Sustainable Transformation through Predictive Maintenance: A Qualitative Investigation into IoT-Driven Supply Chains

Abstract

This study elaborates on the IoT enabled predictive maintenance in supply chain sustainability with specific interest of how it affects operation efficiency, savings and environment. For the research eight in depth interviews with industry professionals were carried out who had taken part in the implementation and management of the predictive maintenance system in different sectors. According to the findings, the benefits of predictive maintenance as mentioned includes unplanned downtime and lack of resources; preventing unplanned emergency estate. Technology also extends equipment life, reduces energy consumption as well as reducing waste, which is environmentally sustainable. Although the study however revealed that there are associated challenges associated to the implementation of predictive maintenance, such as high initial investment costs, technical complexity and special skills, predictive maintenance is still a technology worth being considered attractive because of its born mentioned advantages. Additionally, leadership, training, and new ideas related to collaboration are key to an organization's successful execution of predictive maintenance systems. Overall, the study provides that predictive maintenance is neither as smooth nor hassle free, but for its long term efficiency, cost reduction and sustainability is an integral supply chain optimization strategy. As IoT tech advances, the potential for use as a predictive maintenance approach to develop both the innovation and environmental sustainability of the supply chain grows.

Keywords: Supply Chain Sustainability, Operational Efficiency, IoT, Predictive Maintenance, Cost Savings, Environmental Impact, Resource Optimization