This paper mainly discussed the problem of a multiechelon and multiperiod joint policy of inventory and supply network. According to the random lead time and customers’ inventory demand, the s , S policy was improved. Based on the multiechelon supply network and the improved, the dynasty joint model was built. The supply scheme in every period with the objective of minimum total costs is obtained. Considering the complexity of the model, the improved particle swarm optimization algorithm combining the adaptive inertia weight and grading penalty function is adopted to calculate this model and optimize the spare part problems in various environments.

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In the modern industry, to reduce support pressure, a variety of suppliers have begun to use the same kind of units in many types of equipment. However, highly integrated equipment is more difficult to use in traditional reliability-centered maintenance (RCM) models, and researchers start steering based on the state monitoring method. This paper mainly discusses the remaining useful life (RUL) prediction method based on the Wiener process and introduces the improved condition-based maintenance policy. Combined with the (S-1, S) policy, the joint policy and the model considering the repairable policy are built for the multiunit system. Finally, the optional decision combination is obtained. Except that, the advantage of the joint optimization in a multiunit system and the characteristics of repairable policy in the joint model are analyzed.

In the modern industry, in order to reduce the inventory pressure, a variety of parts began to use unified kind spare parts for maintenance. However, highly integrated equipment is more difficult to use traditional RCM models, and researchers begin to steering based on state monitoring methods. Deepen a prediction of equipment failure. This paper mainly discussed the data-driven analysis method based on the Wiener process to predict the fault law of the same type. The joint model innovatively adopts the (s-1, s) policy considering the industrial characteristic and multi-period resupply. In the end, we analyze (s-1, s) policy in joint optimization by comparison to draw the optimal policy combination.