HVAC systems are crucial to the health and safety of power plant operations from maintaining ambient conditions to protecting equipment to, ultimately, facilitating energy-efficient production. Proper cooling and ventilation of a power plant’s equipment—gas turbine, coal generation, diesel/gas mixture or steam turbine—ensures uninterrupted operation, eliminates dangerous fumes and reduces downtime. Companies often invest millions of dollars in plant equipment, yet neglect to include their HVAC system on the critical equipment list. With all of the attention on power generation, ancillary HVAC equipment is the backbone to protecting plant environment for productivity.
While routine maintenance checks are a key part of an HVAC service program, they do not always catch the problems that cause systems to fail. Advances in predictive maintenance (PdM) technology now allow utilities to predict the health of their HVAC systems and perform maintenance before things go wrong. Unlike preventive maintenance, which is schedule-centered, PdM is designed to anticipate potential problems and extend equipment life based on real-time data. Repairs can be made in advance of a breakdown, leading to reduced operational costs and greater overall plant efficiency.
The Impact of IoT on HVAC
The Internet of Things (IoT) is a concept in which “Ëœthings’ utilize embedded technology to communicate and interact with the external environment via the Internet. The sensors provided by IoT allow users to monitor an infinite number of objects, from household appliances to security systems to industrial equipment. While sensors have been used for equipment maintenance for a number of years, the IoT has provided the HVAC industry with the mobility and communications needed for greater system efficiency. Combining sensor technology (based on the sound and vibration of a machine to determine its condition) with a smartphone (equipped to sense and convey that data), critical information on the health of a machine is transmitted in real-time for analysis against that machine’s record and industry norms. An assessment is made and, if needed, repairs and/or replacements can happen.
Advances in PdM
Predictive maintenance is not a new term in the HVAC industry, in fact its concept dates back several decades. According to the U.S. Department of Energy, past predictive maintenance studies have shown that program using predictive maintenance can result in a savings of eight to twelve percent over a program utilizing preventive maintenance alone. In addition, predictive maintenance can reduce maintenance costs up to 30 percent, eliminate breakdowns 70 to 75 percent of the time, minimize downtime and increase production.
Despite the clear benefits of predictive maintenance, only 12 percent of commercial buildings employ this type of technology. One reason is that PdM has been mired in the high-end market, as it requires some technological infrastructure investments up front. In addition to the initial equipment costs, maintaining an in-house staff properly trained in the use of PdM techniques may require an even greater investment. Some examples of the high-end industrial market include gas and oil companies, utilities and aviation.
While these industries have been using predictive maintenance since the 1990s, the use of PdM has grown significantly, allowing businesses to optimize equipment and increase uptime. For example, wind turbine operations present particular challenges regarding reliable diagnostics and prognostics. Most subsystems in wind turbines may fail during operation, including rotors and blades, pitch control systems, gearboxes and bearings, yaw systems, generators, power electronics, electric controls and brakes to name a few. A recent review of advances in wind turbine operation indicated that the use of both PdM and condition based monitoring have proven to be highly effective in condition monitoring and fault diagnosis.
Another example is the oil and gas industry. With falling oil prices, many companies are currently not operating at optimum production efficiency, forcing them to implement strategies for better asset tracking. Predictive analytics can help identify when equipment and assets are likely to fail or need service, and when to perform preventive maintenance to minimize costly unscheduled downtime.
Previously, only the high-end market could reap the benefits of predictive maintenance. Lower-end businesses were not given the same opportunity, leaving a tremendous amount of data unavailable for analysis and decision-making. Advances in PdM solutions level the playing field, enabling commercial buildings, factories and other facilities to experience these energy and cost savings. The ability to connect to machines and their sensors delivers PdM data into the hands of the technicians, who can determine the appropriate action based on the knowledge provided by that data.
IoT, PdM and HVAC are interconnected elements that rely on one another for success. The technology that IoT provides facilitates the predictive maintenance techniques that enhance HVAC systems. Shared information, real-time monitoring and analytics allow businesses to achieve optimum functionality and cost savings. Computer-driven diagnostics provide technicians with critical information that allows them to act more quickly, saving time and averting possible disaster. While machine-assisted predictive maintenance is a fairly new concept, it will soon play an important role in troubleshooting potential equipment malfunction before it happens.
About the author: Saar Yoskovitz, is CEO and Co-Founder of Augury. Prior to founding Augury Systems, Saar worked as an Analog Architect at Intel. Saar holds a B.Sc. in Electrical Engineering and a B.Sc. in Physics from the Israel Institute of Technology.