Proposed Application of an IoT-based Predictive Maintenance to Improve O&M of University Project by FM Company: A Six Sigma Approach

Abstract

An IoT-based Predictive Maintenance helps to monitor an asset s health in real-time, alerts generation, predictive analytics, and gain data-driven decision-making based on failure probability. 2019 records showed that December KPI only reached 79:21 indicating non-compliance of 80:20 KPI Ratio due to 71% asset-related RM. The purpose of this study is to eliminate 71% of assets’ failure and to evaluate the potential application of IoT-based PdM at University O&M Project by FM Company using the Six Sigma Approach. Results show that RCM can be achieved, elimination of more costly unscheduled maintenance by 40%-70%, a decrease of labor cost by 10% to 25%, incorporation of root-cause analysis, RM reduction of emergencies by 0.57%, urgent tasks by 10.36%, and normal tasks by 60.52%, KPI transformation from 80:20 PM: RM Ratio to 55:35:10 PdM:PM: RM Ratio, maintenance cost reduction by 25% to 30%, ROI by 10x within 5-years’ time frame, and other significant improvements.