In the 21st century, computer integrated manufacturing (CIM) systems will not only be the economic development tools but will also be the essential means of achieving a higher level of flexibility, cohesiveness and performance. CIM systems are beginning to settle into our society and industries, with greater emphasis on the integration of economic, cultural and social aspects together with design, planning, factory automation and artificial intelligent systems.This volume of proceedings brings together 10 keynote and invited speaker addresses, and over 180 papers by practitioners from 28 countries. It documents current research and in-depth studies on the fundamental aspects of advanced CIM systems and their practical applications. The papers fall into 3 main sections: CIM Related Issues; Industrial AI Applications Aspects; and Concurrent Engineering, Advanced Design, Simulation and Flexible Manufacturing Systems.

BACKGROUND There is an increasing awareness that 'time to market' is the key competitive issue in the manufacturing industry today. The global markets are demanding products that are well designed, are of high quality and are at low prices with ever decreasing lead times. Hence manufacturers are forced to utilize the best methods of technology with efficient control and management accompanied by suitably enabling organizational structures. Concurrent engineering (CE) is widely seen to be the methodology that can help satisfy these strenuous demands and keep the profitability and viability of product developers, manufacturers and suppliers high. There have been many reported successes of CE in practice. Rover were able to launch Land Rover Discovery in 18 months as compared with 48-63 months for similar products in Europe. Because of its early introduction to the market it became the best selling product in its class. AT&T report part counts down to one ninth of their previous levels and quality one hundred times (in surface defects) for VLSI (very improvements of large scale integration) circuits as a result of using the CE approach. WHO SHOULD READ THIS TEXT? This book will aim to provide a sound basis for the very diverse subject known as concurrent engineering. Concurrent engineering is recognized by an increasingly large proportion of the manufacturing industry as a necessity in order to compete in today's markets. This recognition has created the demand for information, awareness and training in good concurrent engineering practice.

Reactive scheduling is concerned with monitoring and controlling the execution of predictive schedules and making any changes required to bring them in line with unanticipated events or disturbances happening in real time. Whilst predictive scheduling has been a focus of research for many years, it is only recently that explicit attention has been given to the specific problems of reactive scheduling and the relationship between the two.This publication explores the scope and status of both existing and potential approaches to reactive scheduling. Concentration is centred on knowledge-based approaches as the importance of domain knowledge, whether stored in computers or in the brains of experienced schedulers, is becoming increasingly apparent. Contributions examine a variety of approaches ranging from reactive scheduling decision support frameworks in which the knowledge comes mainly from the human, through to completely new approaches to automated reactive scheduling such as neural networks.The book will be of particular interest to researchers, students and engineers involved in the manufacturing and software development industries. In addition to providing a significant reference volume, it also aims to stimulate increased discussion in this emerging field.

The concept of fuzziness, inspired by Zadeh (1965), brings us fruitful results when it is applied to problems in decision making. Recently, problems in fuzzy decision making are getting more complex, and one of the most complex fac tors is dynamics in systems. Dynamical approach to fuzzy decision making has been proposed by Bellman and Zadeh's celebrated paper "Decision-making in a fuzzy environment" (1970). The idea has developed into fuzzy mathemati cal programming and has been applied in many fields including management science, operations research, control theory, engineering, systems analysis, computer science, mathematical finance etc. Dynamic programming, advo cated in Bellmans book "Dynamic programming" (1957), is one of the most powerful tools to deal with dynamics in systems, and Bellman and Zadeh has proposed the optimality principle in fuzzy decision making by (1970) introducing fuzzy dynamic programming. Fuzzy dynamic programming and fuzzy mathematical programming has been making remakable progress after they were given life by Bellman and Zadeh's paper (1970). In this volume, various kinds of dynamics, not only time but also structure of systems, are considered. This volume contains ten reviewed papers, which deal with dynamics in theory and applications and whose topics are poten tially related to dynamics and are expected to develope dynamical study in near future. first, fuzzy dynamic programming is reviewed from a viewpoint of its origin and consider its developement in theory and applications.

In the competitive business arena companies must continually strive to create new and better products faster, more efficiently, and more cost effectively than their competitors to gain and keep the competitive advantage. Computer-aided design (CAD), computer-aided engineering (CAE), and computer-aided manufacturing (CAM) are now the industry standa