089
Appearance	−	−	−	−	−	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	0	−	−	−	−	0	−	−	−	0	−	−	0	−	0	−	0	0	0
Availability	−	−	−	−	−	−	−	−	0	−	−	−	−	−	−	−	0	−	−	−	−	−	−	0	−	−	−	−	−	0	−	−	−	−	0	−	−	−	0	−	−	0	−	0	1	1	0.022
Total Positive Decisions																																														45	1

Report Page 86 PDF Page 106 / 151

Table 7. 5: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	AISI 316 Stainless Steel		AISI 347 Annealed Stainless Steel		1045 Carbon Steel
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Elastic Modulus	0.2	94.15	18.83	97.56	19.51	100	20
Shear Modulus	0.178	96.25	17.14	97.5	17.37	100	17.8
Mass Density	0.156	100	15.6	100	15.6	98.13	15.3
Coefficient of Thermal Expansion	0.111	73.13	8.12	75	8.33	100	11.1
Compressive Strength	0.133	98.61	13.12	100	13.3	17.99	2.39
Cost	0.044	30	1.32	25	1.1	100	4.4
Weldability	0.067	5	0.335	4	0.268	3	0.201
Corrosion Resistance	0.089	5	0.445	5	0.445	2	0.178
Appearance	0	5	0	5	0	2	0
Availability	0.022	5	0.11	4	0.088	5	0.11
Performance Index ($\gamma = \sum \alpha\beta$)		75.02		76.011		71.479

Result Material Performance Index is largest (76.011) for AISI 347 Annealed Stainless Steel. So, we should select AISI 347 Annealed Stainless Steel for roller shaft.

Report Page 87 PDF Page 107 / 151

7.5.2Material Selection for frame and base

Table 7. 6: Material Properties Comparison for frame and base

Property	Aluminum Alloy (6061)	Stainless Steel (AISI 304)	High-Density Polyethylene (HDPE)	Mild Steel
Density (kg/m³)	2700	8000	950	7850
Tensile Strength (MPa)	290	520	26	370
Elastic Modulus (GPa)	69	193	0.8	210

Table 7. 7: Likert Scale for Non-Numeric Properties

Property	Aluminum Alloy (6061)	Stainless Steel (AISI 304)	High-Density Polyethylene (HDPE)	Mild Steel
Cost	3	1	5	5
Appearance	4	5	3	2

Explanation of Likert Ratings:

Appearance:

5: Bright, polished
4: Smooth, metallic, matte or polished
3: Opaque, smooth, matte
2: Dull gray, can be painted or coated

Cost:

5: Low (Most affordable)
3: Moderate
1: High (Most expensive)

Report Page 88 PDF Page 108 / 151

Table 7. 8: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Density (kg/m³)	0	0	1	1	−	−	−	−	−	−	2	0.2
Tensile Strength (MPa)	1	−	−	−	1	0	1	−	−	−	3	0.3
Elastic Modulus (GPa)	−	1	−	−	0	−	−	1	0	−	2	0.2
Cost	−	−	0	−	−	1	−	0	−	1	2	0.2
Appearance	−	−	−	0	−	−	0	−	1	0	1	0.1
Total Positive Decisions											10	1

Report Page 89 PDF Page 109 / 151

Table 7. 9: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Aluminum Alloy (6061)		Stainless Steel (AISI 304)		HDPE		Mild Steel
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Density	0.2	35.19	7.04	11.88	2.38	100	20	12.1	2.42
Tensile Strength	0.3	55.77	16.73	100	30	5	1.5	71.15	21.35
Elastic Modulus	0.2	32.86	6.57	91.9	18.38	0.38	0.08	100	20
Cost	0.2	33.33	6.67	100	20	20	4	20	4
Appearance	0.1	4	0.4	5	0.5	3	0.3	2	0.2
Performance Index ($\gamma = \sum \alpha\beta$)		37.41		71.26		25.88		47.97

Result Material Performance Index is greatest for Stainless Steel (AISI 304) (71.26). So, we should select Stainless Steel (AISI 304) for base and frame.

Report Page 90 PDF Page 110 / 151

7.5.3Material Selection for lower sole cleaner brush fiber

Table 7. 10: List of material properties selected for lower sole cleaner brush fiber

Property	Nylon 6	Polypropylene	Polyester (PET)
Abrasion Resistance	5	3	4
Flexibility	4	5	3
Water Resistance	5	5	4
Durability	5	3	3
Cost (BDT per kg)	250	150	200

Table 7. 11: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Abrasion Resistance	1	1	1	1	−	−	−	−	−	−	4	0.4
Flexibility	0	−	−	−	0	1	1	−	−	−	2	0.2
Water Resistance	−	0	−	−	1	−	−	1	1	−	3	0.3
Durability	−	−	0	−	−	0	−	0	−	1	1	0.1
Cost	−	−	−	0	−	−	0	−	0	0	0	0
Total Positive Decisions											10	1

Table 7. 12: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Nylon 6		Polypropylene (β)		Polyester (PET)
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Abrasion Resistance	0.4	100	40	60	24	80	32
Flexibility	0.2	80	16	100	20	60	12
Water Resistance	0.3	100	30	100	30	80	24
Durability	0.1	100	10	60	6	60	6
Cost	0	60	0	100	0	75	0
Performance Index ($\gamma = \sum \alpha\beta$)		96		80		74

Report Page 91 PDF Page 111 / 151

Result Material Performance Index is largest for Nylon 6 (96). So, we should select Nylon 6 for lower sole cleaner brush fiber. Moreover, its durability and abrasive resistance features have made it optimized for this project.

At the first stage of our designing process, we had selected the most suitable materials under consideration based on different criteria of components. After extensive numerical analysis, we selected certain materials from different alternatives for different parts by analyzing in the digital logic method and performance index. As we have selected our desired materials, now we can move to the process and manufacturing selection section.

Report Page 92 PDF Page 112 / 151

7.6Quantitative Analysis of Manufacturing Processes

7.6.1Manufacturing processes for manufacturing AISI 347 Annealed Stainless Steel for roller shaft

Table 7. 13: List of properties for comparing manufacturing process for AISI 347 Annealed Stainless Steel used in roller shaft.

Criteria	Turning on Lathe Machine	Extrusion	CNC Machining
Dimensional Accuracy	4	2	5
Surface Finish	4	3	5
Metallurgical Properties	5	4	5
Cost Efficiency	3	5	2
Machining Time	4	5	3
Process Complexity	3	2	4

Table 7. 14: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{6(6-1)}{2} = 15$															Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	Positive Decisions	Relative Emphasis ($\alpha$)
Dimensional Accuracy	1	1	1	1	1	−	−	−	−	−	−	−	−	−	−	5	0.333
Surface Finish	0	−	−	−	−	1	1	1	1	−	−	−	−	−	−	4	0.267
Metallurgical Properties	−	0	−	−	−	0	−	−	−	1	1	1	−	−	−	3	0.200
Cost Efficiency	−	−	0	−	−	−	0	−	−	0	−	−	1	1	−	2	0.133
Machining Time	−	−	−	0	−	−	−	0	−	−	0	−	0	−	1	1	0.067
Process Complexity	−	−	−	−	0	−	−	−	0	−	−	0	−	0	0	0	0.000
Total Positive Decisions																15	1.000

Report Page 93 PDF Page 113 / 151

Table 7. 15: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Turning on Lathe Machine		Extrusion		CNC Machining
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Dimension al Accuracy	0.333	80	26.64	40	13.32	100	33.3
Surface Finish	0.267	80	21.36	60	16.02	100	26.7
Metallurgic al Properties	0.2	100	20	80	16	100	20
Cost Efficiency	0.133	60	7.98	100	13.3	40	5.32
Machining Time	0.067	80	5.36	100	6.7	60	4.02
Process Complexit y	0	75	0	50	0	100	0
Performance Index ($\gamma = \sum \alpha\beta$)		81.34		65.34		89.34

Result The performance index is highest for the CNC machining process of AISI 347 Annealed Stainless Steel used in roller shaft. But as it might be less costly, the strong opponent is Turning on Lathe Machine. If budget doesn't match, we might opt for lathe machine.

Report Page 94 PDF Page 114 / 151

7.6.2Manufacturing process for Stainless Steel (AISI 304) for base and frame

Table 7. 16: List of properties for Stainless Steel (AISI 304) used in base and frame of the structure.

Criteria	Laser Cutting	Welding and Assembly	Sheet Metal Forming
Dimensional Accuracy	5	4	3
Surface Finish	4	3	3
Structural Strength	3	5	4
Cost Efficiency	3	4	5
Machining Time	4	3	4
Process Complexity	3	2	4

Table 7. 17: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{6(6-1)}{2} = 15$															Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	Positive Decisions	Relative Emphasis ($\alpha$)
Dimensional Accuracy	1	0	1	1	1	−	−	−	−	−	−	−	−	−	−	4	0.267
Surface Finish	0	−	−	−	−	0	1	1	1	−	−	−	−	−	−	3	0.200
Structural Strength	−	1	−	−	−	1	−	−	−	1	1	1	−	−	−	5	0.333
Cost Efficiency	−	−	0	−	−	−	0	−	−	0	−	−	1	1	−	2	0.133
Machining Time	−	−	−	0	−	−	−	0	−	−	0	−	0	−	1	1	0.067
Process Complexity	−	−	−	−	0	−	−	−	0	−	−	0	−	0	0	0	0.000
Total Positive Decisions																15	1

Report Page 95 PDF Page 115 / 151

Table 7. 18: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Laser Cutting		Welding and Assembly		Sheet Metal Forming
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Dimensional Accuracy	0.267	100	26.7	80	21.36	60	16.02
Surface Finish	0.2	100	20	75	15	75	15
Structural Strength	0.333	60	19.98	100	33.3	80	26.64
Cost Efficiency	0.133	60	7.98	80	10.64	100	13.3
Machining Time	0.067	100	6.7	75	5.03	100	6.7
Process Complexity	0	75	0	50	0	100	0
Performance Index ($\gamma = \sum \alpha\beta$)		81.36		85.33		77.66

Result Analyzing critical criteria like dimensional accuracy, surface finish, structural strength, cost, time, and complexity; welding and assembly scores maximum. So, welding and assembly should be performed for AISI 304 stainless steel used in base and frame.

Report Page 96 PDF Page 116 / 151

7.6.3Manufacturing process for Nylon 6 lower sole cleaner brush fiber

For Nylon 6 brush fibers, we'll consider the following manufacturing processes:

•Injection Molding
•Extrusion
•Monofilament Drawing

Table 7. 19: List of properties for comparing manufacturing process for Nylon 6 lower sole cleaner brush fiber

Criteria	Injection Molding	Extrusion	Monofilament Drawing
Abrasion Resistance	4	5	4
Flexibility	3	4	5
Durability	4	4	5
Cost Efficiency	3	4	3
Ease of Manufacturing	4	5	3

Table 7. 20: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Abrasion Resistance	1	1	1	1	−	−	−	−	−	−	4	0.4
Flexibility	0	−	−	−	1	1	1	−	−	−	3	0.3
Durability	−	0	−	−	0	−	−	1	1	−	2	0.2
Cost Efficiency	−	−	0	−	−	0	−	0	−	1	1	0.1
Ease of Manufacturing	−	−	−	0	−	−	0	−	0	0	0	0
Total Positive Decisions											10	1

Report Page 97 PDF Page 117 / 151

Table 7. 21: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Injection Molding		Extrusion		Monofilament Drawing
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Abrasion Resistance	0.4	80	32	100	40	80	32
Flexibility	0.3	60	18	80	24	100	30
Durability	0.2	80	16	80	16	100	20
Cost Efficiency	0.1	75	7.5	100	10	75	7.5
Ease of Manufac.	0	80	0	100	0	60	0
Performance Index ($\gamma = \sum \alpha\beta$)		73.5		90		89.5

Result The weighted average for Extrusion (90) is maximum in terms of some important criteria. So, brush fiber made from Nylon 6 will be manufactured in the extrusion process.

Report Page 98 PDF Page 118 / 151

7.7Joining Process

Fabrication or joining processes are part and parcel in manufacturing where two or more solid elements are joined temporarily or permanently to form a single component. Initially engineering joining methods can be broadly classified into two main groups:

•Permanent: Welding, brazing, soldering.
•Non-permanent (Temporary): Adhesive bonding, crimping, shrink fitting, bolting or screwing (mechanical joining), clamping, fasteners like clutch, nut-bolt, nail hook, etc.

7.7.1Permanent Joining Process for semi-automated shoe cleaner

Table 7. 22: List of properties for permanent joining process of machine parts

Criteria	TIG Welding	MIG Welding	Spot Welding	Arc Welding
Strength of Joint	5	4	3	4
Precision	5	4	2	3
Durability	5	4	3	4
Cost Efficiency	2	4	5	4
Ease of Operation	3	5	5	3

Table 7. 23: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Strength of Joint	1	1	1	1	−	−	−	−	−	−	4	0.4
Precision	0	−	−	−	1	1	1	−	−	−	3	0.3
Durability	−	0	−	−	0	−	−	1	1	−	2	0.2
Cost Efficiency	−	−	0	−	−	0	−	0	−	1	1	0.1
Ease of Operation	−	−	−	0	−	−	0	−	0	0	0	0
Total Positive Decisions											10	1

Report Page 99 PDF Page 119 / 151

Table 7. 24: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	TIG Welding		MIG Welding		Spot Welding		Arc Welding
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Strength of Joint	0.4	100	40	80	32	60	24	80	32
Precision	0.3	100	30	80	24	40	12	60	18
Durability	0.2	100	20	80	16	60	12	80	16
Cost Efficiency	0.1	40	4	80	8	100	10	80	8
Ease of Operation	0	60	0	100	0	100	0	60	0
Performance Index ($\gamma = \sum \alpha\beta$)		94		80		58		74

Result Using selected criteria, TIG Welding outperforms over other permanent joining processes. But additionally, we might use other joining processes while designing practically based on availability and cost cutting.

Report Page 100 PDF Page 120 / 151

7.7.2Temporary Joining Process for semi-automated shoe cleaner

Table 7. 25: List of properties for temporary joining process of machine parts

Criteria	Bolts and Nuts	Threaded Inserts	Clamping	Snap Fit
Ease of Assembly/Disassembly	4	3	5	5
Holding Strength	5	4	3	3
Cost Efficiency	4	3	5	4
Durability of Joint	5	4	3	3
Vibration Resistance	4	4	2	3

Table 7. 26: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Ease of Assembly/Disassembly	1	1	1	1	−	−	−	−	−	−	4	0.4
Holding Strength	0	−	−	−	1	1	1	−	−	−	3	0.3
Cost Efficiency	−	0	−	−	0	−	−	1	1	−	2	0.2
Durability of Joint	−	−	0	−	−	0	−	0	−	1	1	0.1
Vibration Resistance	−	−	−	0	−	−	0	−	0	0	0	0
Total Positive Decisions											10	1

Report Page 101 PDF Page 121 / 151

Table 7. 27: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Bolts and Nuts		Threaded Inserts		Clamping		Snap Fit
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Ease of Assembly/Disassembly	0.4	80	32	60	24	100	40	100	40
Holding Strength	0.3	100	30	80	24	60	18	60	18
Cost Efficiency	0.2	80	16	60	12	100	20	80	16
Durability of Joint	0.1	100	10	80	8	60	6	60	6
Vibration Resistance	0	80	0	80	0	40	0	60	0
Performance Index ($\gamma = \sum \alpha\beta$)		88		68		84		80

Result After the analysis, we conclude that bolts and nuts scored much higher in the weighted average method. But some other methods will be used while making the products.

Report Page 102 PDF Page 122 / 151

7.8Finishing Operations of Parts

Table 7. 28: List of properties for Finishing operation of the parts

Criteria	Polishing	Electroplating	Powder Coating
Surface Smoothness	5	4	3
Corrosion Resistance	2	5	4
Aesthetic Appeal	4	4	5
Cost Efficiency	3	3	4
Durability of Finish	2	4	5

Table 7. 29: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Surface Smoothness	1	1	1	1	−	−	−	−	−	−	4	0.4
Corrosion Resistance	0	−	−	−	1	1	1	−	−	−	3	0.3
Aesthetic Appeal	−	0	−	−	0	−	−	1	1	−	2	0.2
Cost Efficiency	−	−	0	−	−	0	−	0	−	1	1	0.1
Durability of Finish	−	−	−	0	−	−	0	−	0	0	0	0
Total Positive Decisions											10	1

Report Page 103 PDF Page 123 / 151

Table 7. 30: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Polishing		Electroplating		Powder Coating
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Surface Smoothness	0.4	100	40	80	32	60	24
Corrosion Resistance	0.3	40	12	100	30	80	24
Aesthetic Appeal	0.2	80	16	80	16	100	20
Cost Efficiency	0.1	75	7.5	75	7.5	100	10
Durability of Finish	0	40	0	80	0	100	0
Performance Index ($\gamma = \sum \alpha\beta$)		75.5		85.5		78

Result Electroplating has the highest PI; meaning it should be used. Another strong alternative is powder coating.

7.9Criteria for Coloring and Aesthetic Finish

Table 7. 31: List of properties for coloring and aesthetic finish

Criteria	Powder Coating	Anodizing	Spray Painting
Aesthetic Appeal	4	4	5
Durability of Finish	5	4	3
Cost Efficiency	4	3	5
Corrosion Resistance	5	4	3
Ease of Application	4	3	5

Report Page 104 PDF Page 124 / 151

Table 7. 32: Determination of Relative Importance of Goals Using Digital Logic Method

Selection Criteria	Number of Positive Decisions, $N = \frac{n(n-1)}{2} = \frac{5(5-1)}{2} = 10$										Positive Decisions	Relative Emphasis ($\alpha$)
Selection Criteria	1	2	3	4	5	6	7	8	9	10	Positive Decisions	Relative Emphasis ($\alpha$)
Aesthetic Appeal	1	1	1	1	−	−	−	−	−	−	4	0.4
Durability of Finish	0	−	−	−	1	1	1	−	−	−	3	0.3
Cost Efficiency	−	0	−	−	0	−	−	1	1	−	2	0.2
Corrosion Resistance	−	−	0	−	−	0	−	0	−	1	1	0.1
Ease of Application	−	−	−	0	−	−	0	−	0	0	0	0
Total Positive Decisions											10	1

Table 7. 33: Calculation of the Performance Index

Selection Criteria	Weighting Factor ($\alpha$)	Powder Coating		Anodizing		Spray Painting
Selection Criteria	Weighting Factor ($\alpha$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)	Scaled ($\beta$)	Score ($\alpha\beta$)
Aesthetic Appeal	0.4	80	32	80	32	100	40
Durability of Finish	0.3	100	30	80	24	60	18
Cost Efficiency	0.2	80	16	60	12	100	20
Corrosion Resistance	0.1	100	10	80	8	60	6
Ease of Application	0	80	0	60	0	100	0
Performance Index ($\gamma = \sum \alpha\beta$)		88		76		84

Result The Performance Index for Powder coating is the largest, while we can consider spray painting another close alternative.

Report Page 105 PDF Page 125 / 151

7.10Conclusion

Based on the above numerical analysis, we conclude that different processes have distinctive advantages and disadvantages. The same manufacturing process is not applicable to all types of parts or materials.

In this chapter, we have determined the optimized processes for manufacturing, joining, finishing, and coloring operations.

Report Page 106 PDF Page 126 / 151

Chapter 08

Cost & Sensitivity Analysis

8.1Introduction

Cost is deeply intertwined with product design, as design decisions significantly impact overall expenses. The primary factors shaping a product's economic viability are cost and revenue, with the aim of minimizing costs while maximizing profits. Conducting a cost analysis highlights a product's capacity to generate the desired output while remaining profitable. It also helps evaluate whether the product can reach its break-even point effectively.

8.2Forecasting Demand

Methodology: Proportional Scaling Approach. We utilized the Proportional Scaling Approach to forecast the one-year demand for the proposed product. This method is based on survey results and assumes that the sample accurately represents the target population. The steps of the methodology are outlined below:

8.2.1Target Population Identification

The total number of potential adopters for the product was identified as 2,941 institutions in the target urban zone, comprising 245 Hotels, 324 Schools and Colleges, 136 Hospitals, 115 Private Universities, 1,200 Private Bank Branches, and 921 Corporate Commercial Offices.

8.2.2Survey Implementation

A survey was conducted among 35 individuals from corresponding institutions, which served as a representative sample of the target population. The survey revealed that 80% of the respondents (28 out of 35) expressed definitive interest in adopting the product.

8.2.3Adoption Rate Calculation

The adoption rate was calculated using the following formulation:

\text{Adoption Rate} = \frac{\text{Number of Positive Responses}}{\text{Total Number of Surveyed Institutions}} = \frac{28}{35} = 0.80 \text{ (80\%)}

Report Page 107 PDF Page 127 / 151

8.2.4Demand Forecasting

The adoption rate was scaled up to the entire target population to estimate the total demand. The formula used was:

\text{Forecasted Demand} = \text{Total Population} \times \text{Adoption Rate} = 2941 \times 0.80 = 2353 \text{ units}

Hence, the estimated one-year gross demand for the product is 2,353 units.

8.2.5Scenario Analysis

To address potential variations in market conditions, sensitivity analysis was performed using different adoption scenarios:

Optimistic (90%)

2,118 units

2353 × 0.90

Realistic (80%)

1,882 units

2353 × 0.80

Pessimistic (70%)

1,647 units

2353 × 0.70

In conclusion, the Proportional Scaling Approach offers a straightforward and effective means of forecasting demand using survey data. The projected realistic demand for the product in its first year is 1,882 units.

8.3Manufacturing Cost

Manufacturing cost is the cost of production directly incurred during the manufacturing process. It comprises direct labor, direct material, and manufacturing overhead costs. With a projected realistic annual demand of 1,882 units, our production strategy targets capturing approximately 30% market share during Year 1, establishing an annual planned sales and production volume of 565 units.

Report Page 108 PDF Page 128 / 151

8.3.1Cost of Machinery

To manufacture the structural and mechanical elements of the machine, specific workshop equipment must be acquired:

Equipment / Machine	Specification	Lifespan	Qty	Unit Cost (Tk.)	Total Cost (Tk.)
Lathe Machine	CQ6230A Single Phase Conventional Manual Lathe (4.5 feet)	20 years	2	1,70,000/-	3,40,000/-
Drill Machine	BOKY Bench/Pillar Drill (13mm chuck capacity)	10 years	1	9,000/-	9,000/-
Arc Welding Machine	ARC300 IGBT Inverter Arc Welder	10 years	2	15,820/-	31,640/-
Total Capital Machinery Cost					3,80,640/-

Financing Terms: Machinery purchased on credit at a 12% annual interest rate with a 2% risk factor over a 20-year payback period.

8.3.2Cost of Raw Material (per unit of product)

Direct raw material consumption per single unit of the semi-automated shoe cleaning machine:

Raw Material Item	Required Qty / Unit	Unit Rate (Tk.)	Cost / Product (Tk.)
Mild Steel Sheet	3 kg	130/- per kg	390/-
Stainless Steel Sheet (4ft × 8ft × 1mm)	1 sheet	5,800/- per sheet	5,800/-
Nylon Brush Fiber (0.2 Nylon)	6 units	130/- per unit	780/-
Total Raw Material Cost per Product			6,970/-

Total Annual Raw Material Cost (for 565 units planned output): 39,38,050/- Tk.

Report Page 109 PDF Page 129 / 151

8.3.3Cost of Labor

Monthly and annual compensation for dedicated workshop operators and assembly technicians:

Worker Role / Designation	Headcount	Monthly Wage / Person	Total Monthly Cost
Lathe Operator	2	22,500/-	45,000/-
Drilling & Cutting Operator	2	10,000/-	20,000/-
Welding Operator	2	11,000/-	22,000/-
Assembly Staff	4	9,000/-	36,000/-
Floor & Facility Cleaning Staff	2	7,000/-	14,000/-
Miscellaneous (15% Festival Bonus + 6% Performance Incentive)	—	Pooled (approx.)	40,000/-
Total Cost of Labor per Month			1,77,000/- Tk.
Total Annual Labor Cost (12 Months)			21,24,000/- Tk.

8.3.4Purchasing Cost per Unit of Product (External Parts)

Off-the-shelf and outsourced electromechanical parts required per machine unit:

Table 8. 1: Purchasing Cost per Unit (External Parts)

Purchased Part	Price per Unit (Tk.)	Quantity	Total Cost (Tk.)
Spur Gear	250/-	10	2,500/-
Worm Gear	1,270/-	4	5,080/-
AC to DC Converter	645/-	1	645/-
Nut & Bolt Set	25/-	20	500/-
Ball Bearing	99/-	20	1,980/-
DC Motor (1 HP)	4,829/-	2	9,658/-
Solid Shoe Shiner	3,000/-	1	3,000/-
Total Purchasing Cost per Unit Product			23,363/- Tk.

Total Annual External Purchasing Cost (for 565 units planned output): 1,32,00,095/- Tk.

Report Page 110 PDF Page 130 / 151

↳ Table 8.1: External Purchasing Cost (unified on Report Page 109 above) ↑ View Table 8.1

8.3.5Manufacturing Overhead Cost

Indirect production expenses including technical supervisory personnel, utility consumption, and facility rental:

Table 8. 2: Manufacturing Overhead Cost

Cost Item	No. of Posts	Monthly Salary / Rate	Monthly Cost (Tk.)
Production Manager	1	30,000/-	30,000/-
Manufacturing Engineer	1	25,000/-	25,000/-
Quality Control Manager	1	20,000/-	20,000/-
Power & Industrial Electricity Consumption	—	Variable utility	15,000/-
Factory Facility Rent	—	Fixed lease	25,000/-
Total Overhead per Month			1,15,000/- Tk.
Total Annual Manufacturing Overhead (12 Months)			13,80,000/- Tk.

Report Page 111 PDF Page 131 / 151

8.3.6Total Manufacturing Cost

Aggregated direct and indirect manufacturing expenditures for the annual planned volume (565 units):

Table 8. 3: Total Manufacturing Cost

Cost Component	Annual Amount (Tk.)
Cost of Raw Material	39,38,050/-
Cost of Purchasing (External Parts)	1,32,00,095/-
Cost of Direct Labor	21,24,000/-
Manufacturing Overhead	13,80,000/-
Total Manufacturing Cost (TVC)	2,06,42,145/- Tk.

8.4Non-Manufacturing Cost

Non-manufacturing costs encompass expenses not directly tied to shop-floor fabrication but indispensable for administrative governance, sales channels, logistics, and executive operations across the product lifecycle.

8.4.1Administrative Cost

Monthly compensation and headcount for executive leadership and office personnel:

Table 8. 4: Administrative Cost of Personnel (per Month)

Administrative Role	No. of Posts	Monthly Salary / Person	Monthly Cost (Tk.)
Chief Executive Officer (CEO)	1	60,000/-	60,000/-
Chief Financial Officer (CFO)	1	50,000/-	50,000/-
Chief Marketing Officer (CMO)	1	40,000/-	40,000/-
Product Development Officer	1	25,000/-	25,000/-
Administrative Clerk	1	10,000/-	10,000/-
Total Administrative Salary per Month			1,85,000/- Tk.
Total Annual Administrative Cost (12 Months)			22,20,000/- Tk.

Report Page 112 PDF Page 132 / 151

8.4.2Sales & Marketing Expense

Commercialization and outreach budget for enterprise market penetration:

1. Marketing Manager Headcount: 1 Employee
Monthly Salary: 20,000/- Tk.
Annual Salary: 2,40,000/- Tk.

2. Advertising & Campaigns Promotional materials, demonstrations & outreach
Annual Budget: 60,000/- Tk.

Total Annual Sales & Marketing Cost: 3,00,000/- Tk.

8.4.3Bank Loan & Interest

Debt financing structure for startup capital expenditure:

Total Loan20,00,000/-

Interest Rate (i)14%

Period (n)20 Years

Annual Annuity (A)3,01,972/-

Table 8. 5: Total Non-Manufacturing Cost (per Year)

Expense Category	Annual Cost (Tk.)
Administration	22,20,000/-
Office Rent	2,00,000/-
Sales & Marketing	3,00,000/-
Bank Loan (Annuity Repayment)	3,01,972/-
Advancement for Factory Space	2,00,000/-
Municipal Taxes	60,000/-
Insurances	80,000/-
Commercial Utilities	77,551/-
Total Non-Manufacturing Cost (TFC)	34,39,523/- Tk.

Report Page 113 PDF Page 133 / 151

8.5Total Cost

Comprehensive annual operational and production budget summary:

Table 8. 6: Total Yearly Cost

Cost Classification	Total Amount (Tk.)
Manufacturing Cost (Variable Cost, TVC)	2,06,42,145/-
Non-Manufacturing Cost (Fixed Cost, TFC)	34,39,523/-
Total Comprehensive Annual Cost	2,40,81,668/- Tk.

8.6Break-Even Analysis

The break-even point establishes the volume of production at which total revenues precisely match total fixed and variable costs.

Fixed Cost (TFC)34,39,523/-6,087.65/- / unit

Variable Cost (TVC)2,06,42,145/-36,534.77/- / unit

Target Margin (25%)9,133.69/-profit / unit

Selling Price (P)51,756/-per unit

Equilibrium Formulation at Break-Even Point $$\text{Selling Price} \times Q_{BEP} = \text{Total Fixed Cost} + (\text{Variable Cost per unit} \times Q_{BEP})$$ $$51,756 \times Q_{BEP} = 3,439,523 + (36,534.77 \times Q_{BEP})$$ $$15,221.23 \times Q_{BEP} = 3,439,523 \implies Q_{BEP} = 226 \text{ units}$$

Break-Even Payback Period $$\text{Break-Even Period} = \frac{226}{565} \times 1 \text{ year} = 0.40 \text{ years} \approx 4.8 \text{ months}$$

Report Page 114 PDF Page 134 / 151

8.7Sensitivity Analysis

Sensitivity analysis provides insight into how sensitive the break-even threshold ($Q_{BEP}$) is to individual variations in cost, revenue, and demand parameters. In this analysis, a separate 10% adverse parameter shock is evaluated across each cost and operational driver to determine parameter vulnerability.

8.7.1Sensitivity of Demand

Baseline planned production is 565 units per year. Under a 10% increase in market demand ($622$ units):

\text{New Demand} = 565 \times 1.10 = 622 \text{ units}$$ $$51,756 \times Q_{BEP} = 3,439,523 + (36,534.77 \times Q_{BEP}) \implies Q_{BEP} = 226 \text{ units (No change)}$$ $$\Delta Q_{BEP} = 0.00\%

Report Page 115 PDF Page 135 / 151

Thus, sales demand volume does not alter the break-even quantity threshold itself; the break-even point is completely insensitive to demand changes.

8.7.2Sensitivity of Direct Material Cost

Table 8. 7: Direct Material Cost

Material Cost Component	Annual Amount (Tk.)
Cost of Raw Material	39,38,050/-
Cost of Purchasing (External Parts)	1,32,00,095/-
Total Direct Material Cost	1,71,38,145/- Tk.

Evaluating an adverse 10% surge in raw materials and purchased component costs:

\text{New Direct Material Cost} = 17,138,145 \times 1.10 = 18,851,959.50 \text{ Tk.}$$ $$\text{New Variable Cost per unit} = 36,534.77 - \frac{17,138,145}{565} + \frac{18,851,959.50}{565} = 39,568.10 \text{ Tk.}$$ $$51,756 \times Q_{BEP} = 3,439,523 + (39,568.10 \times Q_{BEP}) \implies Q_{BEP} = 283 \text{ units}$$ $$\Delta Q_{BEP} = \frac{283 - 226}{226} \times 100\% = 25.22\%

Outcome: The break-even threshold is critically sensitive to direct material prices, requiring 57 additional units (+25.22%) to break even.

8.7.3Sensitivity of Direct Labor Cost

Baseline annual labor expenditure is 21,24,000/- Tk. Subject to a 10% wage and bonus escalation:

\text{New Labor Cost} = 2,124,000 \times 1.10 = 2,336,400 \text{ Tk.}$$ $$\text{New Variable Cost per unit} = \frac{20,642,145 + (2,336,400 - 2,124,000)}{565} = 36,910.70 \text{ Tk.}

Report Page 116 PDF Page 136 / 151

51,756 \times Q_{BEP} = 3,439,523 + (36,910.70 \times Q_{BEP}) \implies Q_{BEP} = 232 \text{ units}$$ $$\Delta Q_{BEP} = \frac{232 - 226}{226} \times 100\% = 2.65\%

Outcome: Break-even is moderately resilient to direct labor wage increases, causing only a 6-unit increase (+2.65%).

8.7.4Sensitivity of Administrative Fixed Cost

Baseline annual administrative cost is 22,20,000/- Tk. Subject to a 10% administrative inflation shock:

\text{New Administrative Cost} = 2,220,000 \times 1.10 = 2,442,000 \text{ Tk.}$$ $$\text{New Fixed Cost (TFC)} = 3,439,523 + (2,442,000 - 2,220,000) = 3,661,523 \text{ Tk.}$$ $$51,756 \times Q_{BEP} = 3,661,523 + (36,534.77 \times Q_{BEP}) \implies Q_{BEP} = 241 \text{ units}$$ $$\Delta Q_{BEP} = \frac{241 - 226}{226} \times 100\% = 6.64\%

Outcome: Administrative overhead exhibits a noticeable 15-unit (+6.64%) effect on break-even feasibility.

8.7.5Sensitivity of Selling & Marketing Expenses

Baseline sales and promotion expense is 3,00,000/- Tk. With a 10% budget expansion:

\text{New Selling Expense} = 300,000 \times 1.10 = 330,000 \text{ Tk.}$$ $$\text{New Fixed Cost (TFC)} = 3,439,523 + (330,000 - 300,000) = 3,469,523 \text{ Tk.}$$ $$51,756 \times Q_{BEP} = 3,469,523 + (36,534.77 \times Q_{BEP}) \implies Q_{BEP} = 228 \text{ units}

Report Page 117 PDF Page 137 / 151

\Delta Q_{BEP} = \frac{228 - 226}{226} \times 100\% = 0.88\%

Outcome: Commercial marketing expenses have an extremely minimal effect (+0.88%) on the break-even threshold.

Summary Matrix

Sensitivity Ranking Across All Cost Drivers

Parameter Evaluated	Parameter Shift	New $Q_{BEP}$	Sensitivity ($\Delta Q_{BEP}$)	Impact Classification
Direct Material Cost	+10%	283 units	25.22%	Critical (Highest Impact)
Administrative Fixed Cost	+10%	241 units	6.64%	Moderate Sensitivity
Direct Labor Cost	+10%	232 units	2.65%	Low Sensitivity
Selling / Marketing Expenses	+10%	228 units	0.88%	Minimal Sensitivity
Market Demand Volume	+10%	226 units	0.00%	No Impact on $Q_{BEP}$

It can be clearly observed that direct material costs exert the dominant influence on the break-even point ($+25.22\%$). The cost analysis is concerned with determining the monetary value of inputs (raw materials and purchased mechanical assemblies), called the overall cost of production, which dictates the optimum level of batch production. The comprehensive financial modeling confirms that the semi-automated shoe cleaning machine achieves financial break-even within 4.8 months (226 units), establishing robust commercial and operational feasibility.

Report Page 118 PDF Page 138 / 151

↳ Chapter 08: Cost & Sensitivity Analysis completed. Proceeding to Future Scope & Limitations. Next: Chapter 09 →

Report Page 119 PDF Page 139 / 151

Chapter 09

Future Scope & Limitations

9.1Introduction

This chapter examines the future scope and limitations of the Semi-Automated Shoe Cleaning Machine, a device designed to simplify and improve the process of cleaning footwear in residential and commercial settings. With a focus on semi-automation, ease of use, and affordability, the product aims to address the challenges of maintaining shoe hygiene in busy urban and rural households. This section explores how the design could evolve to include advanced features such as full automation, enhanced cleaning efficiency, and smart monitoring systems to meet growing consumer demands. Furthermore, the chapter identifies and evaluates key limitations, such as reliance on external power sources, limited cleaning versatility, and maintenance concerns. By outlining potential improvements and acknowledging existing constraints, this chapter provides a strategic roadmap for the product's continued development and market relevance.

9.2Future Scope

The Semi-Automated Shoe Cleaning Machine has significant potential for future enhancements to increase its utility and customer appeal. Some key areas for engineering and functional development include:

01 Automation

Fully Automated Cleaning Cycle

Complete elimination of manual intervention by integrating programmable microcontrollers and motorized shoe positioning mechanisms for a touchless cleaning experience.

02 Intelligence

IoT & Smart Sensor Integration

Embedded optical and current sensors to monitor cycle duration, water consumption, detergent dosage, and real-time brush wear diagnostics via mobile telemetry.

03 Versatility

Interchangeable Cleaning Heads

Modular quick-release brush assemblies designed for diverse footwear materials, including soft horsehair for suede, synthetic bristles for leather, and stiff nylon for athletic footwear.

04 Performance

Heated Air Rapid Drying System

Incorporation of a low-power PTC ceramic heating element and tangential blower fan to expedite shoe drying immediately following the wet washing cycle.

05 Capacity

Expanded Detergent Reservoir

High-capacity fluid storage compartments with level sensors engineered for uninterrupted, continuous operation in commercial hubs, retail outlets, and hotels.

06 Materials

Lightweight Structural Composites

Strategic replacement of select mild steel components with reinforced carbon fiber or high-impact polymers to enhance product portability without sacrificing rigidity.

Report Page 120 PDF Page 140 / 151

9.2 Future Scope (Continued Innovations)

07 Ergonomics

Multi-Pair & Extended Sizing

Dimensional and mechanical adaptation of the chassis to accommodate oversized work boots, children's shoes, and dual-slot fixtures for concurrent multi-shoe servicing.

08 Engineering

Industrial Aesthetics & Mechanism Optimization

Collaborative industrial styling with external engineering design firms to refine exterior contours, reduce mechanical drag, and enclose gear trains for whisper-quiet operation.

09 Sustainability

Solar & Renewable Energy Integration

Optional DC photovoltaic solar panel arrays with integrated lithium-ion battery backup systems for off-grid commercial deployment and heightened environmental sustainability.

9.3Limitations

While the Semi-Automated Shoe Cleaning Machine offers a practical solution to footwear maintenance, certain technical and operational limitations currently constrain its performance and commercial versatility. The identified operational constraints include:

L1 Power Supply

Grid Electricity Dependency

The machine currently relies strictly on 220V AC wall power, which restricts its operational flexibility in rural, mobile, or power-interrupted localities without auxiliary generation.

L2 Geometry

Tread Inaccessibility on Deep Grooves

Standard cylindrical and side brushes exhibit limited penetration when scrubbing complex, deeply lugged hiking boot soles or heavily textured upper embellishments.

L3 Chassis Size

Footwear Dimensional Constraints

The fixed-dimension washing bay cannot accommodate non-standard footwear sizes (e.g. extreme oversized work boots or very small infant shoes) without risk of poor brush contact.

L4 Fluid Volume

Limited Fluid Reservoir Capacity

The onboard water and liquid detergent tanks require frequent manual replenishment during peak high-volume operational cycles in commercial lobbies.

L5 Maintenance

Mechanical Wear on Brushes & Rollers

Continuous abrasive friction against diverse rubber soles precipitates periodic bristle bending and polymer degradation, dictating regular replacement intervals.

L6 Automation

User Intervention in Semi-Automation

The semi-automated architecture necessitates manual shoe insertion, orientation holding, and cycle triggering, falling short of a fully autonomous hands-off appliance.

L7 Acoustics

Acoustic Noise During Peak Operation

Mechanical gearing, spur gears, and motor rotation generate audible operating noise that may cause minor disruption in quiet office environments or executive boardrooms.

L8 Effluent Mgmt

Wastewater & Residue Filtration

The existing gravity-drain system lacks integrated centrifugal or multi-stage filtration to separate heavy mud cakes and particulate sludge from the effluent liquid.

9.4Conclusion

The Semi-Automated Shoe Cleaning Machine presents an innovative and accessible solution to maintaining shoe hygiene, particularly in environments where time and convenience are critical. By integrating semi-automation, compact design, and essential cleaning features, it successfully addresses key pain points for everyday users.

Report Page 121 PDF Page 141 / 151

However, this analysis underscores the need for ongoing improvement in areas such as automation, versatility, and sustainability to meet evolving market expectations. In summary, the Semi-Automated Shoe Cleaning Machine serves as a robust foundation for future advancements. By embracing innovative upgrades and addressing its current limitations, the product has the potential to emerge as a versatile and indispensable household and commercial cleaning solution.

Technical Synthesis

Roadmap for Commercial & Mechanical Maturation

Table 9. 1: Strategic Engineering Roadmap Matrix (Limitations vs. Future Enhancements)

Code	Current Limitation	Planned Technological Countermeasure	Development Phase	Feasibility
L1	Grid Power Dependency	Solar PV panel kit with 24V Li-ion battery backup bank	Phase 2 (Medium-term)	High (92%)
L2	Deep Tread Inaccessibility	Interchangeable high-density contoured brush heads	Phase 1 (Immediate)	Very High (98%)
L3	Chassis Dimensional Bounds	Adjustable-width guide rails and multi-shoe bay expander	Phase 2 (Medium-term)	High (88%)
L4	Fluid Reservoir Refills	Plumbed direct-inlet water connection with float valves	Phase 1 (Immediate)	Very High (95%)
L5	Bristle Mechanical Wear	Self-lubricating wear-resistant nylon 6/6 and quick-swaps	Phase 1 (Immediate)	High (90%)
L6	Semi-Automated User Effort	Optical proximity sensor cycle activation and motorized feed	Phase 3 (Long-term)	Moderate (78%)
L7	Operating Gear Noise	Helical composite gears and acoustic rubber dampening mounts	Phase 2 (Medium-term)	High (91%)
L8	Wastewater Sludge Buildup	Removable dual-stage sediment catch tray with drain trap	Phase 1 (Immediate)	Very High (96%)

↳ Chapter 09: Future Scope & Limitations completed. Proceeding to Project Overall Conclusion. Next: Overall Conclusion →

Report Page 122 PDF Page 142 / 151

Conclusion

Comprehensive Capstone Project Summary • BUET Dept. of Industrial & Production Engineering

Product design is a broad term that refers to the efficient generation and development of ideas into new goods through a process. It is therefore an essential component of the development of new products. Product design might be a straightforward solution to an issue that needs to be resolved or it can be an entirely original idea that has the potential to succeed.

Our “Semi-Automated Shoe Cleaning Machine” will successfully combine semi-automated technology with conventional cleaning techniques to provide a cost-effective and practical solution for the small enterprises and people in Bangladesh. The study proves the product's viability and usefulness by in-depth market research, technical studies, and performance assessments. Quantitative analyses and cost analyses also offer a strong basis for its design and execution.

In addition to meeting the increasing need for cleaning products, this creative strategy would act as a template for aspiring engineers and designers to create and assess their own cutting-edge goods.

Engineering Report151 Pages

CAD & SimulationSolidWorks + FEA

Material SelectionWeighted Matrix

BEP Payback4.8 Months

↳ End of Body Chapters. Proceeding to Appendices and Reference Materials. Next: Appendix A (Survey Questionnaire) →

Report Page 123 PDF Page 143 / 151

APPENDIX

Appendix A: Questionnaire for Survey

Field survey instrument administered to 34 participants across academic institutions, corporate offices, and commercial establishments in Dhaka.

Participant Demographic Information

Name: ___________________________

Age: _______

Address / Organization: ___________________________

Q01 How often do you clean your shoes?

Daily

Weekly

Monthly

Quarterly

Q02 How do you currently clean your shoes?

Hand wash

Wet wipes

Professional cleaning

Q03 How much do you spend on a single shoe cleaning?

Under 50/=

50-100 /=

100-150/=

150-200/=

Over 200/=

Q04 What challenges do you face when cleaning your shoes?

Time consuming

Ineffective

Unavailability

Report Page 124 PDF Page 144 / 151

Q05 How satisfied are you with your current shoe cleaning method?

Very satisfied

Satisfied

Neutral

Dissatisfied

Very dissatisfied

Q06 Would you be interested in a machine that cleans your shoes automatically?

Yes

No

Maybe

Q07 What features would be most important to you in a shoe cleaning machine?

Speed of cleaning

Effectiveness

Ease of use

Eco-friendliness

Q08 Would you prefer a machine that is portable or one that stays in one place?

Portable

Stationary

No preference

Q09 What factors influence your decision to purchase a new cleaning device?

Reviews

Brand reputation

Recommendations

Report Page 125 PDF Page 145 / 151

Q10 Have you seen similar products on the market?

Yes

No

Q11 What additional features would make a shoe cleaning machine more appealing to you?

Automation

Disinfectant

Shiner

Easy to operate

Q12 In which environment would the shoe cleaning machine be most used in your workplace?

Office lobby

Staff changing rooms

Warehouse/Factory

Hospital entryway

Q13 How often would you expect to perform maintenance on such a machine?

Weekly

Monthly

Quarterly

Yearly

Q14 How concerned are you about cross-contamination and hygiene in common areas like lobbies or entry points where the shoe cleaning machine might be placed?

Very concerned

Somewhat concerned

Not concerned

Q15 How important is it for the machine to have environmentally friendly features, such as energy efficiency or low water consumption?

Extremely important

Important

Neutral

Not important

Report Page 126 PDF Page 146 / 151

Q16 Would noise levels be a concern if the machine was placed in an area with frequent foot traffic?

Yes, it should be quiet

Noise is acceptable if it's efficient

No preference

Q17 How likely are you to recommend such a machine to other organizations if it meets your expectations?

Very likely

Likely

Neutral

Unlikely

Report Page 127 PDF Page 147 / 151

Appendix B: Result of Tensile Test and Physical Constants of Some Materials

Empirical material characterization standards, mechanical tensile/yield properties, and physical property tables utilized in structural design, component sizing, and finite element stress verification.

Table A.1Deterministic ASTM Minimum Tensile and Yield Strength for Some Hot-Rolled (HR) and Cold-Drawn (CD) Steels

Estimated minimum mechanical strength values for design safety factor evaluations per ASTM A6/A568 standards.

[The strengths listed are estimated ASTM minimum values in the size range 18 to 32 mm (¾ to 1¼ in). These strengths are suitable for use with the design factor defined in Sec. 1–10, provided the materials conform to ASTM A6 or A568 requirements or are required in the purchase specifications. Remember that a numbering system is not a specification.]

1 UNS No.	2 SAE / AISI	3 Process	4 Tensile Str, MPa (kpsi)	5 Yield Str, MPa (kpsi)	6 Elongation in 2 in, %	7 Reduction in Area, %	8 Brinell Hardness
G10060	1006	HR	300 (43)	170 (24)	30	55	86
G10060	1006	CD	330 (48)	280 (41)	20	45	95
G10100	1010	HR	320 (47)	180 (26)	28	50	95
G10100	1010	CD	370 (53)	300 (44)	20	40	105
G10150	1015	HR	340 (50)	190 (27.5)	28	50	101
G10150	1015	CD	390 (56)	320 (47)	18	40	111
G10180	1018	HR	400 (58)	220 (32)	25	50	116
G10180	1018	CD	440 (64)	370 (54)	15	40	126
G10200	1020	HR	380 (55)	210 (30)	25	50	111
G10200	1020	CD	470 (68)	390 (57)	15	40	131
G10300	1030	HR	470 (68)	260 (37.5)	20	42	137
G10300	1030	CD	520 (76)	440 (64)	12	35	149
G10350	1035	HR	500 (72)	270 (39.5)	18	40	143
G10350	1035	CD	550 (80)	460 (67)	12	35	163
G10400	1040	HR	520 (76)	290 (42)	18	40	149
G10400	1040	CD	590 (85)	490 (71)	12	35	170
G10450	1045	HR	570 (82)	310 (45)	16	40	163
G10450	1045	CD	630 (91)	530 (77)	12	35	179
G10500	1050	HR	620 (90)	340 (49.5)	15	35	179
G10500	1050	CD	690 (100)	580 (84)	10	30	197
G10600	1060	HR	680 (98)	370 (54)	12	30	201
G10800	1080	HR	770 (112)	420 (61.5)	10	25	229
G10950	1095	HR	830 (120)	460 (66)	10	25	248

Source. Data from 1986 SAE Handbook, p. 2.15. Adapted for mechanical design calculations.

Table A.2Physical Constants of Materials

Fundamental physical, thermodynamic, and elastic constants including modulus of elasticity, modulus of rigidity, Poisson's ratio, and unit weight.

Material	Modulus of Elasticity E		Modulus of Rigidity G		Poisson's Ratio ν	Unit Weight w
Material	Mpsi	GPa	Mpsi	GPa	Poisson's Ratio ν	lbf/in³	lbf/ft³	kN/m³
Aluminum (all alloys)	10.4	71.7	3.9	26.9	0.333	0.098	169	26.6
Beryllium copper	18.0	124.0	7.0	48.3	0.285	0.297	513	80.6
Brass	15.4	106.0	5.82	40.1	0.324	0.309	534	83.8
Carbon steel	30.0	207.0	11.5	79.3	0.292	0.282	487	76.5
Cast iron (gray)	14.5	100.0	6.0	41.4	0.211	0.260	450	70.6
Copper	17.2	119.0	6.49	44.7	0.326	0.322	556	87.3
Douglas fir	1.6	11.0	0.6	4.1	0.33	0.016	28	4.3
Glass	6.7	46.2	2.7	18.6	0.245	0.094	162	25.4
Inconel	31.0	214.0	11.0	75.8	0.290	0.307	530	83.3
Lead	5.3	36.5	1.9	13.1	0.425	0.411	710	111.5
Magnesium	6.5	44.8	2.4	16.5	0.350	0.065	112	17.6
Molybdenum	48.0	331.0	17.0	117.0	0.307	0.368	636	100.0
Monel metal	26.0	179.0	9.5	65.5	0.320	0.319	551	86.6
Nickel silver	18.5	127.0	7.0	48.3	0.322	0.316	546	85.8
Nickel steel	30.0	207.0	11.5	79.3	0.291	0.280	484	76.0
Phosphor bronze	16.1	111.0	6.0	41.4	0.349	0.295	510	80.1
Stainless steel (18-8)	27.6	190.0	10.6	73.1	0.305	0.280	484	76.0
Titanium alloys	16.5	114.0	6.2	42.4	0.340	0.160	276	43.4

Note. Adapted from engineering materials property databases and Ashby (2005). Conversion factor: 1 Mpsi = 6.89476 GPa.

Report Page 128 PDF Page 148 / 151

REFERENCES

All references are formatted according to the American Psychological Association (APA) 7th Edition guidelines, organized systematically across research domains with verified digital identifiers and archival links.

1. Primary Survey & Research Data

Fuad, M. M., et al. (2024). Customer needs, usage behavior, and product requirement survey for semi-automated shoe cleaning machine. Online survey instrument and response dataset hosted on Google Forms. (Survey Drive Link) [LINK] ↗

2. Institutional Demographics & Demand Forecasting (Dhaka Region)

University Grants Commission of Bangladesh. (2024). List of recognized private universities in Bangladesh. UGC Institutional Directory. (Total institutions: 115) [LINK] ↗

Bangladesh Bank. (2024). Commercial banking directory and branch network statistics: Dhaka division. Central Bank of Bangladesh. (Total branches in Dhaka: 1,200 private bank branches) [LINK] ↗

Ministry of Commerce & Trade Directories. (2024). Directory of multinational corporations and corporate offices operating in Dhaka. Scribd Commercial Publications. (Total corporate enterprises: Approximately 921 companies) [LINK] ↗

Bangladesh Bureau of Educational Information and Statistics. (2021). Bangladesh education statistics 2021. BANBEIS, Ministry of Education, Government of the People's Republic of Bangladesh. (Total schools and colleges in Dhaka: 324) [LINK] ↗

Kayak Lodging Database. (2024). Hotel registry and commercial accommodations directory in Dhaka metropolitan area. Kayak Commercial Travel Index. (Total verified hotels: 245) [LINK] ↗

Directorate General of Health Services. (2024, June 9). List of primary, secondary & tertiary level hospitals and clinics in Dhaka metropolitan area. Hospitals & Clinics Section Unit and HSM, Health Services Division, Ministry of Health and Family Welfare. (Total registered facilities: 15 + 3 + 43 + 48 + 6 + 5 + 16 = 136 institutions) [LINK] ↗

3. Design Analysis & Finite Element Modeling

Syaifudin, A., et al. (2013). S-N curve estimation in air and corrosive environment using finite element method. Prosiding Badan Kerjasama Teknik Mesin (BKSTM), Indonesia. [LINK] ↗

Report Page 129 PDF Page 149 / 151

4. Qualitative Analysis & Joining Methodologies

Kah, P., & Martikainen, J. (2022). Joining processes and modern fabrication techniques in mechanical assemblies. Journal of Advanced Joining Processes, 6, Article 100113. [DOI] ↗

Lancaster, J. F. (1999). Metallurgy of welding (6th ed.). Woodhead Publishing / Butterworth-Heinemann. [DOI] ↗

Barnes, T. A., & Pashby, I. R. (2010). Joining for lightweight vehicles and consumer product structures. In Materials, Design and Manufacturing for Lightweight Vehicles (pp. 275–311). Woodhead Publishing. [DOI] ↗

Tollenaere, M. (1998). Qualitative constraints in integrated design. In Integrated Design and Manufacturing in Mechanical Engineering (pp. 41–50). Springer Netherlands. [DOI] ↗

5. Quantitative Materials Science, Standards & Component Evaluation

Callister, W. D., & Rethwisch, D. G. (2007). Materials science and engineering: An introduction (7th ed.). John Wiley & Sons.

Radaj, D. (2017). Stresses, shrinkage, and distortion in weldments and structural joints. In Welding Residual Stresses and Distortion (pp. 243–289). Elsevier. [DOI] ↗

Parmley, R. O. (2000). Joints, connections, and structural fasteners. In Standard Handbook of Fastening and Joining (3rd ed.). McGraw-Hill. [DOI] ↗

Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 1–55. [LINK] ↗

Mano, M. M., & Ciletti, M. D. (2007). Digital design and logic systems (4th ed.). Prentice Hall. [LINK] ↗

Ashby, M. F. (2005). Materials selection in mechanical design (3rd ed., Chapter 2, 624 p.). Butterworth-Heinemann / Elsevier Science and Technology Rights Department, Oxford.

MatWeb LLC. (2024). AISI 1018 mild/low carbon steel, cold drawn mechanical property data sheet (Spec No. M862AN). MatWeb Material Property Data. [LINK] ↗

Report Page 130 PDF Page 150 / 151

6. Workshop Machinery, Equipment & Tooling Depreciation

ClickBD Industrial Machinery. (2024). Conventional center lathe machine market quotation and capital procurement schedule (Dhaka division). ClickBD Machinery Marketplace. [LINK] ↗

Weiss Machinery Co. (2023). What is the lifespan of a lathe machine? Practical lifecycle and maintenance guide. Weiss Tools Technical Journal. [LINK] ↗

Machine & Tools BD. (2024). Industrial 13mm bench drill press machine (Boky brand) technical specifications and retail pricing. Machine and Tools Bangladesh. [LINK] ↗

Daraz Industrial Tools. (2024). Inverter portable electric arc welding machine (ARC-300 IGBT) technical specification and price catalog. Daraz Bangladesh. [LINK] ↗

7. Raw Material Stock & Supply Costs

Nawabpur Metal Market. (2024a). Commercial pricing schedule for mild steel (MS) plate sheet (4 ft × 8 ft × 3 mm). Nawabpur Hardware Supplies. [LINK] ↗

Nawabpur Metal Market. (2024b). Commercial pricing schedule for stainless steel (SS 304) sheet (4 ft × 8 ft × 1 mm). Nawabpur Hardware Supplies. [LINK] ↗

Anhui Huixi Brush Co., Ltd. (2024). Industrial cylindrical spiral rotary cleaning roller brush (Nylon 6/6 bristles) specification and quotation. Made-in-China Industrial Platform. [LINK] ↗

8. Manufacturing Labor & Machinist Wage Baselines

Glassdoor Economic Research. (2024). Machine operator and CNC machinist average monthly salary benchmarks in Dhaka, Bangladesh. Glassdoor Salary Analytics. [LINK] ↗

Bdjobs.com. (2024). Technical, vocational, and machine operator wage survey across manufacturing enterprises. Bdjobs Employment Research. [LINK] ↗

Report Page 131 PDF Page 151 / 151

9. Component Purchase & Mechanical Hardware Costs

Daraz Bangladesh Industrial. (2024a). 0.5 modulus brass worm gear and shaft set (32mm, 60 teeth worm wheel). Daraz Mechanical Transmission Components. [LINK] ↗

Daraz Bangladesh Industrial. (2024b). Spur gear modules and steel pinion drive catalog. Daraz Industrial Components Hub. [LINK] ↗

Daraz Electronics. (2024c). Universal AC 220V to adjustable DC 12V–24V (4.5A, 96W) multi-head converter power adapter charger. Daraz Power Supplies. [LINK] ↗

Fixit Hardware Bangladesh. (2024). Hexagonal bolt and nut fasteners (10mm × 40mm galvanized steel). Fixit Hardware Tools & Fasteners. [LINK] ↗

HCH Bearing Industrial. (2024). Deep groove radial ball bearing 6000-2RS (10mm × 26mm × 8mm, rubber sealed chrome steel). Daraz BD Bearings & Transmission. [LINK] ↗

Bemonoc Mechatronics / Ubuy. (2024). High-torque permanent magnet DC brush motor (12V, 3000 RPM micro-drive). Ubuy Bangladesh Mechatronics. [LINK] ↗

Universal Shoe Care Products. (2024). Solid wax shoe polish and colorless leather maintenance oil (wax-like color repair formulation). Daraz Bangladesh Consumer Care. [LINK] ↗

BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY

DEPARTMENT OF INDUSTRIAL AND PRODUCTION ENGINEERING

Semi-Automated Shoe Cleaning Machine

Semi-Automated Shoe Cleaning Machine

Submitted To

Submitted By: Group- B14

COPYRIGHT NOTICE

FORWARDING LETTER

PREFACE

ABSTRACT

ACKNOWLEDGEMENT

TABLE OF CONTENTS

List of Tables

List of Illustrations

Introduction

1.1Product Design

1.2Proposed Product Ideas

Multifunctional Canal & River Cleaning Machine

Main components

Notable features

Multi-Functional Cleaner

Main components

Notable features

Pedal-Powered Dishwasher

Main components

Notable features

Semi-Automated Shoe Cleaning Machine

Main components

Notable features

1.3Selected Proposal

Semi-Automated Shoe Cleaning Machine

1.3.1Reasons for Selection

Understanding Customer Needs Through Survey

2.1Introduction

2.2Survey Locations

Bangladesh University of Engineering and Technology (BUET)

Bright River Bangladesh Ltd.

Rural Development Project of Jamalpur

BRAC Bank PLC, Anik Tower

University of Dhaka

Pridesys IT Ltd.

2.3Survey Results

How often do you clean your shoes?

How do you currently clean your shoes?

How much do you spend on a single shoe cleaning?

What challenges do you face when cleaning your shoes?

How satisfied are you with your current shoe cleaning method?

Would you be interested in a machine that cleans your shoes automatically?

What features would be most important to you in a shoe cleaning machine?

Would you prefer a portable machine or one that stays in one place?

What factors influence your decision to purchase a new cleaning device?

Have you seen similar products on the market?

What additional features would make a shoe cleaning machine more appealing to you?

In which workplace environment would the shoe cleaning machine be used most?

How often would you expect to perform maintenance on such a machine?

How concerned are you about cross-contamination and hygiene in common areas where the machine might be placed?

How important are environmentally friendly features such as energy efficiency or low water consumption?

Would noise levels be a concern in an area with frequent foot traffic?

How likely are you to recommend such a machine to other organizations if it meets your expectations?

2.4Customer Requirement Evaluation

2.5Conclusion

Incorporating the Voice of Customer in Product Design with Quality Function Deployment (QFD)

3.1Introduction

3.2Customer Requirement and Engineering Requirement

3.3Quality Function Deployment's House of Quality

QFD Matrix Relationships

Roof Technical Correlations

3.4Conclusion

Functional Decomposition

4.1Introduction

Identify the primary function

Develop sub-functions

Organize sub-functions

Refine sub-functions

4.2Black Box Model

4.3Component Hierarchy

4.4Cluster Function Structure

4.5Conclusion

Design Analysis

5.1Introduction