Pathway to Smart Maintenance: Integrating Engineering and Economics Modeling

This paper proposes a pathway for smart maintenance by addressing overarching questions and key impediments that arise when manufacturing companies are exploring investments in such projects. The proposed pathway consists of seven distinct steps at which analytical models are used to predict the impact of smart maintenance on system-level operational key performance indicators (KPIs) and the resulting return on investment (ROI). The key advantage of this approach is that the analytical models rely on a few parameters and, therefore, can be used even when there are no sophisticated data collection systems in place, such as in the case of many small and medium enterprises (SMEs). Furthermore, the proposed approach allows for the development of a “personalized” pathway along with the prediction of performance improvement and ROI impact, enabling management to make investment decisions with greater confidence. The proposed pathway also consists of a three-step detour for companies unprepared to embark on their journey towards smart maintenance. The application of the proposed smart maintenance pathway is illustrated through case studies consisting of three real SMEs. First, for companies that are unprepared for smart maintenance, we suggest traditional variance reduction methods and appropriate performance improvement goals along with predicted improvements in operational and financial KPIs. Next, for companies that are prepared to embark on smart maintenance, we provide a detailed evaluation of the impact of condition-based maintenance (CBM) by analyzing various machine combinations that maximize performance-to-cost ratio. In the case of one SME, our analysis shows that an improvement in throughput (0 to 3%) with an ROI (26:1) is achievable through the adoption of smart maintenance, which can be visualized using the DuPont Model.