Titlebook: Manufacturing Decision Support Systems; Hamid R. Parsaei (Professor of Industrial Engineer Book 1997 Chapman & Hall 1997 DOM.Simulation.da

CRAB

苍白

Clinch

使腐烂

Machine learning for process parameter selection in intelligent machining,ect process parameters have significant influence on the quality of the final product, few attempts have been made to incorporate the systematic selection of the process parameters of a metal-cutting operation in a facility-specific manner. It is believed that incorporating the determination of mach

主动脉

An interactive program for machine grouping and layout,set-up time reduction, improved machine utilization, an increase in production rate and employee morale, a decrease in labor costs and traffic congestion and better control of the manufacturing system. Cellular manufacturing (CM) involves grouping of machines based on the parts they manufacture. The

痴呆

Intelligent scheduling systems: an artificial-intelligence-based approach,ificial intelligence (AI) to developing systems that exhibit the attributes of AI. There are potentially numerous benefits that could be realized by incorporating the new trends evolving in AI to develop systems that could search for new heuristic sequencing/scheduling rules in complex manufacturing

Offstage

Optimizing assembly time for printed circuit board assembly,t of production. In recent years, . and . manufacturing (Desrochers, 1990; Jürgen, 1987) systems have received considerable attention from design engineers and other researchers, as they provide an alternative to a higher productivity, increased safety and quality of production. Robots have become a

conifer

GEON

发生

Computer-integrated manufacturing: a complex information system,omation technology makes it possible for manufacturers to have this essential capability. A conceptualized information system that integrates the programmable design of a product and its manufacture with both planning activities and the manufacturing process will be described in this chapter. The in