Spare parts supply chains’ operational planning using technical condition information from intelligent maintenance systems

The use of technical condition information provided by intelligent maintenance systems improves the reliability of spare parts demand forecasts. This paper aims to propose and test a procedure to integrate demand forecasts derived from technical condition information into the operational planning of spare parts supply chains. The procedure employs mathematical programming and a simulation-based sensitivity analysis. Through the development of a proof-of-concept, it was possible to verify that the procedure allows for the minimization of total costs while ensuring service level regarding the delivery of the orders in a predefined time.