Revolutionize Asset Monitoring with Acoustics & AIoT in Oil and Gas industry

“Delek is on a path for our Refinery of Future with a heavy emphasis on digital technologies that will enable efficiency and process improvements. A significant piece of that journey is asset reliability technologies and we have selected Nanoprecise after a competitive evaluation of several offerings on the market. The decision to go with Nanoprecise was based on Hardware, Quality of the AI and Analytics, Technical Support, Competitive Pricing, and the ability to integrate with our broader vision. We’re excited to be scaling up with Nanoprecise to implement their technology across all of our refineries, expand further to our logistics assets, and look forward to their continued support for our business goals.”

Billy Bain

Sr. Director Business Transformation,

Delek US Holdings, Inc.

Say No to Unplanned Downtime

Every industry has its own set of challenges when it comes to maintaining its assets. In the oil and gas sector, the challenges are even more complicated. Companies are battling the need to increase production while lowering operational costs with improved worker safety. With diverse and complex equipment sets often placed in hard-to-reach, remote locations, the challenge of frequent monitoring is huge. Real-time insights on machine health and performance of offshore pumping station, compressor, drilling rig, transportation equipment, pipeline booster station, or any other critical piece of machinery throughout the upstream, midstream and downstream processes, helps maintenance and reliability professionals to make faster and accurate decisions, that drive efficiencies and improve the competitive advantage

Increase Asset Life with Acoustics + AI

Sound is the earliest indicator of failure and Operators have been using sound to gauge the condition of the machines for a long time. During high noise, the equipment may still continue to operate within required parameters, but when left unaddressed, its health will start to deteriorate at a faster rate until the motor completely breaks down. However, in most cases, the distinction in sound is not heard in time to prevent unplanned downtime.

MachineDoctor is the state-of-the-art wireless industrial IoT hardware that captures acoustics emissions to detect anomalies in the operating parameters of the machine and predict failures.

Plug

Machine Doctor™ wireless sensors can be installed on machines using different options such as magnetic bases, stud mounting or adhesives. The sensors connect to each other and the internet automatically in less than 5 minutes.

Play

MachineDoctor™ collects the data and sends it to the cloud, where the data is analyzed by RotationLF – our patented Machine Learning algorithm. This algorithm can learn in as little as 5 days, and provides a holistic dashboard with complete information about the machine health, thereby empowering the users with the right data at the right time.

Peace

Peace

The system performs automated fault diagnosis and offers recommendations to take necessary action. It also predicts the remaining useful life of the equipment, thereby enabling the plant teams to schedule maintenance and allocate manpower appropriately. The system notifies teams with NanoAI alarms via SMS and E-mail, along with prescriptive analytics to aid in their maintenance activities. The Plug and Play Solution gives Peace of mind to maintenance professionals across industries, by giving sufficient time for planning of maintenance activities.

Revolutionize Asset Monitoring with Acoustics & AIoT

Customers who are saving Millions of Dollars in Downtime Cost with Nanoprecise Solutions

Oil & Gas Application Value Creation

Accelerate the performance of your assets with AI-based Predictive Maintenance

Say No to Unplanned Downtime

Increase Asset Life with Acoustics + AI

Creating True Values for our Customers

Detecting Polished Rod Misalignment using Acoustic Emission, 240 hours in Advance

Applications We Cover

How it works

Don't wait for costly downtime. Prevent it.