MachineSense expands predictive maintenance offerings
MachineSense ,which makes hardware and software for predictive maintenance, used NPE2018 to announce a new platform for its products and launch new offerings. Power Analyzer will be the first of MachineSense’s products available on MindSphere, a cloud-based, open Internet of Things (IoT) operating system from Siemens.
MachineSense’s portfolio includes products that employ machine sensors and analytic software for monitoring electricity, vacuum pumps and machine components. The company touts the products’ ability to increase machine uptime, extend machine life and improve efficiency by allowing critical maintenance to be performed at a convenient time rather than after a failure occurs. Easy-to-navigate dashboards allow users to see real-time machine conditions, as well as historical trends. If a machine or component begins operating outside established thresholds, technicians receive actionable maintenance advice via email or text message in advance of machine or component failure, according to the company.
The company’s new offerings include Component Analyzer, which tracks the health and operating conditions of rotating industrial machinery components, and a series of long-range sensors.
MachineSense’s Power Analyzer, unveiled last year, uses sensors to monitor electrical lines and electrical equipment to provide detailed power- quality and energy-consumption information for connected equipment. It also can be used for predictive maintenance by detecting power fluctuations involving equipment.
The sensors can detect power-quality issues such as voltage swells and sags, voltage imbalances and harmonic distortion. These problems can damage equipment, forcing costly repairs and the need for premature equipment replacement.
MachineSense and Siemens are working to offer Power Analyzer on the MindSphere platform. That will give MachineSense customers the option of using MindSphere servers for receiving and processing the information instead of MachineSense servers. As part of the agreement, the customer’s router will send data through a secure connection to MindSphere, where analytic and trend tools will track and interpret machine operation conditions. This arrangement will ensure a secure transfer of data, as well as the convenience of a secure platform for buying and downloading other manufacturing-related apps.
“It allows end users the ability that they don’t have to create a bunch of separate internet portals for all these different service providers,” Machine-Sense President and COO Jim Zinski said. “We all go through the one secure Siemens channel. That makes the objections to adoption much less complicated for an IT department.”
He compared MindSphere to an iPhone or Android app store that offers software and apps from trusted vendors.
Under the agreement, users also will be able to pair their MachineSense sensor data with other tools provided through MindSphere. Those tools and apps will be available through Siemens and other vendors.
“MachineSense is very strong with predictive maintenance and machine help; that’s what we focus on,” Zinski said. “But you may have a customer that would like to add to that more of a service package or a production-monitoring package that would use the same data, and it would provide a different value proposition using that data.”
Concerns about power quality are growing among manufacturers and commercial building managers, according to MachineSense co-founder Conrad Bessemer.
“Popular energy-saving initiatives, like LED lighting and variable-speed motor drives, have unknowingly led to higher harmonic distortion levels in most manufacturing plants and commercial buildings,” he said.
“These harmonics can cause substantial energy waste in unrelated areas of the facility. Harmonics and other power-quality problems also contribute to prematurely failed electrical devices like utility motors in compressors and HVAC systems. These harmful conditions can be diagnosed without a technical expert using the MachineSense Power Analyzer.”
Like Power Analyzer, Component Analyzer, which debuted at NPE2018, and MachineSense’s Vacuum Pump Analyzer eventually will be accessible through Siemens MindSphere.
Component Analyzer employs patented machine-wearable sensors for preventive and predictive maintenance. The sensors can detect abnormal machine vibrations and conditions related to motor health, including pending bearing failure — one of the most common problems in any rotating machine part.
“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,” Zinski said. “Any improper installation [of the sensor] or loose mounting is detected through analytics and sent as an alarm to users.”
Continuous monitoring allows MachineSense software to recognize anomalies and events that can serve as early indicators of developing component health problems.
“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,” Zinski said.
The hardware and software can be quickly installed right out of the box and fitted to nearly any industrial machinery that has rotating components, according to the company.
Component Analyzer will also be available on the Microsoft Azure IoT Central platform in the third quarter of this year, the company said.
MachineSense’s new LoRa long-range sensors are designed for operations with limited access to power or Wi-Fi. Sensors are available for use with MachineSense’s existing maintenance and analytics products, including Power Analyzer, Component Analyzer and Vacuum Pump Analyzer, and will be able to perform a range of new tasks, including monitoring aspects of long-distance vacuum-conveying processes. The sensors also can work with outdoor silos and conveying systems, according to the company.
The new wireless sensors measure vibration, vacuum, pressure, temperature and energy in real time, similar to MachineSense’s existing sensors. However, while traditional sensors can transmit information only 15 to 30 feet, the new IP67-rated sensors can transmit information more than six miles. They are dust- and water-resistant.
LoRa sensors use unlicensed radio spectrum below 1 gigahertz to transmit secure data.
“It is easy to plug into the existing infrastructure and offer a solution to serve battery-operated IoT applications where access to power is a challenge,” Zinski said.
Bruce Geiselman, senior staff reporter
Alpharetta, Ga., 800-743-6367,