Case Study: Data analytics and root cause analysis (RCA) avoids equipment trips and downtime

Project Summary

Platform or equipment trips of the Integrated Control and Safety (ICS) systems and the associated unplanned downtime negatively impact the production efficiency of oil and gas assets.

Being able to avoid these trips would deliver both significant cost savings and an increase in production efficiency. Intelligent Plant used advanced data analytics techniques to build a tool that could analyse alarm and event data in a visual interface.

Intelligent Plant developed an alarm root cause analysis (RCA) capability using data analytics methods and a cloud-based application (SEER) for use in the diagnosis of the major equipment ‘trips’ or downtime. SEER allows the end user to modify operational, maintenance or engineering practice to monitor and potentially prevent future failures.

The project aimed to develop and test an alarm root cause analysis (RCA) cloud-based application (SEER).

Industry value:
The current inability to prevent ‘trips’ has been identified as a major cause of downtime, so the success of the project would mitigate this and increase production efficiency and provide significant cost savings.

Key results:
The SEER application was able to identify trip event commonality and offer statistical insights into events to support the RCA process, delivering statistical insights that would previously have been unattainable due to the extensive time and effort required to produce them.

Lessons learned / Next steps:
Intelligent Plant have plans to further develop the SEER technology to incorporate unit control panel data with existing ICS data to present a fuller diagnostic for engineers and for automation in future.

Intelligent Plant see the potential of SEER to be a game changing application offering vast improvement over traditional working practices. The team will continue to develop SEER to be market ready and have already received commercial interest across a range of industry sectors.