Implementation of Predictive Maintenance Strategies in Medical Equipment Manufacturing and Supply Chains to Enhance Health Safety - Ade Suhara; Muhamad Sayuti; Fathan Mubina Dewadi; Aaron Edogbo Aye (YCMM, 2024)
This research explores the application of predictive maintenance (PdM) to medical equipment and its supply chain to improve healthcare safety. PdM, which utilizes IoT technology, artificial intelligence (AI), and data analytics, enables real-time monitoring of equipment conditions and detection of malfunctions before operational failures occur. Although PdM offers many advantages, such as reduced cost of care and improved patient safety, challenges such as initial costs, interoperability issues, and cybersecurity need to be addressed. This research identifies solutions that can mitigate such barriers and assesses the impact of PdM on operational efficiency and reliability of medical equipment. The results show that PdM can improve medical equipment performance and support more efficient supply chain management.