Download as PDF
Rovisys > Case Studies > Predictive Maintenance for Gas Pipeline Compressors
Rovisys Logo

Predictive Maintenance for Gas Pipeline Compressors

Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Oil & Gas
Applicable Functions
  • Process Manufacturing
Use Cases
  • Machine Condition Monitoring
The Challenge

CPG had a compression asset failure that interrupted service and had the potential to create customer dissatisfaction.

About The Customer
Houston-based Columbia Pipeline Group (CPG) owns 15,000 miles of interstate pipeline across 16 states. They operate more than 100 stations with approximately 1.1 million horsepower of compression, delivering approximately 1.3 tcf of natural gas per year.
The Customer
Columbia Pipeline Group
The Solution

CPG tapped Aurora, Ohio-based automaton firm, The RoviSys Co., to develop a real-time monitoring system. The new enterprise analytics program uses SharePoint, PI, and SQL technologies to analyze data and drive proactive and corrective actions. Its objectives are to avoid a facility shutdown and to minimize failures in compressor stations.

Data Collected
Downtime, Fault Detection, Gas Meters, Maintenance Requirements, Per-Unit Maintenance Costs
Operational Impact
  • [Efficiency Improvement - Deployment]
    Upon implementation, the process for cutting over from the old PI system to the new system was seamless.
  • [Efficiency Improvement - R&D]
    Also, two additional PI environments were designed and implemented: one for CPG to develop new analytic concepts and the other for early adopters to test those concepts before deploying the technology to the entire enterprise. These environments allow CPG to grow its ideas without disrupting day-to-day operations.

Related Case Studies.

Contact us

Let's talk!

* Required
* Required
* Invalid email address
Yes, i want to receive the IoT ONE Insights - Newsletter.
Go to Action

Thank you for your message!
We will contact you soon.