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5/4/2018 | 4 MINUTE READ

Round-the-Clock Predictive Maintenance, Analytics Technology for Rotating Components

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Component Analyzer from MachineSense tracks the trend health and operating conditions of rotating industrial machinery components 24/7. 

Baltimore-based MachineSense, LLC is adding to its portfolio of products at NPE2018 with the release of Component Analyzer. This new product tracks the trend health and operating conditions of rotating industrial machinery components 24/7 with the purpose of helping processors become smarter and more efficient  by virtually eliminating reactive maintenance procedures and unplanned downtime. The product will be on display in booth W3729. 

Component Analyzer senses machine vitals using its patented “machine wearable” design for preventative and predictive maintenance. Its compact multi-sensing system taps abnormal vibration, machine utilization, ambient operating conditions, bearing health, and sensor installation.

“Unlike other vibration sensors available in the market, the component analyzer sensor is an extremely lightweight metal powder filled polymer housing, which enables quick and easy magnetic mounting on a machine’s surface. Any improper installation or loose mounting is detected though analytics and sent as an alarm to users,” says James Zinski, CEO of MachineSense, LLC.

Adds MachineSense co-founder and CTO, Dr. Biplab Pal, “Component Analyzer is the world's first fully edge enabled vibration analyzer, which essentially means all the vibration analysis—including advanced machine learning—is performed in the sensor's edge. However, actionable analytic data can be accessed via the cloud app as well as locally via a mobile app.” Zinski says that’s advantageous because “local edge analytics enable continuous high-speed data monitoring, reduce data transfer and increase data integrity.”

Powered by hybrid nature of edge analytics and cloud database, Component Analyzer is capable of three different modes of analytics: a real time quick view, which is available locally with a mobile app; quasi real-time predictive machine health; and an historical view of the machine health issues both available in the cloud app. “This provides very deep and wide insight into machine health,” said Pal.

Component Analyzer is both a hardware and a software solution. MachineSense uses powerful analytic software, licensed as Crystalball, to understand the data and then reassembles that data into dashboards. The software is accessible through a web browser or mobile app, so users can connect anytime from any desktop computer, laptop, tablet or phone with an internet connection. Visualization of valuable operating metrics is delivered through easy-to-understand dashboards. Users can quickly scan through the status of many machines to identify potential issues that need to be examined in more detail. Thresholds can be set that trigger notifications be sent to technicians when there’s an issue or they can simply rely on the system to issue the baseline established warning when a component or a machine is approaching a fault.

“Easy-to-understand icons direct users to view component health trends displaying up to six months of operating history. Customizable threshold values allow users to identify preferred maintenance conditions, unhealthy operating conditions, or deteriorated component health,” Zinski notes.

The easy-to-navigate software allows users to view real time machine condition graphically with basic green, yellow or red backgrounds. “It’s as simple as a ‘go/no-go view’ of the graphics, says Pal, the software inventor. If a machine or component reaches a yellow warning state actionable maintenance advice is delivered to assigned technicians via email or text messages in advance of machine or competent failure.

“Patented time-domain data sampling methods enable continuous trend monitoring to spot anomalies and repeatable events that occur under changing process or operating conditions, allowing early detection of developing component health issues, and the operating trends that may be causing them,” Zinski states.

Each user can access the account via a personal profile, with permissions that allow users varying levels of access. The system allows for user-defined roles such as: data viewers, data collectors, alarm recipients and administrators. Historic data is available through equipment performance trend lines. And, a streamlined overview dashboard delivers a clear summary of the powerful analytics for all monitored equipment, neatly organized by department and location.

In development, according to Zinski, are “traditional frequency-domain data and analytics that will add enhanced diagnosis capabilities for bearing and gearbox faults initially. Other device libraries are being added each month.”

“Beyond readily available analytics for predictive and preventative maintenance, MachineSense App third party integrators will be able to use its hundreds of rich vibration signatures to build even more advanced analytics customized for their machine using Open API data access,” Pal adds.

“The constant monitoring and predictive analysis that Component Analyzer offers will drastically reduce the cost of traditional reactive maintenance practices by nearly eliminating unplanned downtime, rushed replacement parts and overtime, states Zinski.” He added, “Further gains are realized by increased uptime, extended machine life and improved efficiency by understanding the best time to perform critical maintenance.”

The hardware and software can be quickly installed right out of the box and fitted to nearly any industrial machinery that has rotating components used in diverse industrial applications. “MachineSense sensors have been field tested for more than three years,” notes Zinski. Applications include plastics, agricultural products, food and beverages, medical devices, mining and construction, packaging, pharmaceuticals, textiles, woodworking and many other general industrial applications.

Component Analyzer will also be available in Microsoft Azure IoT Central and Siemens Mindsphere Market place in Q3 2018 so that Azure and Mindsphere customers can access this system in their own platform, reports Pal.


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