The historical (and market) value of classic cars’ depends on their authenticity, which can be ruined by careless restoration processes. This paper reports on our ongoing research on monitoring the progress of such processes. We developed a process monitoring platform that combines data gathered from IoT sensors with input provided by a plant shop manager, using a process-aware GUI. The underlying process complies with the best practices expressed in FIVA’s Charter of Turin. Evidence (e.g., photos, documents, and short movies) can be attached to each task during process instantiation. Furthermore, car owners can remotely control cameras and car rotisserie to monitor critical steps of the restoration process. The benefits are manifold for all involved stakeholders. Restoration workshops increase their transparency and credibility while getting a better grasp on work assignments. Car owners can better assure the authenticity of their cars to third parties (potential buyers and certification bodies) while reducing their financial and scheduling overhead and carbon footprint.

This work was produced with the support of INCD funded by FCT and FEDER under the project 01/SAICT/2016 nº 022153, and partially supported by NOVA LINCS (FCT UIDB/04516/2020).

Classic car documentation,Auto repair shop software,Business process,BPMN,DMN,Internet of things,Industry 4.0,Process monitoring,GUI,Process awareness,Process mining

• Computer and Information Sciences - Natural Sciences