Tolerance Analysis of Mechanical Assemblies using Monte Carlo Simulation - A Case Study.- Operationalization & measurement of service quality in manufacturing supply chains: a conceptual framework.- A novel framework for evaluation of failure risk in thermal power industry.- Modeling and analysis of critical success factors for implementing the it based supply chain performance system.- Lean-sigma for product improvement using the voc for enhancing the product competitiveness.- Structural Equation Modeling application to assess environmental aspects in implementing Sustainable Manufacturing.- Service quality through the lens of sap-lap methodology: a case study.- Selection of the optimum hole quality conditions in manufacturing environment using mcdm approach: a case study.- Reliability analysis of cng dispensing unit by lambda-tau approach.- Assessment of health risks among tractor operators due to whole body vibration.- Modelling, simulation and optimization of product flow in a multi-product manufacturing unit: a case study.- Critical success factors (CSF's) of TQM and its effect on overall business performance.-Benchmarking the interactions among drivers in supply chain collaboration.- Significance of electronic waste management for sustainable industrial production.- An exploratory study into financial supply chain management.
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Dr. Anish Sachdeva is Professor in the Department of Industrial and Production Engineering at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar. He obtained his bachelors in Industrial Engineering from Regional Engineering College, Jalandhar in 1994; masters in Industrial Engineering from Punjab Technical University, Jalandhar in 2003; and his Ph.D from IIT Roorkee in 2008. He has published more than 100 research articles in international journals and conferences. His academic activities include serving as a peer reviewer in journals, acting as session chair in many international conferences, and conducting a number of training programs. His areas of interest include reliability and maintenance engineering, advanced machining, supply chain management, stochastic modeling, and system simulation. Dr. Pradeep Kumar is Professor in the Department of Mechanical & Industrial Engineering at Indian Institute of Technology, Roorkee. He obtained his bachelors (Industrial Engineering) in 1982; masters (Production Engineering) in 1989; and Ph.D. in Manufacturing and Production Engineering in 1994, all from the University of Roorkee. He has been a visiting faculty at West Virginia University, Wayne State University, AIT Bangkok, and King Fahd University of Petroleum and Minerals, Saudi Arabia. He served at the Delhi Technological University as Vice-Chancellor during 2014-15. He has published around 580 research papers in international and national journals, and conference proceedings. Dr. Kumar has completed 43 consultancy projects of various organizations, and 18 sponsored research projects in India and 1 sponsored project in USA. He also has 4 patent disclosures. His research interests include advanced manufacturing processes, microwave joining of metals, metal casting, industrial engineering, supply chain management, quality engineering, and production and operations management. Dr. Om Prakash Yadav is Professor and Interim Department Chair, Industrial and Manufacturing Engineering, North Dakota State University, Fargo. He obtained his bachelors in Mechanical Engineering from Malviya National Institute of Technology, Jaipur in 1986; masters in Industrial Engineering from National Institute of Industrial Engineering, Bombay in 1992; and Ph.D. in Industrial and Manufacturing Engineering from Wayne State University, Detroit in 2002. He has published more than 120 scientific papers in international journals and conferences, and edited more than 15 books and proceedings. He has successfully completed nearly 30 fully funded research and consultancy projects. His research interests include quality and reliability engineering, production and operations management, supply chain (logistics), inventory modeling, lean manufacturing, quantitative modeling, statistical analysis, fuzzy logic, and neural networks.
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