Selection of optimal machine tool configuration by simultaneous consideration of reliability and maintenance.

SELECTION OF OPTIMAL MACHINE TOOL CONFIGURATION BY SIMULTANEOUS CONSIDERATION OF RELIABILITY AND

MAINTENANCE

By

BHUPESH KUMAR LAD

Submitted

in fulfilment of the requirements of the degree of

Doctor of Philosophy

to the

INDIAN INSTITUTE OF TECHNOLOGY DELHI

March 2010

CERTIFICATE

This is to certify that the thesis entitled "Selection of Optimal Machine Tool Configuration by Simultaneous Consideration of Reliability and Maintenance" being submitted by Mr.

Bhupesh Kumar Lad to the Indian Institute of Technology Delhi for the award of the degree of Doctor of Philosophy is a record of original research work carried out by him. He has worked under my guidance and supervision and has fulfilled the requirements for the submission of this thesis, which to my knowledge has reached the requisite standard.

The results contained in this thesis have not been submitted, in part or full, to any other university or institute for the award of any degree or diploma.

(Dr. Makarand S. Kulkarni)

Assistant Professor, Department of Mechanical Engineering, Indian Institute of Technology Delhi,

New Delhi-110016, INDIA

ACKNOWLEDGEMENTS

I take this opportunity to express my deep sense of respect and gratitude to Dr. Makarand S.

Kulkarni for his patient, continuous and valuable guidance and supervision. His constant encouragement, friendly interactions, and constructive support have enabled this work to achieve its present form and status. It would have been next to impossible to write this thesis without his help and able guidance. His insightful discussions about the research had a profound effect on my way of reading, writing, and thinking, in general. He also provided helpful career advice and suggestions whenever needed. I am greatly inspired by his way of communication. I hope that I could to someday be able to command audience as well as he can. I feel greatly privileged to be one of his students.

I wish to express my heartfelt appreciation to my parents and sisters for bearing with me for the inconvenience caused during this research. Their patience, understanding and continuous encouragement has played an important role in the completion of this work. I owe the entire of my academic achievements to my parents.

I am thankful to I.I.T.Delhi for giving me an opportunity to carry out the research work and providing all the facilities.

I am extremely thankful to Micromatic Grinding Technologies Ltd., (MGTL) Ghaziabad, for extending technical support and supplying industrial data and sharing their knowledge for this research work. In specific, I would like to thank Mr. N.K.Dhand (Managing Director, MGTL) for his constant encouragement to this project. I further extend my thanks to Mr.

Sanjay Kumar, Mr. Vikas Dang, Mr. Roy, Mr. Tyagi, and Mr. Bhaghel for their cooperation during the research. I am also thankful to all the respondents who have responded during the research survey carried out as a part of this research.

I am immensely grateful to Prof. S.G. Deshmukh, Mechanical Engineering Department, IIT Delhi for his ever-ready support and personal attention even in the busiest of his schedule.

I am also thankful to Prof. O.P.Gandhi, ITMMEC, IIT Delhi and a member of my Student Review committee (SRC). He was always ready to help whenever needed and provided constructive comments on my research work.

My special thanks are due to Prof. Arun Kanda, Chairman of my SRC, Mr. A.D.Gupta, another member of SRC, for their valuable comments and inputs during my work and presentations.

I am thankful to Dr. V. Jain for his friendly interactions and suggestions during my stay at IIT Delhi.

I would like to express my recondite thanks to my friend Ms. Divya Pandey, who has given me company and shared the odd moments during this research work. I shall be failing in my duty if I do not express my thankfulness for the continuous help extended to me during research work by my friends Mr. Anuj Prakash, Mr. Prashant Ambad, Md. Asjad, Mr.

Gajanan Panchal, Mr. Avinash Samvedi, and Mr. Kamala Kanta Sahoo.

I will forever be thankful to my former college research advisors, Dr. D.S.Bal and Mr.

A.C.Shukla who helped me in building the foundation for my research career.

People here are genuinely nice and want to help you out and I am glad to have interacted with many. I am thankful to all of them.

Bhupesh Kumar Lad

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ABSTRACT

In this research, a design methodology for simultaneous optimization of reliability and maintenance of machine tools based on Life Cycle Cost (LCC) and other performance requirements of the users has been developed. The methodology is explored in the context of three different functional design scenarios, viz., design of general purpose machine tools, design of special purpose machine tools, and design of customized machine tools. It has also helped in supporting decisions related to reliability improvement of existing design by identifying the critical components/subassemblies in a machine tool. While the user's performance requirement models and maintenance models form an essential part of the proposed methodology, it is also supported by expert judgement based parameter estimation methods in the absence of sufficient field failure data, thereby increasing the applicability of the proposed design methodology.

A survey was conducted with a view to have a foretaste of machine tool reliability related issues from the field. Both, user's and manufacturer's view point was studied. It was observed that users usually do not express their reliability requirements explicitly in quantitative terms. In general, machine tool users are more concerned about their operational performance and they judge the reliability of a machine tool based on how well it performs in terms of their shop floor level performance measures. Models are therefore developed to link user's performance requirements with the machine tool reliability and maintenance parameters. Following models have been developed:

1. Availability model 2. Performance rate model 3. Quality rate model

4. Overall Equipment Effectiveness (OEE) model 5. Throughput rate model

6. Life Cycle Cost (LCC) model 7. Cost Per Piece (CPP) model

These models express the user's performance measures in terms of reliability and maintenance parameters. Models also consider the effect of user's cost structures and user's shop floor policy parameters. In order to capture the interdependencies of number of failures and optimal number of preventive repairs and replacements in a given period of time, maintenance models are developed under different maintenance scenarios. Following three maintenance scenarios are identified in a machine tool based on types of preventive maintenance actions and degree of repairs.

1. Perfect corrective and preventive replacement;

2. Imperfect corrective repair, imperfect preventive repair and perfect replacement;

3. Minimal corrective repair, imperfect preventive repair, imperfect overhaul, and perfect replacement;

For each scenario, a maintenance optimization problem is formulated. For the case of imperfect maintenance, complexities in obtaining the optimal preventive maintenance schedule are reduced by developing some approximate models for estimating the number of failures. Along with these models, guidelines for selecting an appropriate range for simulation are provided that helped in increasing the accuracy of prediction. For the case of minimal corrective repair, a conditional number of failures model is developed. This model, apart from regular preventive repair and replacement, also helps the designer in considering the effect of major overhauls on the optimal maintenance schedule decisions. It is demonstrated that the optimal maintenance schedule decision also depends on the user's cost structure and shop floor policy parameters.

In order to use above mentioned performance and maintenance models, in reliability and maintenance optimization it is necessary to have time-to-failure data for different components

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and subassemblies. In the case of machine tools, such data in most of the cases is either not available or is available only partially. In order to enable the designer to use the proposed framework in such situations, an expert judgement based methodology is proposed to obtain the parameters of time-to-failure distributions for both repairable and non repairable components/subassemblies.

Finally, utilizing the performance models, maintenance models and expert judgement based parameter estimation methods; two different design methodologies are proposed. First design methodology allows selection of optimal machine tool configuration based on Life Cycle Cost (LCC) and other performance requirements of the users by simultaneously considering reliability and maintenance at the design stage under three different functional design scenarios, viz., general purpose machine tool design, special purpose machine tool design, and customized machine tool design. In case of general purpose machine tool design, the methodology provides optimized reliability configuration and optimized maintenance schedules. If the user of such machine tools, at the time of the purchasing of machine, is able to provide his cost structure and shop floor level policy parameters, then the methodology can also be used to customize maintenance schedules for the optimized reliability configuration of the general purpose design. For special purpose machine tool design, the methodology provides customized reliability configuration and customized maintenance schedules.

Similarly, for customized machine tool design, the methodology allows selecting optimal reliability configuration and customized maintenance schedule for standard components, while for customer specific components/subassemblies, it allows selecting customized reliability configuration and customized maintenance schedule.

Second design methodology is developed to help the designer in improving the design of the existing system by identifying the critical components/subassemblies. A cost based Failure Consequence Analysis (FCA) is proposed for this purpose. The proposed methodology is

helpful to the machine tool manufacturer in making effective cost driven decisions while improving the reliability performance of the machine tool. It also provides guidance to the machine tool users in identifying the areas where they can focus to obtain better performance from the machine.

In essence, the outcome of this research is a systematic, more practical and user oriented approach for reliability and maintenance based design of machine tools. It can also be viewed as a life cycle oriented approach for reliability and maintenance based design of machine tools.

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TABLE OF CONTENTS

Certificate i

Acknowledgement ii-iii

Abstract iv-vii

Table of contents viii-xii

List of figures xiii

List of tables xiv-xvi

List of abbreviations and notations xvii-xxii

CHAPTER 1: INTRODUCTION 1-22

1.1 Permeable 1

1.1.1 Motivation for the present work 2

1.1.2 Research structure 4

1.2 The problem on hand 4

1.2.1 Machine tool failure 4

1.2.2 Machine tool design 7

1.2.3 Machine tool function design scenarios 8 1.2.4 Reliability improvement of existing design 9

1.2.5 Failure data 10

1.2.6 Maintenance scenarios 12

1.2.7 Problem statements and issues 13

1.3 Research gaps and objectives 13

1.4 Methodology 15

1.5 Scope of research 18

1.6 Thesis outline 20

1.7 Summary 22

CHAPTER 2: LITERATURE REVIEW 23-69

2.1 Introduction 23

2.2 Optimal reliability design 27

2.2.1 Problem description 29

2.2.2 Problem formulation 32

2.2.2.1 Reliability allocation problem 32

2.2.2.2 Redundancy allocations formulation 34 2.2.2.3 Reliability and redundancy allocation formulation 35 2.2.2.4 Multi-objective optimization formulations 35 2.2.2.5 Formulation for repairable system 36

2.2.3 Problem solution 37

2.3 Preventive maintenance optimization 39

2.3.1 Problem addressed and assumptions made regarding influence 40 of repair on equipment age

2.3.2 Maintenance cost model 43

2.4 Failure data collection and expert judgement in reliability study 45 2.5 Capturing customer's reliability requirements 48

2.6 Reliability analysis and improvements 57

2.7 Relevant research projects reported in the literature 62

2.8 Summary 66

CHAPTER 3: MODELS FOR DERIVING RELIABILTY 71-95 REQUIREMENTS OF MACHINE TOOLS

3.1 Introduction 71

3.2 Research survey 73

3.2.1 Machine tool reliability: user's view point 73

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3.2.2 Relationship of user's performance measures with reliability 80 and maintenance parameters: literature perspective

3.2.3 Machine tool reliability: designer's view point 81 3.3 Mechanism to link users' operational measures with machine reliability 82

and maintenance parameters

3.3.1 Availability model 83

3.3.2 Performance rate model 86

3.3.3 Quality rate model 86

3.3.4 Overall equipment effectiveness model 88

3.3.5 Throughput rate model 89

3.3.6 Life cycle cost (LCC) model 89

3.3.7 Cost per piece (CPP) model 92

3.4 Summary 93

CHAPTER 4: EXPERT JUDGEMENT BASED PARAMETER 97-129 ESTIMATION METHOD FOR MACHINE TOOL RELIABILTY

ANALYSIS

4.1 Introduction 97

4.2 Parameter estimation in reliability engineering 99 4.3 Expert judgement as an alternative source of data in reliability studies 100 4.4 Expert judgement based parameter estimation methods 101

4.4.1 Non-repairable component 102

4.4.1.1 Goodness test for results obtained from the expert 116 judgement based method

4.5 Repairable component 123

4.6 Some desirable properties of a "Good" estimator 128

4.7 Summary 129 CHAPTER 5: MACHINE TOOL MAINTENANCE SCENARIOS, 141-157 MODELS AND OPTIMIZATION

5.1 Introduction 131

5.2 Machine tool maintenance scenarios 133

5.3 Preventive maintenance optimization models for different maintenance 136 scenarios

5.3.1 Preventive maintenance optimization in maintenance scenario 138 1 (MScl) (Replacement model)

5.3.2 Preventive maintenance optimization in maintenance scenario 143 2 (MSc2) (repair-replacement model)

5.3.3 Preventive maintenance optimization in maintenance scenario 148 3 (MSc 3) (overhauling model)

5.4 Summary 156

CHAPTER 6: SELECTION OF OPTMLA MACHINE TOOL 159-183 CONFIGURATION BY SIMULTENOUS CONSIDERATION OF

RELIABILITY AND MAINTENANCE

6.1 Introduction 159

6.2 Machine tool functional design scenarios 161

6.2.1 Special purpose machine tool design 161

6.2.2 General purpose machine tool design 161

6.2.3 Customized machine tool design 161

6.3 Simultaneous optimization of reliability and maintenance of machine 162 tools

6.4 Problem formulation 164

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6.5 Problem solution 167 6.6 Simultaneous optimization of reliability and maintenance under three 168

functional design scenarios

6.6.1 Simultaneous optimization of special purpose machine tool 168 6.6.2 Simultaneous optimization of general purpose machine tool 176

design scenario

6.6.3 Simultaneous optimization of customized machine tool design 179

6.7 Summary 182

CHAPTER 7: RELIABILITY PERFORMANCE IMPROVEMENT OF 185-202 EXISTING DESIGN

7.1 Introduction 185

7.2 Failure mode and effects analysis 187

7.3 Proposed cost based Failure Consequence Analysis (FCA) approach 188

7.4 Summary 202

CHAPTER 8: CONCLUSION 203-215

8.1 Summary 203

8.2 Contribution of the research 211

8.3 Utility of the research work 212

8.4 Limitation and future scope of the study 213

REFERENCES 216-240

APPENDICES 241-245

APPENDIX Al: Kijima's Model 241

APPENDIX A2: List of Publication from research 242 APPENDIX A3: Biography of researcher 244