Manufacturing management of productivity in the steel industry using system dynamics modelling and statistical evaluation

Thinandahva Thomas Munyai, Michael Kweneojo O. Ayomoh, Olasumbo Ayodeji Makinde, A. Edgar Nesamvuni and Boitumelo I. Ramatsetse

International Journal of Industrial and Systems Engineering, 2023, vol. 43, issue 4, 491-528

Abstract: This paper has identified and analysed various drivers capable of influencing the level of productivity in steel manufacturing. The South African Steel Manufacturing Industries (SASMI) was used as a case study for this research. In order to achieve this, a comparative analysis of factors that could influence the productivity of SASMI was conducted using the exploratory factor analysis. Next was the creation of an integrated network of the systemic factors and lastly, the development of a system dynamics model for insight into the sensitivity of productivity dynamics per factor over a period of 30 months. Multiple regression analysis (MRA) was used to establish the relationship between productivity and its drivers. The results of the MRA, showed that competitiveness (in terms of production strategy, speed, cost, quality monitoring strategy and market share), facility layout and government support with weights of 0.319, 0.249 and 0.153, respectively, are critical to the productivity of SASMI.

Keywords: productivity; system dynamics; steel manufacturing; manufacturing management; multiple regression analysis; MRA. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:43:y:2023:i:4:p:491-528

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