Automation of Predictive Maintenance Using Internet of Things (IoT) Technology at University-Based O&M Project

Abstract

Predictive Maintenance can be defined as a type of advanced maintenance that detects the onset of system degradation allowing causal stressors to be eliminated or controlled prior to any significant deterioration in component physical state. Thru Internet of Things (IoT) Technology, automation, and implementation of Predictive Maintenance are possible. The purpose of this study is to propose the implementation of Predictive Maintenance using IpT Technology at University-based Operation & Maintenance Project that aims to transform the current Key Performance Indicator (KPI) of PM to CM Ratio from 80:20 to 90:10. Six Sigma DMAIC Methodology and Data-Driven Predictive Maintenance Planning Framework were utilized as the methodology of this research. Research’s results show that KPI, 90:10 (PM to CM Ratio) is achievable and maintenance cost can significantly reduce from 25% to 30%. Other valuable benefits are return of investment (10X), elimination of breakdown (70 - 75%), reduction in downtime (35% - 45%) and increase of production (20% - 25%). The proposed concept can be utilized in other industries to achieve high customer satisfaction percentages, sustainable operations, fault prediction, and online monitoring using PC or mobile applications.

Industry 4.0 and Six Sigma: a systematic review of the literature and research agenda proposal

“…Integrations may bring about efficiency benefits for how supply chains are managed via automation data management for manufacturing and logistics systems, by identifying defects and eliminating non-value-added activities (Jayaram, 2016). These benefits can be extended to predictive maintenance automation with the help of DMAIC projects, to eliminate breakdowns and machine downtime, thus improving the quality and performance of business processes and increasing returns on investments (Fernandez et al. , 2021; Yadav et al ., 2021).…”

“…Benefits of the relationships between Big Data/BDA and SS Six Sigma and I4.0 systematic review defects and eliminating non-value-added activities (Jayaram, 2016). These benefits can be extended to predictive maintenance automation with the help of DMAIC projects, to eliminate breakdowns and machine downtime, thus improving the quality and performance of business processes and increasing returns on investments (Fernandez et al, 2021;Yadav et al, 2021). 4.2.3.6 Other technologies.…”

Review on the Evolution and Impact of Iot-Driven Predictive Maintenance: Assessing Advancements, Their Role in Enhancing System Longevity, and Sustainable Operations in Both Mechanical and Electrical Realms

“…This data is then preprocessed and utilized in machine learning models to predict potential equipment failures, thereby enabling timely maintenance interventions. Fernandez et al (2021) further emphasize the practical implementation of IoT-driven predictive maintenance. Their study demonstrates the successful application of IoT technology in automating predictive maintenance at a university-based operation and maintenance project.…”

“…This proactive approach not only extends the life of mechanical and electrical systems but also optimizes their performance, ensuring sustainable and efficient operations (Madasamy et al, 2023). Fernandez et al (2021) provide a practical example of IoT's impact on system longevity through their study on the automation of predictive maintenance in a university-based operation and maintenance project. The implementation of IoT technology in this context demonstrated a significant improvement in the key performance indicator of preventive maintenance to corrective maintenance ratio, shifting from 80:20 to 90:10.…”

“…Their study demonstrates the successful application of IoT technology in automating predictive maintenance at a university-based operation and maintenance project. By adopting a data-driven predictive maintenance planning framework, significant improvements were observed, including a reduction in maintenance costs and downtime, as well as enhanced production efficiency (Fernandez et al, 2021). These outcomes highlight the potential of IoT in transforming maintenance practices across various sectors, leading to more sustainable operations and improved system longevity.…”