While analytics that ID and prevent downtime events are squarely in the company’s wheelhouse, MachineSense realized that it could extract more data and do more with it. To take the next step, the company implemented Siemens’ MindSphere, a cloud-based, open Internet of Things (IoT) operating system, for its predictive maintenance and analytics for industrial machinery, components, and infrastructure systems including pumps, compressors, and electrical supply.
“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. 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, available on the Siemens Mindsphere IoT platform," says MachineSense co-founder Conrad Bessemer.
MachineSense also provides its clients with what it calls machine wearables—sensors that are placed on recently serviced machines at a customer site. Data hubs are placed within 30 feet of the wearables and are connected to the customer Wi-Fi network. Through the customer router, the data goes to MindSphere where analytic and trend tools track and interpret machine operating conditions. Thanks to the MindSphere apps and visualization options, machine builders are able to read trend charts and continuously track the condition of their equipment. Account users can also elect to receive alerts regarding the status of their machines via email or text messages.
“MachineSense delivers tremendous value to industrial and infrastructure consumers through the company’s vertically integrated solutions,” said Paul Kaeley, senior vice president, global partner ecosystem at Siemens PLM Software. “We are excited to have MachineSense join the MindSphere ecosystem as a partner so that together we can address operational challenges around power quality, predictive and preventive maintenance, and energy efficiency using MindSphere.”
With MindSphere, developers and software engineers can use Siemens-developed MindApps or create their own apps on the open IoT platform. MachineSense lead the way by creating its own Power Analyzer MindApp, a software product created for use with MindSphere that provides power quality analytics, predictive analytics, advanced power meter, and machine utilization analysis. In its first release, MachineSense will be offering a standard MindApp, and in Q3, a fully customized Power Analyzer MindApp will be available for users and third-party integrators.
According to Siemens, MindSphere allows companies of all sizes to link their machines and physical infrastructures to the digital world easily, quickly, and economically. These companies can harness big data from virtually any number of intelligent connected devices to analyze and uncover transformational insights, enhance their offerings, and launch new business models.
A welcome secondary effect, MachineSense is able to appeal to a broader range of clients with this software than it had been able to previously. Its target client base is often manufacturing and processing plants, a core customer base of Siemens. The OEMs’ PLC data is integrated into the MindSphere platform to complement available IoT sensor technology and solutions. Together, they represent an ecosystem of hardware and software solutions that enable OEMs to gain insights into the vast data that they already possess.
“This partnership with Siemens will allow MachineSense to penetrate deep into the manufacturing and commercial building base, where power quality is increasingly becoming an issue for safe operation and expensive repairs and replacement of the machinery,” says Bessemer.
