Building a Strong Predictive Maintenance Plan to Get the Most from Your Equipment
Building maintenance has advanced significantly since the beginning of the 21st century. Facility...
For facility managers, maintenance plays a critical role in your day-to-day operations and often it’s hard to get ahead of your to-do list.
The primary responsibility of facility managers (FMs) is to protect assets – both the building itself and all of the expensive machinery and materials within. This includes mitigating risks of costly emergency repairs, which result in expensive service calls and can cause tension between the building and its occupants if any revenue efforts are impacted by the emergency work.
That’s why predictive and preventive maintenance can transform the way FMs work through the maintenance issues at their buildings. But only about 4% of FMs are utilizing this powerful method of maintenance management. In this article, we’ll dive into why that is and what FMs can do to get ahead of the pack on this.
First, let’s define some key terms.
Preventive maintenance is a key component of facility management that aims to address potential issues before they become major problems. By proactively identifying and addressing maintenance needs, preventive maintenance helps organizations avoid costly emergency repairs and minimize downtime. It involves regularly scheduled inspections, routine maintenance tasks, and the replacement of worn-out components.
One of the main advantages of preventive maintenance is its ability to extend the lifespan of equipment and assets. By implementing preventive maintenance strategies, organizations can ensure that their assets operate at optimal levels and avoid unexpected failures. This can lead to significant cost savings in the long run.
Preventive maintenance also enhances the overall safety and functionality of buildings. Regular inspections and maintenance tasks help identify and address potential safety hazards, ensuring a safe working environment for occupants. Additionally, preventive maintenance minimizes the risk of equipment breakdowns and disruptions to daily operations, promoting efficiency and productivity.
Predictive maintenance takes preventive maintenance a step further by leveraging technology and data to predict equipment failures before they occur. By utilizing advanced analytics and monitoring systems, organizations can collect real-time data on the performance of their assets. This data is then analyzed to identify patterns, detect anomalies, and predict when maintenance is required.
One of the key advantages of predictive maintenance is its ability to optimize maintenance schedules and maximize equipment uptime. By identifying potential failures in advance, organizations can plan maintenance activities strategically, minimizing downtime and disruptions to operations. This proactive approach allows for better resource allocation and scheduling, resulting in cost savings and improved operational efficiency.
Predictive maintenance also enables organizations to optimize their maintenance budgets. By accurately predicting when maintenance is required, organizations can allocate resources more effectively, avoiding unnecessary maintenance tasks and reducing costs. Additionally, predictive maintenance helps extend the lifespan of assets by addressing issues promptly, ensuring their optimal performance and longevity.
To successfully implement preventive and predictive maintenance strategies, organizations need to invest in the right tools and technologies. Facility management software, such as computerized maintenance management systems (CMMS) or cloud-based integrated workplace management systems (IWMS), can play a crucial role in streamlining maintenance processes.
These software solutions enable organizations to track and manage maintenance tasks, generate reports and analytics, and schedule preventive and predictive maintenance activities. They provide a centralized platform for storing equipment data, maintenance history, and performance metrics, facilitating informed decision-making and efficient maintenance planning.
But often they aren’t enough on their own. While these systems effectively track work orders and asset attributes, they typically don’t contain algorithms that are actively running on real-time and historized data to predict failures based on actual operation. At most, they’re able to track lifespan based on published OEM lifespan recommendations. As facility managers and chief engineers are well aware, a lot happens during the operation of a building that results in equipment running short of its manufacturer-defined useful life.
Fault detection and diagnostic (FDD) systems, traditionally contained within or offered as an overlay to a Building Management System, are a start on the predictive maintenance journey. These rules run on real operational data in order to help operators identify problems they wouldn’t otherwise be aware of from traditional moment-in-time alarms. When FDD includes a predictive maintenance rules library is when the options for FMs to change the maintenance game really open up.
Data plays a crucial role in the success of preventive and predictive maintenance strategies. Organizations need to collect and analyze data from various sources to gain insights into asset performance, identify maintenance patterns, and make informed decisions. But they don’t do it alone. As we said above, FDD systems are a great start because they’re already crunching the numbers on operational data, ideally from various systems but at least from HVAC.
When operators are comfortable using the FDD to inform their maintenance agenda, they’re already leaps and bounds ahead of their peers who manage other buildings. Advanced FDD systems take it two steps further – they integrate to or provide their own work order management system and they offer predictive maintenance rules to catch costly repairs or critical failures before they happen.
According to a recent workplace index report, only about 4% of FMs surveyed report using IoT data for predictive asset maintenance. IoT data can be gathered from a variety of sources, including:
IoT sensors provide real-time data on equipment performance, energy consumption, and space utilization. By monitoring equipment conditions and usage patterns, organizations can detect anomalies and predict maintenance needs accurately.
BAS collects data on building systems, such as HVAC, lighting, and security. Analyzing this data can provide insights into equipment performance, energy usage, and potential maintenance issues.
Digital twins and BIM technologies create virtual representations of assets and buildings, allowing organizations to simulate maintenance scenarios and optimize maintenance strategies. These technologies provide real-time insights into asset conditions and facilitate predictive maintenance planning.
Workforce analytics tools can help organizations understand how employees utilize the workspace, facilitating better space planning and maintenance scheduling. By analyzing occupancy patterns and usage data, organizations can optimize maintenance activities and allocate resources efficiently.
But all of it is meaningless if there isn’t a system established to crunch the data and make informed recommendations to FMs, engineers and building operators. Each of the systems listed above produce a ton of time-series data. Alone, any one of those systems could keep an FM team busy for years. Together, the workload compounds, resulting in alerts that are ignored because they aren’t curated enough to be useful. As FM teams shrink and responsibilities grow, this is a recipe for alarm fatigue and work order overload.
What does the top 4% of FMs know that the rest of us don’t? They know how to use predictive and preventive maintenance to organize their work orders and priorities their repairs.
When data from different systems across a building is funneled into a single data layer where it can be modeled and trended, it becomes possible to run rules on the historical data to make informed determinations about what’s going to happen next with individual pieces of equipment. By providing easy-to-understand write ups of the problem and direct first-step resolution recommendations, these automated fault detection and diagnostics systems with predictive maintenance rules reduce the risk of critical failure and lost revenue.
By implemented a predictive maintenance strategy and operator workflow, FM teams can proactively address maintenance needs, optimize resource allocation, and maximize equipment uptime. The integration of technology, effective communication, and the utilization of data analytics are key drivers of successful preventive and predictive maintenance programs.
Investing in facility management software and leveraging data from IoT sensors, BAS, digital twins, and workforce analytics can provide organizations with valuable insights to make informed decisions and optimize their maintenance processes. By embracing preventive and predictive maintenance, organizations can enhance the functionality, safety, and longevity of their assets, ensuring a productive and efficient workplace for their employees.
By adopting these strategies, organizations can join the top 4% of ops teams that are leading the way in facility management maintenance and reaping the benefits of improved operational efficiency, cost savings, and a competitive edge in the market. Embracing preventive and predictive maintenance is not just a choice but a necessity for organizations that strive for excellence in facility management.
Natalie writes about trends in commercial real estate technology, building data analytics, master systems integration and controls for building systems.