An approach for the integration of intelligent maintenance systems and collaborative decentralized spare parts supply chains

Spare parts supply chains are particularly challenged by the low predictability of the demand, the need for high service levels and the cost of inventory. To address these challenges through a strategy of synchronizing supply chain participants, collaborative planning can be combined with intelligent maintenance systems that help predict failures. However, hierarchical models of integration have little acceptance from actors in the chain, who do not wish to share strategic data. Decentralized models promote the feasibility of collaborative planning but have not yet been applied in spare parts supply chains. In this context, in the present work, a bibliometric analysis with a bibliographic review on collaboration and supply chain planning is applied in order to verify the main concepts, directions and research opportunities. Research opportunities were identified in the application of decentralized models in real cases, and there was a general lack of information to support the choice of a solving method. Thus, the objective of this work is to propose a structured procedure to support the application of decentralized collaborative planning in supply chains of spare parts. For this, a table of characteristics is constructed to support the choice of the method for solving linear problems. A structured procedure is then developed and tested to tailor a decentralized collaborative planning concept to a spare parts supply chain integrated with intelligent maintenance systems. This developed structured procedure is applied in a test case and, as a result, an adequate model of collaborative operational planning is proposed for the improvement of this supply chain. Decentralized planning was identified as having achieved better results than a classical management approach even in scenarios of high demand variation, such as in spare parts supply chains.

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