Chapter 17
Manufacturing Capability Knowledge Modeling for Intelligent Manufacturing Systems


The evolution of automated manufacturing systems from fixed automation to flexible and programmable automation is driven by the need for achieving higher degrees of flexibility and adaptability while meeting the productivity requirements. Although flexible manufacturing systems (FMS) and, more recently, reconfigurable manufacturing systems (RMS) [1] [2] successfully enabled flexible automation at the mechanical and mechatronics levels, they still suffer from rigidity at the informatics level [3] [4]. Heavy reliance on humans for off-line programming hampers the abilities of the advanced production systems to respond autonomously to changes in work orders and reconfigure appropriately based on the available manufacturing resources. Ideally, automated manufacturing systems should obtain the necessary cognitive capabilities such as learning, reasoning, and adapting to changes in order to minimize their dependencies, to the extent possible, on human agents for hardwiring the program of instructions [5] [6]. In particular, dynamic configuration of new manufacturing cells or retrofitting the existing ones in an autonomous fashion should be supported by the underlying computational models of next generation manufacturing systems.

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