Sensor, AI data analytics avoids downtime, saves energy

ARC Industry Leadership Forum, 2025: Sunil Vedula, PE, founder and CEO of Nanoprecise, said sensors and analytics use pumps, compressors and turbine data to avoid unplanned downtime; most downtime losses are due to rotating machinery.

Sunil Vedula, PE, founder and CEO, Nanoprecise, said pumps compressors and turbines provide data to avoid unplanned downtime; most downtime losses are due to rotating machinery, as explained at the 2025 ARC Industry Leadership Forum by ARC Advisory Group. Courtesy: Mark T. Hoske, Control Engineering

Courtesy: Mark T. Hoske, Control Engineering

Sensor, data analytics insights

Understand how sensors and analytics use pumps, compressors and turbine data to avoid unplanned downtime; most downtime losses are due to rotating machinery, according to Sunil Vedula, PE, MBA, founder and CEO, Nanoprecise at the 2025 ARC Industry Leadership Forum.
Learn five energy centered predictive maintenance steps.
Examine a six-way sensor and analytics with artificial intelligence (AI) that provide predictive maintenance of rotating industrial assets, with applications and benefits.

Using smart sensors and intelligent data analysis can save large amounts of energy and related costs in manufacturing and commercial facility rotating machinery applications, according to Sunil Vedula, PE, founder and CEO, Nanoprecise. Vedula said pumps compressors and turbines provide data to avoid unplanned downtime; most downtime losses are due to rotating machinery, as explained at the 2025 ARC Industry Leadership Forum by ARC Advisory Group.

Nanoprecise MachineDoctor is a six-in-one sensor for vibration, acoustic, mag flux, speed, temp and humidity that sends information to data storage and cloud computing. Courtesy: Mark T. Hoske, Control Engineering

Five energy centered predictive maintenance steps

Vedula said energy centered predictive maintenance steps are:

1. Edge-based anomaly detection on the edge or on the cloud (finding what’s weird).

2. Automated fault diagnosis

3. Automated remaining time to failure

4. Increased energy consumption due to fault

5. Automated root cause and maintenance insight.

Sensor, analytics for predictive maintenance of rotating industrial assets

Nanoprecise MachineDoctor is a six-in-one sensor for vibration, acoustic, mag flux, speed, temp and humidity that sends information to data storage and cloud computing. The Nanoprecise MachineDoctor VibAnalyst Agent finds the cause behind data using artificial intelligence (AI) and a predictive analytics algorithm supplies custom outputs in an application programming interface (API) to provide alerts and populate a dashboard, with a more than 50% increase in accuracy over six months ago, Vedula said, providing a generative AI approach to using technology to find and correct energy wasting issues. Cybersecurity measures are embedded in the design.

The Nanoprecise MachineDoctor VibAnalyst Agent finds the cause behind data using artificial intelligence (AI) and a predictive analytics algorithm supplies custom outputs in an application programming interface (API) to provide alerts and populate a dashboard. Courtesy: Mark T. Hoske, Control Engineering

Growth and industries for energy saving predictive maintenance

The company recently received $35 million in funding to fuel growth, Vedula said.

Case studies include a water utility with a pump cavitation issue, the Nanoprecise solution lowered energy consumption by 20% after the fix after about $45,000 in electricity was wasted over two years. The cost of a pump doesn’t matter in relation to energy cost, the primary cost over a pump’s lifecycle. Nanoprecise has installed about 20,000 of its sensors. The predictive maintenance solution is being applied to oil and gas, mining, metals, steel, automotive, HVAC and other applications.

Mark T. Hoske is editor-in-chief, Control Engineering, WTWH Media, [email protected].

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