Characteristics of part mix complexity measure for manufacturing systems

The authors provide a general framework for measuring planning and scheduling complexity associated with a group of parts to be manufactured simultaneously. An application of this research could be in generating part mixes with a wide range of part mix complexity for simulation models of manufacturing systems, so as to test the system performance under different levels of complexity. The authors identify special properties of the proposed information-theoretic entropy measure that can be used by system planners to select a set of parts or operations from given alternatives. They study the behavior of this complexity measure with respect to part similarity, and show synergistic effects of different variables on this measure