Model to assess the Economic Profitability of Predictive Maintenance Projects

Abstract

Due to recent developments in data-driven technologies, predictive maintenance has become a promising alternative, especially in comparison to traditional maintenance strategies such as corrective and preventive maintenance. Even though it is currently difficult to assess if the usage of forecasting technologies in the sector of maintenance is able reduce the total cost effectively, answering this question is needed before rolling out algorithms with the aim of adapting predictive maintenance solutions on a larger scale.This paper proposes a profit and cost model that intends to realize an easy application on various processes that involve the assessment of predictive maintenance solutions. The approach divides these solutions into five steps. For each step, technological options are discussed and their costs are quantified. The resulting model can assess the profitability of a single predictive maintenance approach, but can also be applied to evaluate and compare the profitability of different predictive maintenance projects. This approach has been evaluated at a real-world industrial automotive company, where it is currently used to determine future predictive maintenance strategies.