Configuration complexity assessment of convergent supply chain systems

Abstract

System designers usually generate alternative configurations of supply chains (SCs) by varying especially fixed assets to satisfy a desired production scope and rate. Such alternatives often vary in associated costs and other facets including degrees of complexity. Hence, a measure of configuration complexity can be a tool for comparison and decisionmaking. This paper presents three approaches to assessment of configuration complexity and their applications to designing convergent SC systems. Presented approaches are conceptually distinct ways of measuring structural complexity parameters based on different preconditions and circumstances of assembly systems which are typical representatives of convergent SCs. There are applied two similar approaches based on different preconditions that are related to demand shares. Third approach does not consider any special condition relating to character of final product demand. Subsequently, we propose a framework for modeling of assembly SC models, which are dividing to classes.

Identifying Optimal Granularity Level of Modular Assembly Supply Chains Based on Complexity-Modularity Trade-Off

“…Firstly, the coding algorithm used to generate the feasible design space could be ineffective for network designs with a large number of suppliers. This is because the number of combinations of a supply network exponentially increases with the quantity of suppliers [23], [31]. Sophisticated clustering algorithms and meta-heuristics optimisation methods can be employed to offset the increased computational load within an acceptable time-frame.…”

“…Similarly, Wang et al [20] examined the impact of OCC on overall system throughput and found that variety-induced complexity can hinder the human cognitive efficiency and human reaction times in assembly operations, and hence affects the rework/scrap rate of assembly stations and disturbs assembly line throughput. Information entropy was also used alongside graph theory-based metrics (e.g., vertex degree) to quantify complexity in assembly supply chain networks [3], [21]- [23]. A summary of the literature review on supply chain complexity assessment is given in Table 1.…”

“…Based on the literature review of complexity management in assembly supply chains, little attention has been given to the question of supply chain network design from a viewpoint aiming to find a balance between network modularity and supply chain complexity. Only a few studies investigated the implications of network configurations over complexity in modular ASCs [2], [3], [20], [21], [23]. However, these studies mostly depend on pen-and-paper based solutions and did not emphasise the modularity-complexity trade-off within a broader context of the network design optimisation problem.…”

An integrated interpretive structural modeling and a graph-theoretic approach for measuring the supply chain complexity in the Indian automotive industry

“…Pathak et al (2007) and Hearnshaw and Wilson (2013) highlighted that SCC and adaptation phenomena can be better managed through complex adaptive system (CAS) principles. For measuring the structural complexity of the supply chain, Modrak and Marton (2013, 2014) proposed a vertex degree index ( I vd ) adapted from Shannon’s theory of entropy. Elmaraghy et al (2014) proposed a layout complexity assessment index for measuring the structural complexity of manufacturing layout.…”

Development of the Modularity Measure for Assembly Process Structures

“…Subsequently, product design parameters are transformed into the production work order document determining the sequence of operations. An important feature of the system modularity is that complexity of technical systems can be effectively managed through their modular design [9][10][11][12]. Tate [13] categorized modularity from the Axiomatic Design theory perspective into three types: resource, operational, and interfacial.…”