An Ontology Model to Facilitate the Semantic Interoperability in Assessing the Circular Economy Performance of the Automotive Industry

Abstract

Circular economy (CE) focuses on maintaining the value of goods and materials as long as possible, reducing waste and resource usage, and keeping resources within the economy when a product has reached the end of its life. Products and materials have to be utilized many times to produce additional value. In the automotive industry, CE involves processes throughout the value chain comprising multiple dimensions such as energy, materials, lifetime, and utilization. The CE performance of the automotive industry can be measured using key performance indicators (KPIs) from those dimensions. However, since multiple stakeholders are involved throughout the automotive product lifecycle and value chain, calculating KPIs requires data from heterogeneous sources. Thus, a non-uniform understanding of the KPIs among those stakeholders may arise due to a lack of explicit semantic description, including the related assessed CE scenarios, data providers, and data sources. Meanwhile, various sectors have used ontologies to facilitate a common understanding of information structure among systems and organizations. Our paper presents an ontology-based model that enables sharing a common understanding of KPIs used to assess CE performance in the automotive industry. We identify the indicators, the corresponding data requirements, and sources. In this paper, we present the ontology model describing the semantics of data required for the indicators. We also show the deployment model illustrating the implementation of the ontology model in the CE performance assessment phases.