Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection A Dissertation Submitted in Fulfillment of the Requirement for the Award of the Degree of DOCTOR OF PHILOSOPHY (Ph. D.) IN MECHANICAL ENGINEERING BY ANOOP KUMAR SAHU ROLL NO. 512ME105 NATIONAL INSTITUTE OF TECHNOLOGY ROURKELA-769008, ODISHA, INDIA NATIONAL INSTITUTE OF TECHNOLOGY ROURKELA-769008, ODISHA, INDIA Certificate of Approval Certified that the dissertation entitled SUPPLY CHAIN PERFORMANCE APPRAISEMENT AND BENCHMARKING FOR MANUFACTURING INDUSTRIES: EMPHASIS ON TRADITIONAL, GREEN, FLEXIBLE AND RESILIENT SUPPLY CHAIN ALONG WITH SUPPLIER SELECTION submitted by Anoop Kumar Sahu has been carried out under my supervision in fulfillment of the requirement for the award of the degree of Doctor of Philosophy in Mechanical Engineering at National Institute of Technology, Rourkela, and this work has not been submitted to any university/institute before for any academic degree/diploma. _____________________________ Dr. Saurav Datta (Principal Supervisor) Assistant Professor Department of Mechanical Engineering National Institute of Technology, Rourkela-769008, Odisha, INDIA Email: [email protected]/ Ph. No. +91 661 246 2524 (Office) ii Acknowledgement My dissertation entitled Supply Chain Performance Evaluation for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection brought to be a huge successful confine on account of valuable endeavors, selfless dedication, immense contribution, moral support, guidance and advice rendered by a number of individuals. Therefore, I wish to express my hearty appreciation to those due to which, I could carry out my dissertation work towards an effective end. First and foremost, I express my sincere gratitude to my supervisor Dr. Saurav Datta, Assistant Professor, Department of Mechanical Engineering, National Institute of Technology, Rourkela, for providing me valuable insights, guiding consciously, as well as sharing unimplemented innovative ideas in regards of my research work. I must appreciate all his contributions to make my Ph. D. research tenure productive and highly stimulating. I feel grateful to him for continuously delivering me moral support and endless motivation as well as providing mathematical, scientific and engineering fundamentals necessary to formulate, solve and analyze my research topic. I express my sincere gratitude to Prof. Dayal Ramakrushna Parhi, Professor, Department of Mechanical Engineering, who acted as the Chairman of my Doctoral Scrutiny Committee (DSC). I express special thanks to other DSC Members: Prof Saroj Kumar Patel, Associate Professor, Department of Mechanical Engineering, Dr. Mohammed Rajik Khan, Assistant Professor, Department of Industrial Design, Prof. Bipin Bihari Verma, Professor, Department of Metallurgical and Materials Engineering of our institute for their valuable advice at every stage of my work. I convey my sincere thanks to Prof. Siba Sankar Mahapatra, HOD, Department of Mechanical Engineering, National Institute of Technology, Rourkela, for providing me all academic as well as administrative supports throughout the period of my stay at National Institute of Technology, Rourkela. I also express my sincere gratitude to Prof. Sunil Kumar Sarangi, our Honourable Director; Prof. Banshidhar Majhi, Dean (Academic Affairs) for their kind support and concern about solicits to carry out my research work. I gratefully acknowledge the MHRD, Govt. of India for providing me fellowship to successfully carry out my research work. I must acknowledge Mr. Prasant Kumar Pal, Technician (SG1), CAD & CAM Laboratory of our department for providing kind attention toward availing necessary facilities of the department on time. I voluntarily extend my sincere appreciation to Mr/Ms. Nitin Kumar Sahu, Dilip Kumar Sen, Chhabi Ram Matawale, Chitrasen Samantra, Amit Kumar Mehar, Chinmaya iii Prasad Mohanty, Kumar Abhishek, Sanjita Jaipuria, Swayam Bikash Mishra, Swagatika Mishra, Shruti Nigam, Rahul Choudhary, Suman Chatterjee, Rameez Malik, Rajeev Kumar Yadav, scholars and my volunteer wishers associated with our laboratory who provided me valuable suggestions and precious time in accomplishing my entire project work. Last but not the least, I would like to thank the ALMIGHTY and my parents for their moral support and my friends with whom I used to share my day-to-day experience and receive lot of suggestions that improved the quality level of my work. ANOOP KUMAR SAHU iv Abstract Supply chain represents a network of interconnected activities starting from raw material extraction to delivery of the finished product to the end-user. The main constituents of supply chain are supplying/purchasing, inbound logistics, manufacturing, outbound logistics, marketing and sales. In recent times, the traditional supply chain construct is being modified to embrace various challenges of present business needs. Today’s global market has become highly volatile; customers’ expectations are ever-changing. Fierce competition amongst business sectors necessitates adapting modern supply chain management philosophies. Agility, greenness, flexibility as well as resilience have become the key success factors in satisfying global business needs. In order to remain competitive in the turbulent marketplace, industries should focus on improving overall performance of the supply chain network. In this dissertation, supply chain performance assessment has been considered as a decision making problem involving various measures and metrics (performance indicators). Since most of the performance indices are subjective in nature; decision- making relies on active participation of a group of decision-makers (DMs). Subjective human judgment often bears some sort of ambiguity as well as vagueness in the decision making; to overcome uncertainty in decision making, adaptation of grey/fuzzy set theory seems to be fruitful. To this end, present work deals with a variety of decision support tools to facilitate supply chain performance appraisement as well as benchmarking in fuzzy/grey context. Starting from the traditional supply chain, this work extends appraisement and benchmarking of green supply chain performance for a set of candidate case companies (under the same industry) operating under similar supply chain construct. Exploration of grey-MOORA, fuzzy-MOORA, IVFN-TOPSIS, fuzzy-grey relation method has been illustrated in this part of work. Apart from aforementioned empirical studies, two real case studies have been reported in order to estimate a quantitative performance metric reflecting the extent of supply chain flexibility and resilience, respectively, in relation to the case company under consideration. Performance benchmarking helps in identifying best practices in perspectives of supply chain networking; it can easily be transmitted to other industries. Organizations can follow their peers in order to improve overall performance of the supply chain. v Supplier selection is considered as an important aspect in supply chain management. Effective supplier selection must be a key strategic consideration towards improving supply chain performance. However, the task of supplier selection seems difficult due to subjectivity of supplier performance indices. Apart from considering traditional supplier selection criteria (cost, quality and service); global business scenario encourages emphasizing various issues like environmental performance (green concerns), resiliency etc. into evaluation and selection of an appropriate supplier. In this context, the present work also attempts to explore fuzzy based decision support systems towards evaluation and selection of potential suppliers in green supply chain as well as resilient supply chain, respectively. Fuzzy based Multi-Level Multi-Criteria Decision Making (MLMCDM) approach, fuzzy-TOPSIS and fuzzy-VIKOR have been utilized to facilitate the said decision making. vi Contents Items Page Number Title Sheet i Certificate of Approval ii Acknowledgement iii-iv Abstract v-vi Contents vii-x List of Tables xi-xiv List of Figures xv CHAPTER 1 01-31 Background and Rationale 1.1 Introduction 02 1.2 State of Art 06 1.3 Motivation and Objectives 27 1.4 Organization of the Present Dissertation 29 CHAPTER 2 32-118 Supply Chain Performance Appraisement and Benchmarking: Emphasis on Traditional Supply Chain 2.1 Supply Chain Performance Benchmarking: Exploration of Grey-MOORA 33 2.1.1 Coverage 33 2.1.2 Problem Definition: Application Potential of MCDM Techniques 33 2.1.3 Theory of Grey Numbers: Mathematical Basis 37 2.1.4 The MOORA Method 39 2.1.4.1 The Ratio System Approach of the MOORA Method 39 2.1.4.2 The Reference Point Approach of the MOORA Method 40 2.1.4.3 The Importance Given to Objectives 41 2.1.5 The Grey-MOORA 42 2.1.6 Case Empirical Research 48 2.1.7 Managerial Implications 51 2.1.8 Concluding Remarks 52 2.2 Supply Chain Performance Appraisement and Benchmarking: 71 Exploration of Fuzzy-MOORA 2.2.1 Coverage 71 2.2.2 Problem Definition 71 2.2.3 Fuzzy Preliminaries 72 2.2.3.1 The Generalized Trapezoidal Fuzzy Numbers 73 2.2.3.2 The Generalized Interval-Valued Trapezoidal Fuzzy Numbers 75 2.2.3.3 The Generalized Interval-Valued Trapezoidal Fuzzy Numbers Ordered Weighted 80 Geometric Average Operator vii 2.2.4 The Crisp MULTIMOORA method 81 2.2.5 MULTIMOORA Method Based Upon Interval-Valued Trapezoidal Fuzzy Numbers 83 2.2.6 Case Empirical Research 85 2.2.7 Managerial Implications 89 2.2.8 Concluding Remarks 90 CHAPTER 3 119-186 Performance Benchmarking of Green Supply Chain 3.1 Green Supply Chain (GSC) Performance Benchmarking using 120 Integrated IVFN-TOPSIS Methodology 3.1.1 Coverage 120 3.1.2 Problem Formulation 120 3.1.3 TOPSIS 121 3.1.4 Fuzzy Set Theory 123 3.1.5 Interval-Valued Fuzzy Modified TOPSIS Method 125 3.1.6 Empirical Research: Data Analyses 131 3.1.7 Managerial Implication 135 3.1.8 Concluding Remarks 136 3.2 Green Supply Chain Performance Appraisement and Benchmarking using 153 Fuzzy Grey Relation Method 3.2.1 Coverage 153 3.2.2 Problem Definition 153 3.2.3 Fuzzy Grey Relation Method 155 3.2.3.1 Triangular Fuzzy Numbers 155 3.2.3.2 Ranking of Triangular Fuzzy Numbers 157 3.2.3.3 Procedural Steps of Fuzzy Grey Relation Method 158 3.2.4 Empirical Illustration 161 3.2.5 Managerial Implications 164 3.2.6 Concluding Remarks 165 CHAPTER 4 187-216 Green Supplier Selection 4.1 Coverage 188 4.2 Problem Definition 188 4.3 Fuzzy Set Theory 189 4.3.1 Fuzzy Sets 189 4.3.2 Fuzzy Numbers 190 4.3.3 Linguistic Values 190 4.3.4 Defuzzifying triangular fuzzy numbers with COA 191 4.4 FMLMCDM Approach: Model Development 192 4.4.1 Notations 192 4.4.2 The MLMCDM Model 193 4.5 Fuzzy-TOPSIS 197 viii 4.6 Case Empirical Research 199 4.6.1 Case Illustration: Exploration of FMLMCDM Approach 200 4.6.2 Case Illustration: Exploration of Fuzzy-TOPSIS 201 4.7 Managerial Implications 202 4.8 Concluding Remarks 203 CHAPTER 5 217-237 Performance Evaluation of Flexible Supply Chain 5.1 Coverage 218 5.2 Supply Chain Flexibility Dimensions 218 5.2.1 Supply Network Flexibility 218 5.2.2 Operations Systems Flexibility 219 5.2.3. Logistics Processes Flexibility 219 5.2.4 Information Systems Flexibility 220 5.2.5 Organizational Design Flexibility 220 5.3 Problem Definition 221 5.4 Fuzzy Approach 222 5.4.1 The Theory of Generalized Trapezoidal Fuzzy Numbers 223 5.4.2 Ranking of Fuzzy Numbers: ‘Incentre of Centroid’ Method 224 5.5 Procedural Hierarchy: Case Application 227 5.6 Managerial Implications 229 5.7 Concluding Remarks 230 CHAPTER 6 238-268 Performance Evaluation of Resilient Supply Chain 6.1 Coverage 239 6.2 Problem Definition 239 6.3 Justification on Exploration of Fuzzy Set Theory 240 6.4 Fuzzy Numbers: Operational Rules 241 6.5 Ranking of Generalized Trapezoidal Fuzzy Numbers: The Revised Ranking Method 243 6.6 Proposed Fuzzy Based Resilience Appraisement Module: Case Research 246 6.7 Managerial Implications 251 6.8 Concluding Remarks 251 CHAPTER 7 269-293 Resilient Supplier Selection 7.1 Coverage 270 7.2 Problem Definition 270 7.3 Methodology 271 7.3.1 VIKOR Method 271 7.3.2 Fuzzy-VIKOR 272 7.4 Proposed Decision Support Framework 276 7.5 Case Empirical Research 277 7.6 Managerial Implication 280 ix 7.7 Concluding Remarks 281 CHAPTER 8 294-301 Summary and Contributions: Scope for Future Work References 302-340 List of Publications 341-342 Glossary 343-344 Resume of ANOOP KUMAR SAHU 345 x