AIM-TRUE: AI-driven automotive service market – towards more resource-efficient and sustainable vehicle maintenance

Europe’s automotive industry is increasingly facing the need for concrete solutions to the challenges related to resource-efficient and sustainable transport systems. With more data available, it has become apparent that artificial intelligence (AI) and machine learning (ML) methods can also help to reduce climate emissions and energy consumption through more efficient use of resources in vehicle aftermarket operations. Volvo Group is proud to deliver complete transport solutions to its customers, from personalised vehicles suited for any task at hand – be it hauling goods over thousands of kilometres or distributing them within a few city blocks – to services that keep the vehicles running efficiently throughout their lifetime. Doing it successfully and with sustainable resource utilisation requires new ML-based, flexible, and green services that reduce costs while increasing customer satisfaction and maintaining a competitive advantage. All these goals can only be achieved by anticipating where and when a part will be needed and delivering that part to the correct region before this need even arises, thus reducing costs and increasing service levels.

AIM-TRUE will leverage ML to better understand the factors affecting parts availability and enable individualised inventory control policies. The project’s primary goal is to improve heavy-duty aftermarket resource efficiency and sustainability by reducing three aspects: urgent transport orders, back-and-forth haulage, and part scrapping. The new generation of predictive logistics provides opportunities for better system understanding, large-scale optimisation, quality monitoring, and new data-driven innovative services, all of which are prerequisites for the efficient use of resources – while providing the right parts at the right place and time.