DEVELOPMENT OF AN
AUTOMATED MANUFACTURABILITY EVALUATION SYSTEM FOR SHEET METAL COMPONENTS
by
KOLLA VENKATA RAMANA
MECHANICAL ENGINEERING DEPARTMENT
Submitted
in fulfilment of the requirements of the degree of DOCTOR OF PHILOSOPHY
to the
INDIAN INSTITUTE OF TECHNOLOGY DELHI December, 2004
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Certificate
This is to certify that the thesis entitled 'Development of an Automated Manufacturability Evaluation System for Sheet Metal Components' submitted by Kolla Venkata Ramana to the Indian Institute of Technology Delhi, for the award of the degree of Doctor of Philosophy, is a record of the original bonafide research work carried out by him under my guidance and supervision. The results contained in it have not been submitted in part or full to any other institute or university for the award of any degree/diploma.
Dr. P. V. Madhusudhan Rao Associate Professor Mechanical Engineering Department Indian Institute of Technology Delhi New Delhi
Acknowledgement
This thesis symbolizes an important milestone in the journey of my life. I take this opportunity to express my sincere gratitude to Dr. P. V. Madhusudhan Rao, my Ph.D.
guide and research supervisor at IIT Delhi, and all those who made this possible.
Dr. Rao initiated me into the world of automated manufacturability evaluation and the associated data and knowledge modeling concepts, which formed a backbone of this thesis. I am grateful for his expert guidance and wise counsel that enabled me to enrich this exciting domain. My last five years of interaction with him has been a great learning experience. I am immensely benefited by his devotion for the research, his ability to see things that are not obvious and his perseverance to pursue creative leads in research.
Besides being a source of immense knowledge and experience, he is very kind and caring with great compassion and love for the students. I will forever cherish my close association with him.
I am grateful to Mr. T. Muni Sekhar Reddy for supporting my decision to join Ph.D. I am thankful to the faculty and staff members of IIT Delhi, especially Prof. T. K. Kundra, Prof. G. S. Sekhon and Dr. D. Ravi Kumar for their constructive criticism and valuable comments on my research. I am also thankful to the examiners of this thesis, B. 0. Nnaji of University of Pittsburgh, Pittsburgh, USA and S. S. Pande of IIT Bombay, India, for providing their valuable comments. I lack words to express my gratitude to Mr. Ram Chander of N. C. Lab who helped me at every stage. My research is immensely benefited from the discussions with my friends and fellow researchers at IIT Delhi: D. Vinod Jacob, Dr. K. Rama Bhupal Reddy and Dr. K. Srinivasa Rao. I am grateful to Dr. Shaw
C. Feng of NIST, Gaithersburg, Maryland, USA for his valuable comments on one of my research papers. I thank all my friends and colleagues at IIT Delhi, for their help and support during this endeavour.
I am thankful to CSIR, New Delhi for sanctioning me foreign travel grant for presenting a research paper at ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Montreal, Canada, 2002. I am grateful to IIT Delhi for funding me to present a research paper at International Symposium on Product Life Cycle Management, Bangalore, India, 2003. Thanks are also due to DST, New Delhi and IIT Delhi for sanctioning grants for presenting a research paper at 34th International Conference on Computers & Industrial Engineering, San Francisco, California, USA, 2004.
I am grateful to my friend Mr. M. Sreenivasa Reddy for his support and encouragement in every moment of my life. I am indebted to my family members for their support in this long endeavour. Especially my wife Madhavi had to endure my absence from her and from many family occasions. I am very grateful to my mother Koteswari, father Narasimha Rao and brothers Durga Prasad and Dr. Nageswara Rao for their encouragement, love and support.
Kolla Venkata Ramana
Abstract
Automated Ananufacturability evaluation of a given design is a key requirement in realizing the integration of design and process planning activities. The purpose of such an evaluation is to assist designers in their effort to come up with manufacturable parts economizing in terms of cost and time. The present work deals with one such system developed for automated manufacturability evaluation of sheet metal components.
The present research work is different from previous attempts in many ways. Firstly it combines both rule-based and plan-based methods of manufacturability evaluation.
Secondly it covers all three phases of manufacturability evaluation namely manufacturability verification, manufacturability quantification and manufacturability optimization. Thirdly more complete data and knowledge models of product and process are used for realizing design-process planning integration with a relation among their representations. The scope of the present system covers those sheet metal parts which can be manufactured by shearing (blanking and piercing) and bending processes.
In this work a framework for automated manufacturability evaluation with data and knowledge models is proposed to realize design-process planning integration. Based on the proposed framework a more comprehensive system for automated manufacturability evaluation of sheet metal components is developed. The prime components of the present system are feature reasoning, design evaluation, process planning and, data and knowledge modeling.
Feature reasoner recognizes sheet metal features and extracts feature and part related information from the part model, stores it as feature data, and makes it available to design
evaluator and process planner simultaneously in response to their demands for further use. Design evaluator in relation with various data and knowledge models checks for design feature violations if any and corrects them by proposing design changes. Process planner in relation with various data and knowledge models generates the process plan.
Data and knowledge models consist of data and knowledge objects with intra-object and inter-object relations via design evaluator and process planner. An object incorporates both data and knowledge in the form of attributes and operations. Data and knowledge models used in automated manufacturability evaluation are feature data and knowledge model, material data model, resource/process data and knowledge model, and process plan data and knowledge model. Knowledge here is in the form of manufacturability evaluation guidelines expressed as rules and expressions and is used for design evaluation and process planning. Sheet metal manufacturability evaluation guidelines depending on their nature are divided into four major groups namely: part feature guidelines for design evaluation, process plan generation guidelines, part feature guidelines for process plan generation, and manufacturing resource/process selection guidelines. Knowledge forms a part of the operations of an object and forms the basis for relationships of objects.
The thesis presents results of automated manufacturability evaluation for many shee metal components including industrial components. Extension of this work to other sheet metal processes such as spinning and roll-forming is also presented at the end.
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Table of Contents
Abstract i
List of Figures ix
List of Tables xiii
1 Introduction 1
1.1 Research context and motivation 1
1.2 Research objectives 6
1.3 Research methodology and organization of the thesis 7
2 Literature Review 11
2.1 Introduction 11
2.2 Automated manufacturability evaluation 11
2.3 Data and knowledge modeling 20
2.3.1 International standards and related works 21
2.3.2 Data models / knowledge models 27
2.3.3 Data and knowledge models 34
2.4 Summary 39
3 Automated Manufacturability Evaluation Framework 41
3.1 Introduction 41
3.2 Automated manufacturability evaluation framework 41 3.3 Sheet metal manufacturability evaluation guidelines 44 3.4 Feature reasoning, design evaluation and process planning 46
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3.5 Data and knowledge modeling 50
3.6 Summary 55
4 Sheet Metal Manufacturability Evaluation Guidelines 57
4.1 Introduction 57
4.2 Sheet metal manufacturability evaluation guidelines 57 4.3 Part feature guidelines for design evaluation .. 59 43.1 Part feature guidelines for design evaluation - Hole 59 4.3.2 Part feature guidelines for design evaluation - Slot 61 4.3.3 Part feature guidelines for design evaluation - Notch 62 4.3.4 Part feature guidelines for design evaluation - Projection 62 4.3.5 Part feature guidelines for design evaluation - Relief cut-out 64 4.3.6 Part feature guidelines for design evaluation - Bend 64 4.4 Process plan generation guidelines 66 4.5 Part feature guidelines for process plan generation 66 4.5.1 Part feature guidelines for process plan generation - Hole 67 4.5.2 Part feature guidelines for process plan generation - Slot 68 4.5.3 Part feature guidelines for process plan generation - Notch 68 4.5.4 Part feature guidelines for process plan generation - Projection 68 4.5.5 Part feature guidelines for process plan generation - Relief cut-out..70 4.5.6 Part feature guidelines for process plan generation - Bend 70 4.6 Manufacturing resource/process selection guidelines 71
4.6.1 Die making times and costs 71
4.6.1.1 Die set purchase cost for individual dies 71
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4.6.1.2 Shearing-blanking die making time and cost 72 4.6.1.3 Shearing-piercing die making time and cost 73 4.6.1.4 Bending die making time and cost 74 4.6.1.5 Progressive die making cost and time 75
4.6.2 Die material cost 76
4.6.3 Part processing times and costs 76 4.6.3.1 Part processing time and cost on individual dies 77 4.6.3.2 Part processing time and cost on progressive die 78
4.6.4 Part material cost 79
4.7 Summary 79
5 Feature Reasoning, Design Evaluation and Process Planning 81
5.1 Introduction 81
5.2 Feature reasoning 81
5.3 Design evaluation 91
5.4 Process planning 99
5.5 Summary 107
6 Data and Knowledge Modeling 109
6.1 Introduction 109
6.2 Data and knowledge modeling . 109
6.3 Data and knowledge models in design evaluation 110 6.3.1 Feature data and knowledge model 111
6.3.2 Material data model 114
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6.4 Data and knowledge models in process planning ... 114 6.4.1 Feature data and knowledge model . 115 6.4.2 Resource/process data and knowledge model 116 6.4.3 Process plan data and knowledge model 119
6.4.4 Material data model 120
6.5 Summary 121
7 Automated Manufacturability Evaluation System Development 123
7.1 System development 123
7.2 Automated manufacturability evaluation results for part I 124 7.3 Automated manufacturability evaluation results for part II 128 7.4 Automated manufacturability evaluation results for part III 130 7.5 Automated manufacturability evaluation results for part IV 135 7.6 Automated manufacturability evaluation results for part V 138
7.7 Analysis of results 142
8 Conclusions 145
8.1 Summary 145
8.2 Contributions 148
8.3 Future work 149
References 151
Appendix A 165
A.1 STEP file for sheet metal component example 165
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Appendix B 171 B.1 Data and knowledge model object classes for example sheet metal component.171
Appendix C 177
C.1 A manufacturability advisor for spun and roll-formed sheet metal components.177
C.1.1 Results 179
C.1.1.1 Advisor output for example spun part 179 C.1.1.2 Advisor output for example roll-formed part 181
Publications Brief Bio-Data
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