Level: Intermediate
TCM Section(s)
11.3. Information Management
2.3. Strategic Asset Management Process Map
Venue: 2024 AACE International Conference & Expo
Abstract: The current state of facility asset management relies upon infrequent inspections leading to fix-at-failure and preventive or scheduled maintenance strategies, which directly contribute to the trillion-dollar federal facilities' deferred maintenance and repair backlog in the United States. To improve asset management programs, many organizations are looking into more technologically advanced maintenance strategies to shift from reactive or preventative facility management to using data to drive their maintenance strategy. Data-driven decision-making is emerging as the cornerstone of effective facility management. Industries are rapidly adopting this paradigm shift, focusing on the escalating importance of accessible and dependable data. This trend is particularly pertinent to aging infrastructure and facilities, where the availability of accurate data plays a pivotal role in curtailing maintenance costs by allowing organizations to allocate funds to those assets in need of maintenance.
This paper describes the integration of artificial intelligence (AI) and internet of things (IoT) sensors to create a transformative predictive maintenance (PdM) solution, allowing asset owners and managers to carefully predict upcoming equipment failures and take the required steps to mitigate them. In cases with modern assets, programmable logic controller (PLC) data may be used and incorporated into AI models. This paper will focus specifically on IoT integration and post-installation on older assets. Use cases, implementation methods, and specific considerations will be highlighted to illustrate the efficacy of this solution. Lastly, the processes of a case study are highlighted to demonstrate how this application was delivered in a real-world scenario. The trajectory of asset management is poised to shift dramatically from traditional reactive maintenance towards PdM strategies, and this solution is a critical component to achieving that goal.
TCM Section(s)
11.3. Information Management
2.3. Strategic Asset Management Process Map
Venue: 2024 AACE International Conference & Expo
Abstract: The current state of facility asset management relies upon infrequent inspections leading to fix-at-failure and preventive or scheduled maintenance strategies, which directly contribute to the trillion-dollar federal facilities' deferred maintenance and repair backlog in the United States. To improve asset management programs, many organizations are looking into more technologically advanced maintenance strategies to shift from reactive or preventative facility management to using data to drive their maintenance strategy. Data-driven decision-making is emerging as the cornerstone of effective facility management. Industries are rapidly adopting this paradigm shift, focusing on the escalating importance of accessible and dependable data. This trend is particularly pertinent to aging infrastructure and facilities, where the availability of accurate data plays a pivotal role in curtailing maintenance costs by allowing organizations to allocate funds to those assets in need of maintenance.
This paper describes the integration of artificial intelligence (AI) and internet of things (IoT) sensors to create a transformative predictive maintenance (PdM) solution, allowing asset owners and managers to carefully predict upcoming equipment failures and take the required steps to mitigate them. In cases with modern assets, programmable logic controller (PLC) data may be used and incorporated into AI models. This paper will focus specifically on IoT integration and post-installation on older assets. Use cases, implementation methods, and specific considerations will be highlighted to illustrate the efficacy of this solution. Lastly, the processes of a case study are highlighted to demonstrate how this application was delivered in a real-world scenario. The trajectory of asset management is poised to shift dramatically from traditional reactive maintenance towards PdM strategies, and this solution is a critical component to achieving that goal.