Table Of ContentCellular Manufacturing Systems
To Bati Devi, Ravi Kumar and Sheenoo
N.5.
To Sumathi, Prashanthi and Prajan
D.R.
Cellular Manufacturing
Systems
Design, planning and control
Nanua Singh
Department of Industrial and Manufacturing Engineering,
Wayne State University, Detroit, USA
and
Divakar Raiamani
Department of Mechanical and Industrial Engineering,
University of Manitoba, Winnipeg, Canada
CHAPMAN &. HALL
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~c, 1996 Chapman & Hall
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TSBN-13: 978-1-4612-8504-5 e-TSBN-13: 978-1-4613-1187-4
DOl: 10.1007/978-1-4613-1187-4
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Contents
Preface xi
1 Introduction 1
1.1 Production systems and group technology 2
1.2 Impact of group technology on system performance 4
1.3 Impact on other functional areas 7
1.4 Impact on other technologies 9
1.5 Design, planning and control issues in cellular
manufacturing 10
1.6 Overview of the book 11
1.7 Summary 13
Problems 13
References 13
Further reading 14
2 Part family formation: coding and classification systems 15
2.1 Coding systems 17
2.2 Part family formation 19
2.3 Cluster analysis 22
2.4 Related developments 28
2.5 Summary 30
Problems 31
References 31
3 Part-machine group analysis:methods for cell formation 34
3.1 Definition of the problem 35
3.2 Bond energy algorithm (BEA) 38
3.3 Rank order clustering (ROC) 42
3.4 Rank order clustering 2 (ROC 2) 46
3.5 Modified rank order clustering (MODROC) 50
VI Contents
3.6 Direct clustering algorithm (DCA) 52
3.7 Cluster identification algorithm (CIA) 54
3.8 Modified CIA 56
3.9 Performance measures 58
3.10 Comparison of matrix manipulation algorithms 64
3.11 Related developments 64
3.12 Summary 65
Problems 66
References 68
4 Similarity coefficient-based clustering: methods for cell
formation 70
4.1 Single linkage clustering (SLC) 71
4.2 Complete linkage clustering (CLC) 74
4.3 Average linkage clustering (ALC) 75
4.4 Linear cell clustering (LCC) 78
4.5 Machine chaining problem 80
4.6 Evaluation of machine groups 83
4.7 Parts allocation 87
4.8 Groupability of data 88
4.9 Related developments 91
4.10 Summary 93
Problems 94
References 95
5 Mathematical programming and graph theoretic
methods for cell formation 97
5.1 P-median model 97
5.2 Assignment model 99
5.3 Quadratic programming model 103
5.4 Graph theoretic models 104
5.5 Nonlinear model and the assignment allocation
algorithm (AAA) 107
5.6 Extended nonlinear model 114
5.7 Other manufacturing features 117
5.8 Comparison of algorithms for part-machine
grouping 119
5.9 Related developments 121
5.10 Summary 123
Problems 124
References 125
Contents VII
6 Novel methods for cell formation 128
6.1 Simulated annealing 129
6.2 Genetic algorithms 134
6.3 Neural networks 141
6.4 Related developments 151
6.5 Summary 151
Problems 152
References 152
7 Other mathematical programming methods for cell
formation 154
7.1 Alternate process plans 155
7.2 New cell design with no inter-cell
material handling 156
7.3 New cell design with inter-cell
material handling 163
7.4 Cell design with relocation considerations 169
7.5 Cell design considering operational variables 171
7.6 Related developments 174
7.7 Summary 176
Problems 177
References 178
8 Layout planning in cellular manufacturing 181
8.1 Types of layout for manufacturing systems 182
8.2 Layout planning for cellular manufacturing 186
8.3 Design of robotic cells 201
8.4 Summary 208
Problems 208
References 210
9 Production planning in cellular manufacturing 212
9.1 Basic framework for production planning
and control 213
9.2 Production planning and control
in cellular manufacturing systems 228
9.3 Operations allocation in a cell with
negligible setup time 234
9.4 Minimum inventory lot-sizing model 238
9.5 Summary 243
References 244
Further reading 245
VIII Contents
10 Control of cellular flexible manufacturing systems
Jeffrey S. Smith and Sanjay B. Joshi 246
10.1 Control architectures 247
10.2 Controller structure components 257
10.3 Control models 266
10.4 Summary 271
References 271
Index 275
Preface
Batch manufactcring is a dominant manufacturing activity in the world,
generating a great deal of industrial output. In the coming years, we are
going to witness an era of mass customization of products. The major
problems in batch manufacturing are a high level of product variety and
small manufacturing lot sizes. The product variations present design
engineers with the problem of designing many different parts. The
decisions made in the design stage significantly affect manufacturing
cost, quality and delivery lead times. The impacts of these product
variations in manufacturing are high investment in equipment, high
tooling costs, complex scheduling and loading, lengthy setup time and
costs, excessive scrap and high quality control costs. However, to
compete in a global market, it is essential to improve the productivity in
small batch manufacturing industries. For this purpose, some innovative
methods are needed to reduce product cost, lead time and enhance
product quality to help increase market share and profitability. What is
also needed is a higher level of integration of the design and
manufacturing activities in a company. Group technology provides such
a link between design and manufacturing. The adoption of group
technology concepts, which allow for small batch production to gain
economic advantages similar to mass production while retaining the
flexibility of job shop methods, will help address some of the problems.
The group technology (GT) approach originally proposed by
Mitrofanov and Burbidge is a philosophy that exploits the proximity
among the attributes of given objects. Cellular manufacturing (CM) is an
application of GT in manufacturing. CM involves processing a collection
of similar parts (part families) on a dedicated cluster of machines or
manufacturing processes (cells). The cell formation problem in cellular
manufacturing systems (commonly understood as the cell design
problem in literature) is the decomposition of the manufacturing
systems into cells. Part families are identified such that they are fully
processed within a cell. The cells are formed to capture the inherent
advantages of GT like reduced setup times, reduced in-process
inventories, improved product quality, shorter lead time, reduced tool
requirements, improved productivity, better overall control of
operations, etc. The common disadvantages are lower machine and
labor utilization and higher investment due to duplication of machines
x
Preface
and tools.
The problem of cell design is a very complex exercise with wide
ranging implications for any organisation. Normally, cell design is
understood as the problem of identifying a set of part types that are
suitable for manufacture on a group of machines. However, there are a
number of other strategic level issues such as level of machine flexibility,
cell layout, type of material handling equipment, types and number of
tools and fixtures, etc. that should be considered as part of the cell
design problem. Further, any meaningful cell design must be compatible
with the tactical! operational goals such as high production rate, low
WIP, low queue length at each work station, high machine utilization,
etc. A lot of research has been reported on various aspects of design,
planning and control of cellular manufacturing systems. Various
approaches used include coding and classifications, machine-component
group analysis, similarity coefficients, knowledge-based, mathematical
programming, fuzzy clustering, clustering, neural networks, and
heuristics among others.
The emphasis in this book is on providing a comprehensive treatment
of· various aspects of design, planning and control of cellular
manufacturing systems. A thorough understanding of the cell formation
problem is provided and most of the approaches used to form cells are
provided in Chapters 2 through 7. Issues related to layout design,
production planning and control in cellular manufacturing systems are
covered in Chapters 8, 9 and 10 respectively.
The book is directed towards first and second year graduate students
from the departments of Industrial, Manufacturing Engineering and
Management. Students pursuing research in cellular manufacturing
systems will find this book very useful in understanding various aspects
of cell design, planning and control. Besides graduate engineering and
management students, this book will also be useful to engineers and
managers from a variety of manufacturing companies for them to
understand many of the modern cell design, planning and control issues
through solved examples and illustrations.
The book has gone through thorough classroom testing. A large
number of students and professors have contributed to this book in
many ways. The names of Dr G.K. Adil, Pradeep Narayanswamy,
Parveen S. Goel and Saleh Alqahtany deserve special mention. We are
grateful to Dr Jeffery S. Smith of Texas A & M University and Dr Sanjay
Joshi of Penn State University for contributing Chapter 10 in this book.
We are also indebted to Mark Hammond of Chapman & Hall (UK) for
requesting us to write this book. We appreciate his patience and
tolerance during the preparation of the manuscript.
The cover illustration is reproduced courtesy of Giddings & Lewis
(USA).
Nanua Singh
September 1995. Divakar Rajamani
