Energy / Oil and gas

Woodside: Adjusting equipment maintenance intervals

Company
Woodside
Country
Australia
Adoption stage
Limited operation
Source published
Date basis
The date the source was published. It can differ from the date adoption started.
How the source was checked
Read the full source text

The work problem

Woodside treats high reliability as the basis of operations, and deciding when to carry out maintenance is at the heart of it. Doing preventive maintenance earlier than needed piles up unnecessary work, while doing it late increases risk. As the North West Shelf assets moved past the production plateau into the next stage, the company had to hold performance while also keeping cost competitiveness.

Technology and data

Woodside brought a tool called Maint Intel into the North West Shelf project. It uses AI to analyse maintenance records and identify equipment failure modes. Those results go into advanced statistical models that recommend the optimal maintenance interval. The recommendation comes from matching large volumes of data, maintenance plans and past performance against the company's reliability targets. The tool was built by Woodside's Digital team together with Amazon Web Services in India. The tool does not change the schedule itself; it goes as far as recommending the optimal maintenance interval.

Results

Woodside said it first trialled and validated the tool on the offshore Angel platform. It said extension to other assets was scheduled for the same year. It said that working together, the Digital team and AWS AI specialists in India cut model processing time from five days to under two hours. The company explained that unnecessary work fell sharply, freeing the team's time for other important work.

Limits and open questions

What was reduced is the time to run the model. Figures for maintenance cost or failure rate reduction, and who approves the recommendation, do not appear in the source.

Sources

Compiled from public sources. These are not results from ATF Works customers.

Read original (opens in a new tab)