| Title | A conceptual data model promoting data-driven circular manufacturing |
|---|---|
| ID_Doc | 27888 |
| Authors | Acerbi, F; Sassanelli, C; Taisch, M |
| Title | A conceptual data model promoting data-driven circular manufacturing |
| Year | 2022 |
| Published | Operations Management Research, 15.0, 3-4 |
| Abstract | Circular economy (CE) paradigm fosters manufacturing companies' sustainability taking place through different circular manufacturing (CM) strategies. These strategies allow companies to be internally committed to embrace circular values and to be externally aligned with several stakeholders not necessarily belonging to the same supply chain. Nevertheless, these CM strategies adoption is limited by heterogeneous barriers, among which the management and sharing of data and information remain the most relevant ones, bounding the decision-making process of manufacturers in CM. Moreover, the extant literature unveiled the need to structure data and information in a reference model to make them usable by manufacturers. Therefore, the goal of the present work is to propose a reference model by developing a conceptual data model to standardise and structure the necessary data in CM to support manufacturers' decision-making process. Through this model, data and information to be gathered by manufacturers are elucidated, providing an overview of which ones should be managed internally, and shared externally, clarifying the presence of their mutual interdependencies. The model was conceptualised and developed relying on the extant literature and improved and validated through academic and industrial experts' interviews. |
| https://link.springer.com/content/pdf/10.1007/s12063-022-00271-x.pdf |
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