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Nanoprecise

Industrial IoT predictive maintenance platform Nanoprecise secures funding from Sensata Technologies

May 05, 2021

Edmonton (Alberta) [Canada], May 5 (ANI/PRNewswire): Nanoprecise, a leading predictive maintenance platform, today announced an investment led by Sensata Technologies, a leading industrial technology company and provider of sensor-rich solutions that create insight for customers.
This funding will allow Nanoprecise to continue its rapid pace of growth with the support of Sensata, a global business focused on sensing and data insight.
Founded in 2015 in Edmonton, AB, Canada, Nanoprecise has built a rapidly growing global position in the fast-growing IoT industry. Nanoprecise has created a unique 6in1 IoT sensor named the MachineDoctor™ and this IoT sensor is integrated with advanced analytics software that is driven by ML/AI algorithms providing truly
.
Nanoprecise's
™ analytics software diagnoses machinery in industrial environments, including motors, gearboxes, turbines, and centrifugal compressors, among others. It records the real-time RPM, sound, vibration, temperature, humidity, and other key parameters of the machine to detect anomalies in near real time to predict the
of the component empowering plant operators or end-users to manage decisions that may cause major damage or
.
Nanoprecise has made this technology available in the market in numerous commercial models that allow different organizations to maximize return on investment.
Sensata's investment in Nanoprecise is guided by its strategic growth initiative to expand its Industrial Internet of Things and Machine Health Monitoring (MHM) offerings. "We see tremendous opportunity to partner with Nanoprecise, a leader in the development of advanced hardware and software to monitor and predict the remaining useful life of our customer's rotary equipment," said Naoto Mizuta, Vice President, General Manager, Sensata Industrial. "We are excited to partner with Nanoprecise to advance its solution and meet our strategic objectives around data insights in the MHM space."
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