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Function block-enabled operation planning and machine control in Cloud-DPP
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0002-3517-3636
Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi’an, People’s Republic of China.ORCID iD: 0000-0003-2165-775X
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-9694-0483
KTH, School of Industrial Engineering and Management (ITM), Production engineering.ORCID iD: 0000-0001-8679-8049
2023 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 61, no 4, p. 1168-1184Article in journal (Refereed) Published
Abstract [en]

Today, due to shop-floor uncertainties and widespread cross-enterprise collaborations, manufacturing systems of enterprises are increasingly demanded to be agile, adaptive, flexible and interoperable. Process planning systems are mission-critical constituent components of manufacturing systems in machining job shops of small and medium-sized enterprises in the machining and metal cutting sector. Cloud-based adaptive distributed process planning, which includes global supervisory planning in the cloud and local operation planning based on function block and cloud technologies, provides an effective approach for enhancing agility, adaptability, flexibility and interoperability of manufacturing systems. 

Place, publisher, year, edition, pages
Informa UK Limited , 2023. Vol. 61, no 4, p. 1168-1184
Keywords [en]
cloud manufacturing, Cloud-DPP, function block, machine control, Process planning, smart manufacturing, Interoperability, Metal cutting, Enterprise collaboration, Machine controls, Operation planning, Planning controls, Shopfloors, Uncertainty, Process control
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-321196DOI: 10.1080/00207543.2022.2028921ISI: 000753945800001Scopus ID: 2-s2.0-85125087057OAI: oai:DiVA.org:kth-321196DiVA, id: diva2:1710608
Note

QC 20251218

Available from: 2022-11-14 Created: 2022-11-14 Last updated: 2025-12-18Bibliographically approved

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Givehchi, MohammadWang, Xi VincentWang, Lihui

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