Condition Monitoring for Oil & Gas and Energy

– THINaër IoT use case for Oil & Gas and Energy –

Real-time Condition Monitoring

Know the current condition of your high value assets.

Predictive Maintenance

Use inferences and real-time data to predict maintenance needs.

Performance Optimization

Alerts to prevent failures and prevent maintenance.

Organizations spend up to $88 Million each year on unplanned downtime.

Reduce unnecessary burden on high value assets by preventing downtime and optimizing performance.

Summary

An international energy company needed to track the performance of critical assets to prevent the unplanned costs of reactive maintenance.

Challenge

An international oil and gas company was looking for ways to reduce unplanned equipment maintenance. And while difficult to quantify, the downtime amounts to excess loss of multiple millions of dollars each year; the longer the equipment is down, the more financial impact it has on the the organization.

A Kimberlite study identified that offshore oil and gas organizations experience on average $49 million annually in financial impacts due to unplanned downtime. The study goes on to suggest that even a few days of downtime can cost organizations millions of dollars per day.

Unforeseen financial impact coupled with challenges like equipment malfunction and difficulty gaining insight into equipment condition have forced oil and gas companies to look for more efficient and cost effective ways to prevent unplanned expenses.

Solution

The international oil and gas organization identified the most critical pieces of equipment that could easily be used to gather data about uptime, downtime and general maintenance. Using the THINaër Condition Monitoring solution, the organization is able to understand the current state of the equipment and the condition of its environment.

The solution uses industrial beacons capable of transmitting sensor data like temperature, humidity, pressure and dew point, enterprise-grade gateways capable of capturing that sensor data and transmitting it to the THINaër platform, and algorithms that learn base line values of “normal” operating conditions for the oil and gas equipment. Then, over a period of time, THINaër captures the data about fluctuations in environmental condition to do things like:

  • alert local personnel of real-time changes to the envirionment
  • notify critical personnel of unplanned spikes in condition variables
  • trigger downstream workflows based on out-of-range readings or unusual activity
  • notify maintenance teams when equipment is due for service or repair

The data is encrypted both in motion and at rest and is available for use in dashboard applications, integrated systems and other data analytics engines. It’s also made available in Sonar, the web-based dashboard that visualizes real-time data about high value assets and the conditions in which they exist.

Results

While the benchmarks are still being established and the data in the early phases of being captured, projections suggest there exists the potential to save anywhere from $1 Million per day that a single machine is down to over $88 Million per occurrence for the most critical downtime scenarios.

Think about your own industry or organization. Do you know how much it costs each time a machine is out of operation or a single process is interrupted or, worse yet, halted?

THINaër can help both create your benchmarks to determine optimal operating conditions and capture the data required to prove compliance to the benchmarks and identify areas of improvement to ensure compliance.

To learn more about this use case and others powered by THINaër, contact us.

$49 M

Annual financial impact due to unplanned downtime.

Key Takeaways

Customer

  • an international energy company

Industry

  • oil & gas
  • energy

Challenge

  • oil and gas company needed to decrease the cost of unplanned maintenance

Solution components

  • THINaër platform
  • Bluetooth/BLE beacons
  • Enterprise-grade gateway
  • Sonar dashboard
  • data visualization tools
  • THINaër implementation services

Results

  • projected to save between $5 Million to $88 Million per single downtime occurrence

Contacts

Downloads

  • PDF brochure of this use case (coming soon!)

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