Modelling And Intelligent Optimisation Of Production Scheduling In Vcim Systems

This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.

Two large international conferences on Advances in Engineering Sciences were held in Hong Kong, March 16–18, 2016, under the International MultiConference of Engineers and Computer Scientists (IMECS 2016), and in London, UK, 29 June – 1 July, 2016, under the World Congress on Engineering (WCE 2016) respectively. This volume contains 21 revised and extended research articles written by prominent researchers participating in the conferences. Topics covered include engineering mathematics, computer science, electrical engineering, manufacturing engineering, industrial engineering, and industrial applications. The book offers state-of-the-art advances in engineering sciences and also serves as an excellent reference work for researchers and graduate students working with/on engineering sciences.

This book investigates in detail production scheduling technology in different kinds of shop environment to achieve sustainability manufacturing. Studies on shop scheduling have attracted engineers and scientists from various disciplines, such as electrical, mechanical, automation, computer, and industrial engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of intelligent optimization and the significant influence of production scheduling in the manufacturing systems. The book is intended for undergraduate and graduate students who are interested in intelligent optimization technology, shop scheduling, and green manufacturing systems or other scheduling applications.

This is the first book to focus on emerging technologies for distributed intelligent decision-making in process planning and dynamic scheduling. It has two sections: a review of several key areas of research, and an in-depth treatment of particular techniques. Each chapter addresses a specific problem domain and offers practical solutions to solve it. The book provides a better understanding of the present state and future trends of research in this area.

Optimization techniques in production management are becoming increasingly important for efficient and competitive manufacturing. This book presents a collection of tutorial papers by outstanding researchers on the application of optimization concepts. Topics introduced include hierarchical production planning and large scale scheduling, optimal production control, exact and heuristic algorithms for production scheduling and stochastic modelling.

Advanced modeling techniques are a necessary tool in order to design and manage manufacturing systems effectively. This book contains a set of tutorial chapters on topics ranging from aggregate production planning to real time control, including predictive and reactive scheduling, flow management in assembly systems, simulation of robotic cells, design of manufacturing systems under uncertainty and a historical perspective on production management philosophies. The book will be of interest both to researchers and practitioners, including graduate students in Manufacturing Engineering and Operations Research.

World Class Applications shows what real organisations have done to implement Six Sigma, the methodology used, and the results delivered. The book provides details of how these organisations overcame issues with the statistical tools of Six Sigma and provides valuable lessons by explaining what went wrong when implementation failed. Cases cover topics including: Six Sigma in HR; Implementing Six Sigma in the Dow Chemical company; Six Sigma in IT; and Six Sigma to improve reporting quality.

The book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer vision, current issue in big data and cloud computing, computation linguistics, cyber-physical systems as well as topics in intelligent information management. Written by active researchers, the different chapters are based on contributions presented at the workshop in intelligent systems and computing (ISC), held during CSIT 2016, September 6-9, and jointly organized by the Lviv Polytechnic National University, Ukraine, the Kharkiv National University of Radio Electronics, Ukraine, and the Technical University of Lodz, Poland, under patronage of Ministry of Education and Science of Ukraine. All in all, the book provides academics and professionals with extensive information and a timely snapshot of the field of intelligent systems, and it is expected to foster new discussions and collaborations among different groups.