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Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators

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  • Vladimir Modrak
  • Zuzana Soltysova

Abstract

Manufacturing systems can be considered as a network of machines/workstations, where parts are produced in flow shop or job shop environment, respectively. Such network of machines/workstations can be depicted as a graph, with machines as nodes and material flow between the nodes as links. The aim of this paper is to use sequences of operations and machine network to measure static complexity of manufacturing processes. In this order existing approaches to measure the static complexity of manufacturing systems are analyzed and subsequently compared. For this purpose, analyzed competitive complexity indicators were tested on two different manufacturing layout examples. A subsequent analysis showed relevant potential of the proposed method.

Suggested Citation

  • Vladimir Modrak & Zuzana Soltysova, 2017. "Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators," Complexity, Hindawi, vol. 2017, pages 1-15, June.
    • Handle: RePEc:hin:complx:9102824
    DOI: 10.1155/2017/9102824
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    References listed on IDEAS

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    Cited by:

    1. Gerardo Beruvides & Fernando Castaño & Rodolfo E. Haber & Ramón Quiza & Alberto Villalonga, 2017. "Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization," Complexity, Hindawi, vol. 2017, pages 1-11, December.
    2. Marina Crnjac Žižić & Amanda Aljinović Meštrović & Marko Mladineo & Nikola Gjeldum, 2025. "Smart Sustainable Disassembly Systems for Circular Economy," Sustainability, MDPI, vol. 17(18), pages 1-18, September.
    3. Salvatore Cannella & Roberto Dominguez & Jose M. Framinan & Borja Ponte, 2018. "Evolving Trends in Supply Chain Management: Complexity, New Technologies, and Innovative Methodological Approaches," Complexity, Hindawi, vol. 2018, pages 1-3, June.

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