Development of operational complexity measure for selection of optimal layout design alternative

Abstract

Characterising existing approaches to operational complexity, it can be stated that for those metrics are characterful different factors used as variables such as product structure, machine composition, number of technological functions performed by machine, and others. Moreover, the complexity metrics using the information content as a basis can be divided into two groups: those which define complexity as an absolute entropy quantity, and metrics defining complexity as the relative entropy magnitude. Our view on the operational complexity is based on an assumption that process complexity value obtained as a sum of the partial complexities is not so important than a balanced operational complexity value expressing relative quantity to equilibrium levels. Accordingly, this paper introduces the novel operational complexity measure that initially identifies operational complexities of individual machines based on the number of parts, machines and operations. In the subsequent steps, these sub-measures are used to define summary complexity measure involving two balanced operational complexity characteristics. The novel measure can be effectively used to find the most suitable layout design alternative. For the purpose to prove its effectiveness, on two practical cases where tested its practicability by comparing it to the complexity indicator expressing the sum of the partial complexities.