Quantitative Analysis And Optimal Control Of Energy Efficiency In Discrete Manufacturing System

This book provides energy efficiency quantitative analysis and optimal methods for discrete manufacturing systems from the perspective of global optimization. In order to analyze and optimize energy efficiency for discrete manufacturing systems, it uses real-time access to energy consumption information and models of the energy consumption, and constructs an energy efficiency quantitative index system. Based on the rough set and analytic hierarchy process, it also proposes a principal component quantitative analysis and a combined energy efficiency quantitative analysis. In turn, the book addresses the design and development of quantitative analysis systems. To save energy consumption on the basis of energy efficiency analysis, it presents several optimal control strategies, including one for single-machine equipment, an integrated approach based on RWA-MOPSO, and one for production energy efficiency based on a teaching and learning optimal algorithm. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of discrete manufacturing systems.

This Special Issue addresses the important issue of the energy efficiency of both manufacturing processes and systems. Manufacturing is responsible for one-third of global energy consumption and CO2 emissions. Thus, improving the energy efficiency of production has been the focus of research in recent years. Energy efficiency has begun to be considered as one of the key decision-making attributes for manufacturing. This book includes recent studies on methods for the measurement of energy efficiency, tools and techniques for the analysis and development of improvements with regards to energy consumption, modeling and simulation of energy efficiency, and the integration of green and lean manufacturing. This book presents a breadth of relevant information, material, and knowledge to support research, policy-making, practices, and experience transferability to address the issues of energy efficiency.