An integrated approach in modeling, optimization, and simulation of non-conventional manufacturing systems

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Today's production manager must deliver performance improvements at an increasing pace in order to meet the objectives of "better, faster, cheaper and cleaner." Globalization, increasingly diverse and sophisticated customer markets, the rapid pace of technological change, scarcity of natural resources, and stringent environmental controls have all contributed to a turbulent business environment. Today, if a manufacturer is satisfied with the status quo, it is flirting with extinction. Technology, in the form of equipment and information systems, has always been a route to higher efficiency and improvement. However, an equally important - and in some cases more important - avenue for competitiveness is the way we organize and manage production systems. There is an emerging consensus that existing layout configurations do not meet the needs of multi-product enterprises and there is a need for new generation of factory layout that are more flexible, modular, and easy to reconfigure. The proposed research will provide in-depth undersigning to rapid modeling and simulation of non-conventional manufacturing systems to answer questions related to: changes in product mix and volume; relocation, addition and deletion of machine tools; reconfiguration of material handling system; operator assignment, shift-scheduling and capacity adjustment; and product lot sizing and scheduling. Main contribution of the proposed research will be made in developing: (1) Models, algorithms and computerized tools to design and optimize non-conventional manufacturing systems such as cellular, fractal and reconfigurable manufacturing systems; (2) Manufacturing systems performance metrics tailored to the design criteria of these non-conventional manufacturing systems; (3) Methodologies for automatic synthesis and generation of supervisory control algorithm for reconfigurable manufacturing systems; (4) Simulation model generators to evaluate several reconfiguration decisions in reconfigurable manufacturing systems on a recurrent bases.