A Qualitative Study of IoT-Enabled Predictive Maintenance and Its Influence on Supply Chain Sustainability

This study explores the role of IoT-enabled predictive maintenance in enhancing supply chain sustainability, focusing on its impact on operational efficiency, cost savings, and environmental performance. The research was conducted through in-depth interviews with industry professionals involved in the implementation and management of predictive maintenance systems across various sectors. The findings highlight the significant benefits of predictive maintenance, including the reduction of unplanned downtime, improved resource optimization, and the prevention of costly emergency repairs. Additionally, the technology contributes to environmental sustainability by extending equipment lifespans, reducing energy consumption, and minimizing waste. Despite these advantages, the study identifies several challenges associated with the implementation of predictive maintenance, such as high initial investment costs, technical complexity, and the need for specialized skills. Furthermore, the research reveals that successful adoption of predictive maintenance systems requires strong leadership, employee training, and a culture of collaboration within organizations. The study concludes that while the implementation of predictive maintenance poses certain obstacles, the long-term benefits in terms of operational efficiency, cost reduction, and sustainability make it a crucial strategy for supply chain optimization. As IoT technologies continue to advance, the potential for predictive maintenance to drive innovation and environmental sustainability in supply chains will only increase.