Enhancing the Optimization of the Selection of a Product Service System Scheme: A Digital Twin-Driven Framework

A product service system (PSS) has been developed for manufacturing enterprises to provide users with personalized products and services. The optimization of PSS scheme selection is a key stage in the PSS design phase. Given the dynamic characteristics of the multi-dimensional influencing factors and their coupling relationships, we propose a digital twin-driven framework to enhance the optimization of PSS scheme selection. The framework is divided into a digital twin layer, an information layer, and an approach layer. The logical relationship between the three layers is given, and a quantitative PSS scheme selection optimization mechanism is designed. Fuzzy numbers and rough boundary intervals are integrated for the attribute value determination of the PSS scheme. A modified TOPSIS developed by replacing Euclidean distance with relational vector distance is adopted for the PSS scheme assessment. A case of an air purification PSS scheme selection optimization under the proposed digital twin driven framework is studied. It is shown that the designed PSS scheme selection optimization mechanism is effective and can be enhanced with the presented framework.