A digital twin for spare parts supply chain planning and control

Geopolitical crises, raw materials shortage, the COVID-19 outbreak, and social and economic disruptions have significantly and unpredictably affected the supply chains’ performance. Managing a wide variety of products, as well as the relationships with different suppliers and customers spread worldwide, have become more challenging, especially for companies operating with global and extremely complex supply chains. With its high service level requirements, the spare parts supply chain has been one of the most affected. This paper aims to introduce a digital twin system to support spare parts planning and control through a cost- and reliability-based model design. The proposed model minimizes the overall supply chain cost, including holding cost, power consumption for material handling, stock-out risk, and sale loss probability. This model aids decision-makers in managing spare parts inventory and controlling customers’ service level under uncertainty. The digital twin is applied to a case study of an Italian automatic packaging machine company to support decision-makers on spare parts decisions.