Application of DEMATEL method in the analysis of factors affecting flexible manufacturing in Iran's automobile industry (Study case: Saipa group companies)

Document Type : Research Article (Original Article)

Authors

1 Assistant Prof.of Management Department, Faculty of Econoics and Management, Urmia University

2 PhD in Public Administration, Lorestan University

Abstract

Automotive companies must consider strategic initiatives to compete and respond to dynamic customer demand. In this regard, flexible manufacturing is a strategy that is used in the productivity, quality of the final product and vulnerabilities caused by unexpected changes in the volume and mix of orders in the automotive industry. The current research aimed to identify and analyze the influenceability and Permeability factors affecting flexible manufacturing in Iran's automobile industry. This research is applied in terms of purpose and terms of research typology. It is among mixed research with qualitative and quantitative approaches. The statistical population of this research was the professors and experts of industrial management, business management and industrial engineering in the qualitative section, and according to the purpose of the research, sampling in this research was done in a targeted manner using the snowball technique and in the number of 26 people. The statistical population of this research was quantitatively senior and middle managers of Saipa group companies, who participated in this research using the convenience sampling method. In the qualitative part, the data obtained from the interviews using thematic analysis and MAXQDA2020 software led to the extraction of 11 factors affecting flexible manufacturing, and the analysis of the quantitative part was performed using the Dematel method. Based on Dematel analysis, the make-smart of lines, process re-engineering, and technological infrastructure significantly influence other factors. Professionalization of human capital, automation and technological platforms are also more permeability than other factors.

Keywords


Amiri, M., Sadaghiyani, J., Payani, N., & Shafieezadeh, M., Developing a DEMATEL method to prioritize distribution centers in supply chain. Management Science Letters, (2011) 1(3), 279-288.
 Boyer, K.. Longitudinal linkages between intended and realized operations strategies. International Journal of Operations & Production Management, (1998)18(4), 356-373.
Chae, S., Yan, T., & Yang, Y.. Supplier innovation value from a buyer–supplier structural equivalence view: Evidence from the PACE awards in the automotive industry. Journal of Operations Management, (2020) 66(7-8), 820-838.
Clarke, V. and Braun, V. Using Thematic Analysis in Psychology. Qualitative Research in Psychology, (2006),  3(2), pp. 123-140.
Cronin, C., Conway, A., & Walsh, J.. Flexible manufacturing systems using IIoT in the automotive sector. Procedia Manufacturing, (2019) 38, 1652-1659.
Delic, M., & Eyers, D. R.. The effect of additive manufacturing adoption on supply chain flexibility and performance: An empirical analysis from the automotive industry. International Journal of Production Economics, (2020) 228, 107689.
El-Khalil, R., & Darwish, Z.. Flexible manufacturing systems performance in US automotive manufacturing plants: a case study. Production planning & control, (2019) 30(1), 48-59.
Herrera-García, M. C., & Arias-Portela, C. Y.. Flexible Manufacturing Systems: A Methods Engineering and Operations Management Approach. In International Conference on Intelligent Human Systems Integration Springer, Cham (2021) (pp. 760-765)..
Komesker, S., Kern, W., Wagner, A., Bauernhansl, T., & Ruskowski, M.. Structured Information Processing as Enabler of Versatile, Flexible Manufacturing Concepts. In Advances in Automotive Production Technology–Theory and Application Springer Vieweg, Berlin, Heidelberg. (2021) (pp. 108-116).
Lin, k., and Lin, C.. Cognition Map of Experiential Marketing Strategy for Hot Spring Hotels in Taiwan Using the DEMATEL Method. Fourth International Conference on Natural Computation. IEEE. (2008)
Mendes, L., & Machado, J.. Employees’ skills, manufacturing flexibility and performance: a structural equation modelling applied to the automotive industry. International Journal of Production Research, (2015) 53(13), 4087-4101.
Mentes, A., Akyildiz, H., Yetkin, M., and Turkoglu, N.. An FSA based fuzzy DEMATEL approach for risk assessment of cargo ships at coasts and open seas of Turkey. Safety Science, (2015) 79, 1–10.
Mishra, R., Pundir, A. K., & Ganapathy, L.. Empirical assessment of factors influencing potential of manufacturing flexibility in organization. Business Process Management Journal. (2018)
Prakash, R., Singhal, S., & Agarwal, A.. Modelling manufacturing system effectiveness: an integration of analytical hierarchy process and linear programming. International Journal of Intelligent Enterprise, (2017) 4(3), 227-242.
Qamar, A., Hall, M. A., Chicksand, D., & Collinson, S.. Quality and flexibility performance trade-offs between lean and agile manufacturing firms in the automotive industry. Production Planning & Control, (2020) 31(9), 723-738.
Rybicka, J., Tiwari, A., & Enticott, S.. Testing a flexible manufacturing system facility production capacity through discrete event simulation: automotive case study. International Journal of Industrial and Manufacturing Engineering, (2016) 10(4), 719-723.
Sellitto, M. A., & Mancio, V. G.. Implementation of a Flexible Manufacturing System in a production cell of the automotive industry: decision and choice. Production, (2019) 29.
Solke, N. S., & Singh, T. P.. Analysis of relationship between manufacturing flexibility and lean manufacturing using structural equation modelling. Global Journal of Flexible Systems Management, (2018)19(2), 139-157.
Tsai, W. H. and Chou, W. C.. Selecting management systems for sustainable development in SMEs: A novel hybrid model based on DEMATEL, ANP, and ZOGP. Expert Systems with Applications, (2009) 36(2), 1444–1458.
Tzeng, G., and Huang, J.. Multiple Attribute Decision Making. Taylorand Francis. (2011)