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A model of the assessment and optimisation of production process quality using the fuzzy sets and genetic algorithm approach

Author

Listed:
  • Snezana Nestic
  • Miladin Stefanovic
  • Aleksandar Djordjevic
  • Slavko Arsovski
  • Danijela Tadic

Abstract

In this paper, the production process is decomposed for typical manufacturing small and medium sized enterprises (SMEs) and the metrics of the defined sub processes, based on the requirements of ISO 9001:2008, are developed. The weight values of production process performance indicators are defined, using the experience of decision makers from the analysed manufacturing SMEs, and calculated using the fuzzy set approach. Finally, the developed solution, based on the genetic algorithm approach, is presented and tested on data from 112 Serbian manufacturing SMEs. The presented solution enables quality assessment of a production process, the ranking of indicators, optimisation and provides the basis for successful improvement of the production process quality. [Received 13 April 2013; Revised 7 October 2013; Accepted 5 November 2013]

Suggested Citation

  • Snezana Nestic & Miladin Stefanovic & Aleksandar Djordjevic & Slavko Arsovski & Danijela Tadic, 2015. "A model of the assessment and optimisation of production process quality using the fuzzy sets and genetic algorithm approach," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 9(1), pages 77-99.
    • Handle: RePEc:ids:eujine:v:9:y:2015:i:1:p:77-99
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    Cited by:

    1. Slavko Arsovski & Goran Putnik & Zora Arsovski & Danijela Tadic & Aleksandar Aleksic & Aleksandar Djordjevic & Slavisa Moljevic, 2015. "Modelling and Enhancement of Organizational Resilience Potential in Process Industry SMEs," Sustainability, MDPI, vol. 7(12), pages 1-15, December.
    2. Keeeun Lee & Inchae Park & Byungun Yoon, 2016. "An Approach for R&D Partner Selection in Alliances between Large Companies, and Small and Medium Enterprises (SMEs): Application of Bayesian Network and Patent Analysis," Sustainability, MDPI, vol. 8(2), pages 1-18, January.

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