From Ontologies to Operative Data Models: A Data Model Development Supporting Zero Defect Manufacturing

Resource consumption is expected to reach 167 Gigatonnes by 2060 doubling the amount accounted in 2017. More than ever, manufacturing companies are asked to rapidly face this issue to limit their negative impacts on the entire society. Factories are supposed to act on their internal operating activities to enhance the quality of both products and processes reducing as much as possible the industrial waste generated. Among all, the zero-defect manufacturing principles represent an opportunity towards this direction, but companies necessitate to rely on their existing assets, both digital and physical, to create value based on that. Therefore, this contribution aims to develop an operating database based on a structured data model enabling to link, and reason over, three main areas (i.e. material, process, function) influencing the final product quality. These areas were identified in an already validated ontology, GRACE, considering them as the key elements to be kept under consideration to evaluate the impacts on product quality facilitating to make zero-defect oriented decisions. Indeed, the developed model, to be useable by a manufacturing company, was aimed to ensure to be data source independent, to embed these four areas, to include all the internal processes (i.e., pre-assembly, assembly) of a factory, and to transform abstracts ideas into operative actions. The data model development procedure is described, and its application was performed in a case study (i.e., an assembly line). This application enabled to validate it highlighting the key requirements for a discrete manufacturing company to embrace zero-defect manufacturing.