I-PRAG-7: I-PRAG-7: Semantics for Production Feasibility
Experiment Description
During the last decade, new demands in the manufacturing domain are observable as consequences of new trends and capabilities, including Industry 4.0. Increasing demand for high customization of small batch production belongs to the most important and challenging demands.
However, the legacy approaches and available technologies do not provide appropriate means which can tackle the aforementioned demand. On the one hand side, there are operational issues, including compatibility of MES/ERP systems or logistics. On the other hand side, it is difficult to estimate which type and degree of customization are feasible with available input material, hardware, and technological processes during the planning phase. The situation is identical also with setting up of a new product.
Semantic technologies (namely ontologies together with automated reasoning) can cope with this challenge. The experiment exploits PPR ontology (see external reference) for a description of related processes, including production dependencies between operations as well as the specification of required manufacturing activities. Furthermore, PPR ontology describes relevant resources regarding the production, i.e., workstations, devices and their provided manufacturing activity, and the capabilities of the resources.
Based on the experiment, it is possible to demonstrate - verification of production feasibility with the help of automated reasoning (e.g., is a new product manufacturable with a given hardware configuration?); exploits outcomes and explicit conceptualization to find the optimal set of production steps in flexible manufacturing with the help of genetics algorithms based on given KPIs. And thus, it also provides inputs for high-level capacity planning.
The experiment exploits PPR ontology (see external reference) for a description of related processes, including production dependencies between operations as well as the specification of required manufacturing activities. Furthermore, PPR ontology describes relevant resources regarding the production, i.e., workstations, devices and their provided manufacturing activity and the capabilities of the resources.
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Impact
Better insight into relations among recipe, operations and required and/or available hardware bring clearer understanding of required shared conceptualization. This poses an important impact on precision and quality of experiment results and helps to verify production feasibility in more detail.