Manufacturing complexity and its measurement based on entropy models

Information-theoretic modeling of manufacturing organizations has led to the development of measures on the information of states of manufacturing systems. This paper provides an information-theoretic framework for the definition, measurement, and control of the states of manufacturing systems. Based on the information-theoretic entropy, the models of the static entropy and the dynamic entropy of manufacturing systems are developed, respectively. Scheduling is introduced to measure the manufacturing complexity and the feasible concepts of maximum schedule horizon and schedule adherence are advanced to quantitatively evaluate the effectiveness of schedules. Finally, an example is used to demonstrate the validity of the proposed methodology.