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

Published: 07 October 2021 Publication History

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.

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  • (2022)Substation Equipment Spare Parts’ Inventory Prediction Model Based on Remaining Useful LifeMathematical Problems in Engineering10.1155/2022/33968502022(1-11)Online publication date: 27-Apr-2022

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cover image ACM Other conferences
ICRCA 2021: 2021 the 5th International Conference on Robotics, Control and Automation
March 2021
129 pages
ISBN:9781450387484
DOI:10.1145/3471985
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 October 2021

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Author Tags

  1. FM
  2. IoT
  3. KPI
  4. O&M
  5. PM
  6. PdM
  7. RCM
  8. RM

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  • Research-article
  • Research
  • Refereed limited

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  • Mapua University

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ICRCA 2021

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Overall Acceptance Rate 15 of 29 submissions, 52%

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Cited By

View all
  • (2022)Substation Equipment Spare Parts’ Inventory Prediction Model Based on Remaining Useful LifeMathematical Problems in Engineering10.1155/2022/33968502022(1-11)Online publication date: 27-Apr-2022

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