An effective supply chain management approach needs to be holistic and integrated, to avoid inefficiency between the echelons of the global chain. To achieve this goal, supply chain directors and decision makers are required to tradeoff a centralized planning approach for a decentralized one. This article develops a mixed approach where only the critical products are centrally planned, while leaving the noncritical ones to autonomous decisions at the local plants of a multiechelon supply chain. To validate the benefits of the proposed planning model, a complex supply chain in the automotive industry is used as testbed, where a comparison between top-down (from finished products to raw materials) and bottom-up (from raw materials to finished products) approaches is also introduced. analysis of variance test is performed on a full factorial design involving six criticality criteria and it suggests that the proposed selection model reduces the system size by 10%-30% with respect to a fully centralized approach, and the top-down procedure leads to a critical subsystem smaller in size by about 5%-10% in terms of number of products compared to the bottom-up one.

Improving supply chain in the automotive industry with the right bill of material configuration

Franceschetto, Simone;Amico, Clarissa;Brambilla, Mattia;Cigolini, Roberto
2023-01-01

Abstract

An effective supply chain management approach needs to be holistic and integrated, to avoid inefficiency between the echelons of the global chain. To achieve this goal, supply chain directors and decision makers are required to tradeoff a centralized planning approach for a decentralized one. This article develops a mixed approach where only the critical products are centrally planned, while leaving the noncritical ones to autonomous decisions at the local plants of a multiechelon supply chain. To validate the benefits of the proposed planning model, a complex supply chain in the automotive industry is used as testbed, where a comparison between top-down (from finished products to raw materials) and bottom-up (from raw materials to finished products) approaches is also introduced. analysis of variance test is performed on a full factorial design involving six criticality criteria and it suggests that the proposed selection model reduces the system size by 10%-30% with respect to a fully centralized approach, and the top-down procedure leads to a critical subsystem smaller in size by about 5%-10% in terms of number of products compared to the bottom-up one.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1231388
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