Modelling and Complexity Assessment of Assembly Supply Chain Systems

Vladimír Modrák · Dávid Márton

30 citations0/0 files storedProcedia Engineering

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Abstract

This paper focuses on the modeling of assembly supply chain (ASC) systems in order to establish a framework generating topological classes of ASCs. Subsequently, structural parameters of the networks levels are explored with the aim to generate all possible non–repeated ASC structures. In this paper, we also define several structural complexity metrics indicators, such as the index of vertex degree that is adopted from the Shannon«s entropy theory as well as other pertinent complexity indicators. After the application of these indicators to ASC structures, we benchmark complexity indicators based on predefined criteria. Research results are especially applicable at the early configuration design stage to make a decision about a suitable networked manufacturing structure that will satisfy the production functional requirements and will make managerial tasks simpler and more cost effective.

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References

1956An introduction to cybernetics 2008Product variety and manufacturing complexity in assembly systems and supply chains 1999Virtuous and vicious cycles on the road towards international supply chain management 2001Supply chain complexity and delivery performance: an international exploratory study 2004Advances on measuring the operational complexity of supplier–customer systems 1998Chaos Theory: Implications for Supply Chain Management 2005Development of an Approach for Analyzing Supply Chain Complexity

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2018An integrated interpretive structural modeling and a graph-theoretic approach for measuring the supply chain complexity in the Indian automotive industry 2018A graph theory-based algorithm for a multi-echelon multi-period responsive supply chain network design with lateral-transshipments 2021Mitigation of the ripple effect in supply chains: Balancing the aspects of robustness, complexity and efficiency 2021Supply Chain Management and Risk Management in an Environment of Stochastic Uncertainty (Retail)2015Modeling and measuring the structural complexity in assembly supply chain networks

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