BUS606: Operations and Supply Chain Management

In the past decades, product and manufacturing process developments have faced rapidly changing market needs. This global trend has resulted in more complex products and manufacturing processes to produce them. As is well known, assembly processes play a key role in production systems. Therefore, any effort for the improvement and optimization of the assembly process is vital to manufacturing competitiveness, since about 50% of the product cost should be ascribed to the assembly phase. One possible way to improve manufacturing competitiveness is to reduce assembly process complexity and the associated cost. Even though the system complexity is inherent and cannot be avoided, it has to be kept affordable. Before defining system complexity for specific purposes, it is important to present some background on complexity as such. According to Flood and Carson, "complexity does not solely exist in things, to be observed from their surface and beneath their surface". Flood adds that if systems are tangible things, then complexity and system are synonymous, where system is prime. According to Faulconbridge and Ryan, "a system necessarily has a boundary through which it or its elements interact with elements or systems outside the boundary". This system-inherent property allows us to adopt graph complexity measures for the complexity quantification of engineered systems. Reynolds points out that the structural modeling approach is applicable for clearly structured systems, in contrast to the behavioral approach, where structure is not assumed a priori. In the context of the architectural design, system complexity is proportional to the risk that the functional requirements cannot be met. In order to briefly introduce a structural complexity measurement problem, it would be useful to mention the fact that prevalent approaches toward measuring system complexity are based on entropy theory. Entropy can be interpreted in different ways, but in terms of technical systems, it is construed as a measure of information. This entropy measure was introduced by Shannon and Weaver, who reduced the concept of entropy to pure probability theory. Their considerations were adopted by Frizelle and Woodcock in order to define static and dynamic system complexity. In regard to the scope of this paper, our primary concern is static system complexity, defined as the amount of information needed to specify the system and its components. System complexity belongs to general systems theory, because it has been applied to different kinds of systems, including technical, social, and biological networks.

The purpose of this paper is to analyze existing complexity assessment methods to measure assembly supply chain (ASC) complexity and propose accurate complexity metric(s) that will include not only specific criteria for static complexity measures, but also sustainability viewpoints.