IoT Applications in Asset Management: A Case Study on Efficiency Improvement

This thesis explores the integration of Internet of Things (IoT) technologies into industrial asset management through a detailed case study of mold‑fleet monitoring. Beginning with a systematic literature review, it synthesizes key theories and empirical findings on lifecycle costing, predictive maintenance and digital monitoring to establish a robust theoretical foundation. Building on this, the study examines how a manufacturing firm implements the IoT Matix Sensor solution—outlining its architecture, data‑acquisition methods and real‑time dashboard capabilities for capturing vibration, temperature and cycle‑time metrics at mold level—while addressing maintenance planning and performance calibration. The literature review also presents traditional methods for improving Overall Equipment Effectiveness (OEE)—focusing on availability and performance—and the case study then verifies how IoT sensors influence and enhance the specific activities used to boost these OEE dimensions. The findings demonstrate how targeted IoT deployments can enhance maintenance decision‑making, improve operational efficiency and reduce unplanned downtime. By combining theoretical review with empirical evidence, this work offers a structured framework for future smart‑manufacturing initiatives and contributes to advancing asset‑management strategies in practice.