Advertisement

Decision Support System for Rapid Production Order Planning in Production Network

  • Sebastian Saniuk
  • Anna Saniuk
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 637)

Abstract

Today the functioning of small and medium enterprises in production networks gives many opportunities for businesses, but also raises some concern and requires solutions to many problems. The process of forming the network of enterprises is dependent on the degree of preparation of these companies to share their resources, the possibility of estimating the related costs and the rapid planning jointly implemented projects. The aim of the article is to present a prototype decision support system for rapid production order planning in production network. The proposed tool can be helpful in the development of the concept of Industry 4.0. In particular, the article is presented the way the selection of partners to the network and load the productive resources to the needs of the timely implementation of the new order. The proposed approach and its computer implementation allow the permissible variations of network in condition of cost, resource and logistics system constraints to be determined.

Keywords

Production planning and scheduling Production network Rapid order planning 

References

  1. 1.
    Lenort, R., Staš, D., Samolejová, A.: Capacity planning in operations producing heavy plate cut shapes. Metalurgija 48(3), 209–211 (2009). ISSN 0543-5846Google Scholar
  2. 2.
    Ciupke, K.: Multivariate process capability index based on data depth concept. Qual. Reliab. Eng. Int. 32, 2443–2453 (2016). doi: 10.1002/qre.1947 CrossRefGoogle Scholar
  3. 3.
    Jasiulewicz-Kaczmarek, M.: Integrating lean and green paradigms in maintenance management. In: Boje, E., Xia, X. (eds.) Proceedings of the 19th IFAC World Congress Cape Town, South Africa, August 24–29, 2014, IFAC-Papers OnLine, vol. 47(3), pp. 4471–4476 (2014)Google Scholar
  4. 4.
    Kramarz, M.: Customer Service in a Selected Chain Link of a Supply Chain of the Motor Industry [in:] Scientific Papers Logistics and Transport No. 2(7)/2008. The International College of Logistics and Transport, Wrocław (2008)Google Scholar
  5. 5.
    Dekker, H.C., Goor, A.R.V.: Supply chain management and management accounting, a case study of activity based costing. Int. J. Logist. 3(1), 41–52 (2000)CrossRefGoogle Scholar
  6. 6.
    Camarinha-Matos, L. M.: Afsarmanesh, H., Ollus, M.: Methods and Tools for Collaborative Networked Organizations. Springer Science and Business Media, Berlin (2008)Google Scholar
  7. 7.
    Corvello, V., Migliarese, P.: Virtual forms for the organization of production: a comparative analysis. Int. J. Prod. Econ. 110, 5–15 (2007)CrossRefGoogle Scholar
  8. 8.
    Burduk, A.: The role of artificial neural network models in ensuring the stability of systems. In: 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing, vol. 368, pp. 427–437 (2015). doi: 10.1007/978-3-319-19719-7_37
  9. 9.
    Mazurkiewicz, D.: Maintenance of belt conveyors using an expert system based on fuzzy logic. Arch. Civil Mech. Eng. 15(2), 412–418 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.University of Zielona GoraZielona GóraPoland

Personalised recommendations