Analyzing the Decisions Involved in Building a Digital Twin for Predictive Maintenance

Abstract

Producing a digital twin (DT) involves many interlinking decisions. Existing research tends to describe the parts of a DT and how they work, but not the decision-making that went into building the DT nor the consideration of alternative design options. There is therefore a need for a decision-support tool to guide developers to create DTs efficiently while meeting functional requirements such as accuracy and interoperability. To work toward creating a DT decision-support tool, this paper presents an analysis of the decisions required to create a predictive maintenance DT for an automotive manufacturer. The decisions at each stage of the build process are identified and represented as inputs, outputs, controls and mechanisms. This allows for a conversion into generalized decisions presented in the form of an IDEF0 diagram. The research is a fundamental component in producing a decision-support tool for DT design and deployment.