Abstrakti
To survive in dynamic markets and meet the changing requirements, manufacturing companies must rapidly design new production systems and reconfigure existing ones. The current designer-centric search of feasible resources from various catalogues is a time-consuming and laborious process, which limits the consideration of many different alternative resource solutions. This article presents the implementation of an automatic capability matchmaking approach and software, which searches through resource catalogues to find feasible resources and resource combinations for the processing requirements of the product. The approach is based on formal ontology-based descriptions of both products and resources and the semantic rules used to find the matches. The article focuses on these rules implemented with SPIN rule language. They relate to 1) inferring and asserting parameters of combined capabilities of combined resources and 2) comparison of the product characteristics against the capability parameters of the resource (combination). The presented case study proves that the matchmaking system can find feasible matches. However, a human designer must validate the result when making the final resource selection. The approach should speed up the system design and reconfiguration planning and allow more alternative solutions be considered, compared with traditional manual design approaches.
Alkuperäiskieli | Englanti |
---|---|
Sivut | 128-154 |
Sivumäärä | 27 |
Julkaisu | International Journal of Computer Integrated Manufacturing |
Vuosikerta | 36 |
Numero | 1 |
Varhainen verkossa julkaisun päivämäärä | 2022 |
DOI - pysyväislinkit | |
Tila | Julkaistu - 2023 |
OKM-julkaisutyyppi | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä |
Rahoitus
This research has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 680759 with project title ReCaM (Rapid Reconfiguration of Flexible Production Systems through Capability-based Adaptation, Autoconfiguration and Integrated Tools for Production Planning) and under grant agreement no. 952003 with project title AI REGIO (Regions and DIHs alliance for AI-driven digital transformation of European Manufacturing SMEs).
Julkaisufoorumi-taso
- Jufo-taso 2
!!ASJC Scopus subject areas
- Mechanical Engineering
- Computer Science Applications
- Industrial and Manufacturing Engineering