Plant operators can capture machine data to help predict when machines will fail or require maintenance by using automated, online condition monitoring. One energy company manually monitored rotating equipment at a power generation plant, sometimes taking more than 60,000 measurements per month. These manual diagnostic rounds were inconsistent due to human error or competing priorities. Plus, manual collection is costly. By adopting online condition monitoring tools, plants can monitor the condition of plant equipment. They can also set up alarms that signal when equipment is stressed or needs attention.
NI InsightCM Enterprise is a software solution National Instruments (NI) recently introduced to help companies gain insight into the health of their equipment. With years of experience in condition monitoring, NI developed NI InsightCM Enterprise as its first end-to-end software solution that addresses big analog data challenges and builds on the Industrial Internet of Things (IIoT).
NI is no stranger to condition monitoring. "We've been doing it for over 15 years now, but through the tools approach where customers take NI tools and use it as they see fit for this or that application area," Kamalina Srikant, product manager for condition monitoring at National Instruments, told Design News. "This is the first time, as a company, we're creating an end-to-end solution and we've decided to do this because we see a big market need."
Using NI InsightCM Enterprise, plant operators can cost-effectively monitor both critical and ancillary rotating machinery, offering a holistic view of their plant equipment. The solution involves data management, data analysis, and systems management challenges that are common in big analog data applications. NI designed the system with the flexibility and open architecture to make evolving diagnostic requirements.
NI InsightCM Enterprise was designed to connect to sensors from a wide range of vendors. "We're sensor neutral because we don't want to just focus on vibration. We support vibration, pressure, digital inputs, temperature, and more," Srikant told us. "Our vision is to fuse all of this sensor data together into the system, so we're working on more complex measurements such as, thermal imaging, partial discharge, and motor current signature analysis."
The NI system acquires and analyzes sensory information, generates alarms, and allows maintenance specialists to remotely diagnose machine faults. The condition monitoring system can acquire data from a wide range of sensors for fault diagnostics. The solution was designed to simplify the configuration of measurements from thousands of sensors, so users can remotely monitor device health, configure channels, and upgrade firmware on deployed systems.
Condition monitoring is coming into its own as part of the technology renaissance in manufacturing. Plus, reductions in cost have made the technology available to a wider range of users. "With trends such as the decreasing cost of sensors and higher performance ratio for price, we are seeing more adoption than we did in the past," said Srikant. "Also, with the trend around big analog data, everyone is trying to solve the question of 'what do you do with the data?' In past people would only monitor critical parts and systems were disparate, but today there is a drive toward gaining more business value from condition monitoring."
The companies most interested in condition monitoring still tend to be the companies with the most at risk. "The companies that are most motivated to solve this are the ones that have the highest risk associated with downtown," said Srikant. "That includes consumer packaged goods, discrete manufacturing at high volumes, or companies doing process manufacturing where downtime costs millions of dollars."
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