Cooperation platform for distributed manufacturing

• Autorzy: Pietroń Roman

Identyfikatory

DOI

10.7494/dmms.2020.14.2.3650

• Języki publikacji: EN

Abstrakty

EN

The aim of the paper is to analyse contemporary trends in distributed manufacturing (DM) research and to present a concept to develop and test some task allocation, planning and scheduling algorithms for DM network organisations. Some concepts to identify key factor criteria and reasoning policies and rules for production/manufacturing decision support system are also undertaken. And finally, an aim is to draw a proposal for a development of a prototype decision support system with necessary communication and knowledge oriented modules to be implemented in an example of dynamic, DM and logistics network structure, particularly for very popular dynamic cluster forms in Poland. The developed concept of the organization of a multi-entity DM network will enable business-effective use of the system, supporting manufacturing decision making, consulting and offering information services in the control centre (the so-called Competence Centre) by constructing virtual reality and access to services in a distributed network of cloud computing type. Integration of the whole system into one information system will enable analysis and network resource optimization of manufacturing and logistics processes, new analytical functions, reduction of delays in the manufacturing system, management of changes and risks, and visualization of the current state of the DM system.

Słowa kluczowe

EN

management; distributed manufacturing; resource allocation

PL

zarządzanie; produkcja rozproszona; alokacja zasobów

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2020
• Tom: Vol. 14, no. 2
• Strony: 145--163
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Pietroń Roman

• Wrocław University of Science and Technology, Department of Operations Research & BusinessIntelligence, Wrocław, Poland

• https://orcid.org/0000-0002-8191-8889

Bibliografia

• [1] Akoorie, M.E.M., Ding, Q., 2009. Global competitiveness in the Datang hosiery cluster, Zhejiang. Chinese Management Studies, 3(2), pp. 102–116.
• [2] Dietrich, F., Palm, D., Louw, L., 2020. Smart contract based framework to increase trans-parency of manufacturing networks. Procedia CIRP, 91, pp. 278–283.
• [3] Durão, L.F.C., Christ, A., Anderl, R., Schützer, K., Zancul, E., 2016. Distributed Manufacturing of Spare Parts based on Additive Manufacturing. Use Cases and Technical Aspects.Procedia CIRP, 57, pp. 704–709.
• [4] Gąbka, J., Susz, S., 2016. Concept of decision support system assisting dispersed manufacturingnetworks. IV International Scientific-Technical Conference MANUFACTURING 2014, Selected Conference Proceedings. Poznań University of Technology, pp. 114–123.
• [5] Kays, E., Karima, A., Varela, L., Putnik, G., Ávila, P., 2018. Ranked sequence positional weightheuristic for simultaneous balancing and scheduling jobs in a distributed manufacturing environment. Procedia CIRP, 67, pp. 3–7.
• [6] Liu, Y., Xu, X., Zhang, L., Wang, L., Zhong, R.Y., 2017. Workload-based multi-task schedulingin cloud manufacturing. Robotics and Computer-Integrated Manufacturing, 45, pp. 3–20.
• [7] Matt, D.T., Rauch, E., Dallasega, P., 2015. Trends towards Distributed Manufacturing Systems and modern forms for their design. Procedia CIRP, 33, pp. 185–190.
• [8] Milisavljevic-Syed, J., Allen, J.K., Commuri, S., Mistree, F., 2019. Design of networked manufacturing systems for Industry 4.0.Procedia CIRP, 81, pp. 1016–1021.
• [9] Moghaddam, M., Shimon, Y., Nof, S.Y., Menipaz, E., 2016. Design and administration ofcollaborative networked headquarters.International Journal of Production Research,54(23), pp. 7074–7090.
• [10] Rauch, E., Seidenstricker, S., Dallasega, P., Hämmerl, R., 2016. Collaborative Cloud Manufacturing: Design of Business Model Innovations Enabled by Cyberphysical Systems in Distributed Manufacturing Systems. Journal of Engineering, 3, pp. 1–12.
• [11] Rut, J., 2017a. Komputerowe systemy wspomagania decyzji w procesach produkcyjno-logistycznych przedsiębiorstw (cz. 1). Logistyka, 2, pp. 8–10.
• [12] Rut, J., 2017b. Komputerowe systemy wspomagania decyzji w procesach produkcyjno-logistycznych przedsiębiorstw (cz. 2). Logistyka, 3, pp. 2–9.
• [13] Seidenstricker, S., Rauch, E., Battistella, C., 2017. Business model engineering for distributed manufacturing systems.Procedia CIRP, 62, pp. 135–140.
• [14] Srai, J.S., Kumar, M., Graham, G., Phillips, W., Tooze, J., Ford, S., Beecher, P., Raj, B.,Gregory, M., Tiwari, M.K., Ravi, B., Neely, A., Shankar, R., Charnley, F., Tiwari, A.,2016. Distributed manufacturing: scope, challenges and opportunities. International Journal of Production Research, 54(23), pp. 6917–6935.
• [15] Szaller, Á., Egri, P., Kádár, B., 2020a. Trust-based resource sharing mechanism in distributed manufacturing. International Journal of Computer Integrated Manufacturing, 33(1), pp. 1–21.
• [16] Szaller, Á., Pedone, G., Egri, P., Szaloki, A., Nick, G., 2020b. A mutualistic framework forsustainable capacity sharing in manufacturing. Procedia CIRP, 93, pp. 938–943.
• [17] Woo, J., Kulvatunyou, B., Cho, H., 2008. Allocation of manufacturers through internet-based collaboration for distributed process planning. International Journal of Production Research, 46(7), pp. 1991–2007.
• [18] Zheng, T., Ardolino, M., Bacchetti, A., Perona, M., 2020. The application of Industry 4.0 technologies in manufacturing context: a systematic literature review. International Journal of Production Research, October 2020, https://doi.org/10.1080/00207543.2020.1824085.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)