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Title of Thesis

Operational Design of a Cellular Manufacturing System

Author(s)

Adnan Tariq

Institute/University/Department Details
Department of Mechanical Engineering, College of Electrical and Mechanical Engineering / National University of Sciences and Technology, Rawalpindi
Session
2010
Subject
Mechanical Engineering
Number of Pages
251
Keywords (Extracted from title, table of contents and abstract of thesis)
Iris, Localization, Grayscale, Texture, Analysis, Recognition, Bit, Planes, verification, human, beings, security

Abstract
Cellular Manufacturing (CM), which contains the flexibility of Job-Shop and at the same time has a higher rate of production as flow lines, is proving to be a useful substitute for the production carried out in batches. In spite of the fact that there are so many benefits associated with CM but designing CM, for real world problems, is a very complex job. Since the main task in designing a CM is grouping of machines into cells and parts into corresponding families, therefore, most of the research carried out so far has considered the Cellular Manufacturing System (CMS) design as a Machine-Part grouping problem only and focus on the operational aspects of the design has been very little. Once the Machine-Part grouping stage is over, scheduling of the system is supposed to be the next stage in completing the operational design of a CMS. This is the stage where important production related information; such as processing sequence and processing time is taken into consideration. Scheduling is very essential as it enhances productivity and maximizes the usefulness of a given manufacturing system by utilizing the available resources in an optimized manner. Therefore, alongside Machine-Part grouping, scheduling is of paramount importance too, as it ensures proper utilization of resources.
In order to carryout a complete operational design of CMS, a two stage methodology has been developed in this research. First, the problem of Machine-Part grouping (CMS design) is solved, and then sequencing and scheduling of parts on machines is carried out. Since each cell is like a Job-Shop, therefore the scheduling part of the problem is solved using a similar approach as in case of a Job-Shop scheduling problem (JSSP).
Separate hybrid tools, for solving Machine-Part grouping problem and Job-Shop Scheduling Problem (JSSP), has been developed by combining Genetic Algorithms (GA) with Local Search Heuristics (LSH). Each tool’s effectiveness has been verified, separately, by solving a number of benchmark problems from literature. Finally, the two tools are combined in such a manner that the output of the Machine-Part grouping serves as an input to the tool developed for the scheduling of Job-Shop. Final outcome of the program is a cellular arrangement of the system (machine groups and corresponding part families) and detailed information about the sequencing and scheduling of the system.
The development of two effective hybrid GA based tools, for Machine-Part grouping and Job-Shop Scheduling, and their combination are the main contributions of this research..

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3,095 KB
S. No. Chapter Title of the Chapters Page Size (KB)
1 0 CONTENTS

 

4
39 KB
2

1

INTRODUCTION

1.1 Introduction
1.2 Group Technology (GT)
1.3 Job-Shop Manufacturing
1.4 Flow Line Manufacturing
1.5 Cellular Manufacturing
1.6 Advantages of Cellular Manufacturing
1.7 Problem Definition
1.8 Research Objectives
1.9 Conceptual Approach
1.10 Contributions
1.11 Organization of Thesis
1.12 Summary

13
105 KB
3 2 LITERATURE REVIEW – GENETIC ALGORITHMS

2.1 Introduction
2.2 Artificial Intelligence (AI)
2.3 Genetic Algorithms (GA)
2.4 Summary

27
72 KB
4 3 LITERATURE REVIEW – CELLULAR MANUFACTURING SYSTEM DESIGN TECHNIQUES

3.1 Introduction
3.2 Classification of Cellular Manufacturing System (CMS) design techniques
3.3 Evaluation of solutions in GT
3.4 Summary

34
248 KB
5 4 LITERATURE REVIEW – JOB-SHOP SCHEDULING

4.1 Introduction
4.2 Scheduling
4.3 Job-Shop Scheduling
4.4 Solution Techniques to Handle Job-Shop Scheduling Problems (JSSP)
4.5 Summary

71
112 KB
6

5

METHODOLOGY FOR MACHINE-PART GROUPING

5.1 Introduction
5.2 Hybrid GA for Machine-Part grouping
5.3 Cell Formation Problem
5.4 Methodology for the Hybrid GA for Machine-Part Grouping
5.6 Numerical Example of Machine-Part grouping
5.7 Sensitivity Analysis
5.8 Summary

84
297 KB
7

6

METHODOLOGY FOR CELL SCHEDULING AND COMBINATION WITH MACHINE-PART GROUPING

6.1 Introduction
6.2 Scheduling of a CMS
6.3 A Hybrid GA for JSSP
6.4 The Standard JSSP
6.5 Methodology for the Hybrid GA for JSSP
6.6 Numerical Example of Job-Shop Scheduling
6.7 Sensitivity Analysis
6.8 Combined Methodology for Operational Design of a CMS
6.9 Numerical Example of Combined Model
6.10 Summary

122
296 KB
8

7

RESULTS AND DISCUSSIONS

7.1 Introduction
7.2 Performance and Analysis of Hybrid GA for Machine-Part Grouping
7.3 Statistical Analysis
7.4 Formation of Single Machine Cells
7.5 Computational Results and Discussion (Hybrid GA for JSSP)
7.6 Computational Results and Discussion (Combined Model)
7.7 Summary

159
244 KB
9

8

CONCLUSION AND RECOMMENDATIONS FOR FUTURE RESEARCH STUDY

8.1 Introduction
8.2 Conclusion of Hybrid GA for Machine-Part Grouping
8.3 Conclusion of Hybrid GA for Job-Shop Scheduling
8.4 Conclusion of Combined Model (Operational Design of a CMS)
8.5 Directions for Future Research
8.6 Summary

179
73 KB
10 9 REFERENCES

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176 KB