Assessing the cascading impact of industry 4.0 disruption on supply chain analytics through the lens of dependency concepts

Abstract

Nowadays, Industry 4.0 (I4.0) is regarded as one of the most sophisticated technologies that businesses need to have to stay competitive. I4.0 infrastructure system may be seen to function as a network of interdependent elements connected with multiple networks through various means. One such network is the supply chain which has an interrelation with Industry 4.0. Any disruption to Industry 4.0 will ripple through its entire supply chain and will lead to cascading effects. Thus, there is a need to examine how to minimize the disruption of I4.0 and make its dependent supply chain more functional and cost-saving. To that end, the aim of this research is threefold: (i) modeling the dependence between fourth industrial revolution and supply chain performance using the Bayesian network, (ii) capturing how a disruption in one network may propagate through the entire network and impact its overall robustness, (iii) conducting a series of advance analyses including belief propagation, sensitivity analysis, and information theory approach to validate the result and draw further insights. As a result of these analyses, it was found that technological factors and supplier quality are vital to the I4.0 disruption and performance of supply chain performance.