Design of Experiment with ARAS in Technology Selection for Effective Cognitive Supply Chain Management

Abstract

The core principle of Industry 4.0 is the augmentation of artificial intelligence components with almost all the business activities. The manufacturers are preferring cognitive supply chain management (COGSCM) to conventional logistic practices for exercising effective planning and control. Automatic monitoring of production and inventory levels with less manual interference are the highlighting features of COGSCM. As the right choice of technology makes COGSCM more effective, this paper proposes a hybrid method of decision making to make optimal selection of the technology. The technique of Design of experiment (DOE) is combined with Additive Ratio Assessment (ARAS) to develop a new method. The competency and consistency of the model is tested with the secondary data sets and further analysed with other similar combined methods. It is observed that the proposed method is yielding better results in comparison to the existing methods of making decisions.