By Neil Maldeis
Originally published in the February 2011 issue of Today’s Facility Manager
The traditional approach to heating, ventilating, and air conditioning (HVAC) maintenance relies on a calendar or hour meter to determine when equipment is serviced. But technology advances over the last decade provide facilities managers (fms) with actionable information that enables them to perform maintenance when it is needed, not just because the schedule says it is time.
Predictive or reliability centered maintenance uses testing, diagnostics, and computer modeling to identify actual maintenance needs. This approach hinges on establishing a performance standard for HVAC systems based on the performance of similar systems. Systems are continuously monitored, and their actual performance is compared to benchmark data. As a result, it is possible to identify potential problems and schedule maintenance before they can cause systems to fail.
With their budgets under pressure and the cost of energy and labor rising, many fms are increasing their emphasis on predictive maintenance as a means of controlling costs and reducing the likelihood of an HVAC system failure that could shut down their operations.
Advances in HVAC related technologies make it possible for many organizations to adopt a predictive maintenance model without a large capital investment. In fact, most organizations already have the technology backbone in place to enable a predictive approach.
For example, today’s sophisticated building automation systems are designed to support predictive maintenance programs, and web enabled dashboard make it easier than ever for fms to gather, access, and apply relevant information to keep their buildings operating efficiently. Most organizations already have highly capable building automation systems in place. But facilities staffs may need additional training to take full advantage of their features, according to the Platts division of McGraw Hill, which estimates that more than half of facilities departments are underusing their building automation systems.
HVAC fault detection and diagnostics (FDD) is another advanced technology that enables predictive maintenance. FDD technologies automatically detect and report faults in critical HVAC components, giving technicians early warning of potential problems, improving reliability, and reducing unscheduled downtime. Using FDD can save fms as much as $1 per square foot in annual energy and maintenance costs, according to New Building Institute estimates.
The latest predictive modeling technologies use computer programs to compare an HVAC system’s operating characteristics with aggregated information from many similar systems. For example, they continuously analyze vibration levels, refrigerants and other fluids, and motor performance to detect potential problems. This enables fms to schedule maintenance proactively and have needed parts on hand. [To read about the importance of HVAC conditions in data center environments, see “Today’s Data Centers,” also from this issue.]
Energy services companies (ESCOs) often include predictive modeling as a service offering. Many fms seek this advice when determining if a predictive maintenance program is the best approach. Others have the knowledge and resources to take on this task themselves. In either case, fms will want to start by calculating the true cost of the current approach to HVAC maintenance. Identifying the average cost of planned and unplanned maintenance over a period of several years is a good starting point. But it is also important to calculate the potential impact of a system failure on operations. For example, fms should estimate the cost to their budgets of responding to an HVAC failure, including the higher cost of repairs made in a reactive mode.
Next, fms should consider the disruption caused by an unplanned system failure that could be avoided with a proactive predictive maintenance program. They should consider that an unplanned HVAC failure could cause a building to close for hours or even days. The cost of an unplanned failure should be estimated in terms that make sense to the organization (which may include lost revenue and the impact of an HVAC failure on productivity, customer satisfaction, or business reputation).
Many large organizations have most of the technology needed to adopt a predictive maintenance solution. In stating their case, fms should consider any upfront investment required, including hardware, software, training, or changes to existing service contracts. They should then estimate the savings from eliminating scheduled, but unnecessary, maintenance tasks, which will offset the cost of implementing a predictive maintenance program.
When all these factors are considered, predictive maintenance is worth considering for most organizations.
Maldeis is energy engineering manager for Trane. He is responsible for the technical development, support, and review of performance based contracting solutions and activities on a national basis. He has nearly 30 years of experience as a mechanical/project engineer in building construction and energy conservation.
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