Nanoprecise Sci Corp
Automated Predictive Maintenance
Overview
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HQ Location
Canada
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Year Founded
2017
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Company Type
Private
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Revenue
< $10m
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Employees
11 - 50
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Website
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Company Description
Nanoprecise has created a "patent-pending" solution (hardware + software) that combines physics, material science, and data analytics to diagnose issues with machinery and detects anomalies, characterizes the faulty components and predicts the "Remaining Time to Failure." Since Nanoprecise was founded in Dec 2017, it has customers spanning across Oil & Gas, Mining, Utilities, HVAC & Infrastructure sectors.
IoT Solutions
Nanoprecise's sensor is the first sensor in the world that extracts RPM, vibration, sound, temperature & humidity information, all from one sensor. The software (which is built on AI algorithms that are only limited to research papers until now) analyzes the data from various sensing elements and achieves Anomaly Detection, fault characterization & remaining useful life prediction. This end to end solution can be deployed cost-effectively and can be utilized on any machine in the world in any industry.
Nanoprecise has developed VibrationLF, a Predictive Maintenance solution incorporating wireless sensors based on nanotechnology and sophisticated Machine Learning technology to accurately diagnose faults in rotating equipment and provide a forecast time to replacement, allowing maintenance teams to plan their maintenance activities.
Nanoprecise has developed VibrationLF, a Predictive Maintenance solution incorporating wireless sensors based on nanotechnology and sophisticated Machine Learning technology to accurately diagnose faults in rotating equipment and provide a forecast time to replacement, allowing maintenance teams to plan their maintenance activities.
Key Customers
AltaSteel, Hindustan Zinc, Iffco, BJ
IoT Snapshot
Nanoprecise Sci Corp is a provider of Industrial IoT sensors technologies, and also active in the chemicals, and utilities industries.
Technologies
Use Cases
Industries
Technology Stack
Nanoprecise Sci Corp’s Technology Stack maps Nanoprecise Sci Corp’s participation in the sensors IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.
Case Study
Detecting Cavitation And High Vane Pass Frequency For Pumps
The Condensate Cooling Water (CCW) pump, one of the critical pumps in maintaining steadystate operations, is a horizontal vane pump operating at up to 1650 m3/hr with a discharge pressure of 9 MPa (62 psi) at 986 rpm. Each day this pump is offline costs the plant $250,000 in lost revenue and each failure costs tens of thousands of dollars to execute an unplanned repair. Thus, Larsen & Toubro (L&T) really needed a predictive maintenance solution to detect faults at an early stage and provide a reliable prediction of Remaining Useful Life (RUL)
Case Study
Detection of a Bearing Outer Race Failure on a critical pump saved downtime cost
The process condensate pump, one of the critical pumps in the manufacturing process, has a history of failures every 6 to 12 months. It is a centrifugal pump operating at 3000 rpm with a discharge pressure of 28 MPa (400 psi). Each day this pump is offline, it costs the plant as much as $145,000 in lost production and each failure costs tens of hundreds of dollars to execute an unplanned repair. Nanoprecise Sci Corp was asked to implement a predictive maintenance solution in order to detect faults at an early stage and provide a reliable prediction of Remaining Useful Life (RUL).
Case Study
Automatic monitoring of acoustic emission saves catastrophic failure
Traditional measurement tools are ineffective when it comes to slowly rotating equipment. There are faults like Bearing Failure, Ring Plugging, Gear Tooth Crack and many more which can lead to the shutdown of machines. 1 minute of downtime cost the company $10. RingPluggingis a very common issue which Pinnacle Pellet was facing very frequently due to diverse feed quality into the machines. Product ring plugging can be detected as sound levels increase in specific roller bearings.
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