A Multi-criteria Decision-Making Model for Digital Transformation in Manufacturing: A Case Study from Automotive Supplier Industry

Abstract

In digital transformation era, technology selection stands as a critical strategic technology management process for manufacturing companies in developing countries who struggle to adapt themselves to technological change despite their limited financial, technological and organizational resources and capabilities. In literature background, various scholars discussed that, regardless of scale, companies which had been able to apply lean production principles and techniques in their manufacturing processes, have the advantage of utilizing their process management (including measurement and control) systems as a leverage in effective needs and benefit analysis. However, determining both the various implications and costs together with the potential benefits of technology transfer requires a multidimensional analysis which includes technological, organizational, operational, economic, legal aspects in a common framework. Even if the company is competent in technology assessment, they may still face the challenge of combining multiple criteria that can enable contextual decision making for “appropriate” technology acquisition. In this framework, by utilizing a case study from a major automotive parts supplier company in Turkey, our study aims to explore the criteria and methods/techniques that can be used within a structured feasibility analysis (which may serve as a) decision making model for identifying appropriate technologies for effective digital transformation in accordance with the process improvement needs of manufacturing companies in developing country contexts. For this, after a detailed review of literature and similar practices in the selected industry, we defined the multiple dimensions of technology selection decision models. We also analysed current technology transfer needs of the selected company by process analysis techniques from lean production theory (Value Stream mapping, SPC) and also collected opinions of the practitioner experts. As the selected company is a supplier of a Japanese automotive manufacturer and has been applying lean production techniques for several decades, we could be able to use the information/data which the company provided. As well, to define the potential technologies that can respond to the defined needs, we applied technology auditing for available Industry 4.0 technologies with content analysis on literature and with interviews with the experts from the field. Together with the financial feasibility with NPV, ROI, Technology Acquisition Cost Analysis and Impact on labour productivity measures (where the horizon value is adapted for income/cost saving analysis), we designed a multi criteria decision making model which includes organizational, economic, technical and regulative factors and their sub-criteria, we proposed the feasibility analysis model. The proposed model is applied for the potential Industry 4.0 technologies which may respond to the process improvement needs of the studied company. To rank the feasibility results, we used TOPSIS multiple criteria decision-making method in the final phase.

Appendix 1

Total Scores of Technologies by Feasibility Sub-Factors