Energy consumption is of great interest to manufacturing companies. Beyond considering individual processes and machines, the perspective on process chains and factories as a whole holds major potentials for energy efficiency improvements. To exploit these potentials, dynamic interactions of different processes as well as auxiliary equipment (e.g. compressed air generation) need to be taken into account. In addition, planning and controlling manufacturing systems require balancing technical, economic and environmental objectives. Therefore, an innovative and comprehensive methodology – with a generic energy flow-oriented manufacturing simulation environment as a core element – is developed and embedded into a step-by-step application cycle. The concept is applied in its entirety to a wide range of case studies such as aluminium die casting, weaving mills, and printed circuit board assembly in order to demonstrate the broad applicability and the benefits that can be achieved.

The Advanced Research Institute (A.R. 1.) on "the efficiency of Manufacturing Systems" was held under the auspices of the NATO Special Programm~ Panel on Systems Science as a part of the NATO Science Committee's continuous effort to promote the advancement of science through international co-operation. Advanced Research Institutes are organised for the purpose of bringing together experts in a particular field of interest to identify and make known the present state of knowledge in that area and, through informed debate, to make recommendations for directions for future research that would benefit the community at large. To this end two kinds of contribution were obtained by invitation. There were those papers which were about the current state of work in the area of manufacturing systems and its organisation; in addition three theme papers were presented to provide a stimulus to the discussion in terms of ways of thinking, both about the area and about the kind of research needed.

Over the last several years, manufacturers have expressed increasing interest in reducing their energy consumption and have begun to search for opportunities to reduce their energy usage. In this book, the authors explore a variety of opportunities to reduce the energy footprint of manufacturing. These opportunities cover the entire spatial scale of the manufacturing enterprise: from unit process-oriented approaches to enterprise-level strategies. Each chapter examines some aspect of this spatial scale, and discusses and describes the opportunities that exist at that level. Case studies demonstrate how the opportunity may be acted on with practical guidance on how to respond to these opportunities.

The past two decades have seen a great deal of research into the stochastic modelling of production, manufacturing, and inventory systems for the purpose of improving their performance. This book provides a graduate-level introduction to these techniques covering exact, approximate, and numerical techniques. The author has aimed to strike a balance between theoretical issues and the practical aspects of modelling manufacturing systems. It is based on graduate courses given to operations research and industrial engineering students and includes numerous examples and exercises.

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.

Optimization of Manufacturing Systems Using the Internet of Things extends the IoT (Internet of Things) into the manufacturing field to develop an IoMT (Internet of Manufacturing Things) architecture with real-time traceability, visibility, and interoperability in production planning, execution, and control. This book is essential reading for anyone interested in the optimization and control of an intelligent manufacturing system. As modern manufacturing shop-floors can create bottlenecks in the capturing and collection of real-time field information, and because paper-based manual systems are time-consuming and prone to errors, this book helps readers understand how to alleviate these issues, assisting them in their decision-making on shop-floors. Includes case studies in implementing IoTs for data acquisition, monitoring, and assembly in manufacturing. Helps manufacturers to tackle the growing complexities and uncertainties of manufacturing systems in globalized business environments Acts as an introduction to using IoT for readers across industrial and manufacturing engineering

The text is designed for engineering students at the senior undergraduate level and first-year students at graduate level, and professionals (R&D engineers in the industry and factory managers). The authors offer a unique effort in presenting a unified and systematic treatment of various modeling methodologies and analysis techniques for performance evaluation of automated manufacturing systems. The text begins with an overview of automated manufacturing systems, and then provides a clear and comprehensive discussion of three principal analytical modeling paradigms: Markov Chains, Queues and Queuing Networks, and Petri Nets. Salient Features • Present the first ever treatment of the mathematical modeling of manufacturing systems. • Offers a unified study of principal analytical modeling paradigms for automated manufacturing systems. • Discusses many recent research contributions in the area of modeling of automated manufacturing systems. • Discusses many recent research contributions in the area of modeling of automated manufacturing systems, including deadlock modeling, transient analysis, queuing network approximations, Petri Net modeling, and integrated analytical modeling. • Provides a large number of exercises and problems.