Using data in a predictive maintenance model
Unlike standard fault detection software, that only provides raw data, the diagnostics element of FDD provides real-time, applicable insights and, through equipment and system modeling, can identify a fault’s root cause. Knowing the root cause will enable the maintenance team to more quickly and efficiently remedy the problem and restore the system to optimum performance. Using artificial intelligence (AI) in fault prioritization allows engineers to make informed decisions on maintenance and repairs that would normally take hours of manual analysis—ultimately resolving problems faster.
Asset data can also show when a piece of equipment is operating properly at a specific maintenance interval. This allows operators to skip routine maintenance when possible, preserving resources like fossil fuels, plastics, and metals (e.g., copper). By getting ahead of the maintenance schedule, operators aren’t as bogged down and can respond to real time needs. Of course, by continuously making operations more efficient and maintenance processes more precise, it’s expected that wear and tear on equipment will be reduced as well.
Another benefit of a predictive maintenance model is the inherent avoidance of unexpected, costly major repairs because of asset neglect. Assets can become neglected when facility operators are overwhelmed with alarms, analysis, and capital prioritization. Diagnostic software eliminates hours of manual labor and helps streamline operations to get the job done right.
Asset life cycle optimization and replacement forecasting
Historical data allows operators to identify trends and predict future maintenance needs. With improved efficiency, maintenance, and repairs, driven by data analysis, facility operators can optimize the life cycle of assets.
By doing so, assets are used to their full potential—ensuring the most sustainable use of the many resources needed to manufacture new ones. Not only is this a more sustainable use of resources needed for the asset itself, ensuring longevity reduces resource use and emissions from the transportation, removal, installation, and labor necessary for replacement.
As the program becomes engrained in facility operations, predictive analytics can support capital project prioritization—predicting when assets will reach their end-of-useful-life and require replacement. The advantages to financial planning and forecasting are staggering. In the near-future, the ability to be predictive and forward-thinking in a climate-driven economic future will be an invaluablebusiness strategy.
Fault detection and diagnostics may not have direct results on sustainability, but taking asset management to the next level with technical services that offer FDD can. By improving efficiencies and building historical data that can predict future outcomes, sustainability becomes a measurable, achievable goal.
By using predictive analytics, with a wholistic approach, historical data allows ISS to create climate resilience in your facilities. Business leaders can plan for long term cold, dry, heat, and more. As our climate becomes more unpredictable and climate change continues to affect facility operations, solutions like FDD allow us to make critical, consistent, and accurate recommendations.
Sustainability with ISS goes well beyond improving asset competencies, too. We are committed to a sustainable procurement process. ISS is committed to vetting vendors for sustainable practices, ensuring manufacturers meet milestones, and that contractors are environmentally conscious.
As climate change continues to drive business strategy and best practices, it’s important to have a partner you can trust in planning for the future. Sustainability goes well beyond energy use and precision maintenance, but technical services from ISS can help manage these critical aspects.