Optimization Methods in Engineering (eBook, PDF)

Select Proceedings of CPIE 2019
Redaktion: Tyagi, Mohit; Sharma, Vishal; Sachdeva, Anish

• Format: PDF

Produktbeschreibung

This book comprises peer-reviewed contributions from the International Conference on Production and Industrial Engineering (CPIE) 2019. This volume provides insights into the current scenario and advances in the domain of industrial and production engineering in the context of optimum value. Optimization and its applicability in various areas of production and industrial engineering like selection of designing parameters and machining parameters, decisions related to conditions of optimum process/operation parameters, behavior of response variables, facilities planning and management, transportation and supply chain management, quality engineering, reliability and maintenance, product design and development, human factors and ergonomics, service system and service management, waste management, sustainable manufacturing and operations, systems design, and performance measurement are discussed in the book. Given the range of topics covered, this book can be useful for students, researchers, and professionals interested in latest optimization techniques related to industrial and production engineering.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 619
• Erscheinungstermin: 5. Juni 2020
• Englisch
• ISBN-13: 9789811545504
• Artikelnr.: 59571672

Autorenporträt

Dr. Mohit Tyagi is currently an Assistant Professor in the department of  Industrial and Production Engineering at Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India. He obtained his B.Tech. (Mechanical Engineering) from UPTU Lucknow in 2008 and M.Tech. (Product Design and Development) with Gold Medal from MNNIT Allahabad in 2010. He did his Ph.D. from Indian Institute of Technology, Roorkee in 2015. His research interests include Industrial Engineering, Supply Chain Management, Corporate Social Responsibilities, System Optimization, Performance Measurement System, Data Science and Fuzzy Inference System. He has around 6 years of teaching and research experience. He has more than 55 publications in international and national journals.   Dr. Anish Sachdeva is currently an Associate Professor in the department of Industrial and Production Engineering at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India. He obtained his B.Tech. (Industrial Engineering) from Regional Engineering College, Jalandhar (now National Institute of Technology, Jalandhar)  in 1994, M.Tech.(Industrial Engineering) from Punjab Technical University, Jalandhar in 2003, and Ph.D. (department of Mechanical & Industrial Engineering), IIT Roorkee in 2008. He has published more than 100 research articles in international journals and conferences of high repute. He has guided 60 M.Tech. and 12 Ph.D. candidates. His academic life includes serving as a peer reviewer in journals, acting as session chair in international conferences and conducting training programs. His areas of interest include Reliability and Maintenance Engineering, Advanced Machining, Supply Chain Management, Stochastic Modeling, and System Simulation. Dr. Vishal S Sharma is a Professor in the department of Industrial and Production Engineering at Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India. Heobtained his Bachelor's degree (Production Engineering) from Shivaji University, Kolhapur, in 1992, Master's  degree in Mechanical (Production) Engineering from Punjab University, Chandigarh, in 1998, and his Ph.D. in Mechanical Engineering from Kurukshetra University in 2005. He also received a postdoctoral fellowship from ENSAM Cluny, France in 2010. He has three years of industrial exposure and 23 years of teaching experience at Dr. B R Ambedkar National Institute of Technology Jalandhar. He has published more than 70 scientific papers in international journals and conferences, and edited more than 10 books and proceedings. His current research interests include additive manufacturing and machining, condition monitoring and industrial IOT/Industry 4.0.

Inhaltsangabe

Evaluating Statistical Approaches for Tool Condition Monitoring in Drilling Applications.- Parametric Assessment of Temperature Monitoring Trends in Food Supply Chain Performance System.- An Efficient Algorithm for Solving Cell Formation Problem in Cellular Manufacturing.- Design of Optimal Noise Barrier for Metropolitan Cities using Artificial Neural Networks.- Predictive Analytics in Food Grain Logistics: Supervised Machine Learning Approach.- Tribological Analysis of Increasing Percentage of CrC Content in Composite Coating by Atmospheric Plasma Spray Technique.- Effect of cutting parameters on MRR and surface roughness in turning of AISI 1018 and AISI P20 using Taguchi method.- Optimization of Exit Diameter of Hole on Ti-6Al-4V Super Alloy Using Laser Drilling.- An Improved Artificial Neural Networking Architecture Approach for Prediction of Cutting Parameters in Turning of EN31 Steel.- Effect of Temperature on the Wear Behaviour of CrN Coating Deposited by Physical Vapour Deposition.

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