Equipment Health & Maintenance

Australia’s leading natural gas producer announced an ambitious target of increasing operational efficiencies by 30% over the next three years to its investors. To work towards this target, the customer, headquartered in Perth, is strongly leveraging digitization and automation with AWS services to find the right balance between production and equipment maintenance strategies, in an effort to decrease costs and increase labor productivity.

Specifically, the customer launched a Condition-Based Maintenance Project targeting 1,500 cooling fans in an LNG processing facility to improve equipment visibility for analysis, troubleshooting, and maintenance. Previously, equipment condition data was manually collected only every 3 months and analyzed by a mix of machine and person; the average maintenance work time was 80 days. Since migrating to the AWS Cloud, the company developed and implemented sensors to transmit site equipment data to the cloud, built customized machine-learning models to perform continuous analysis on data in production, and automated the work planning process. The Condition-Based Maintenance Project, has resulted in the following benefits for the customer:

• Cooling fans equipment field data is captured every 15 minutes to provide near real-time monitoring
• The average work planning process has reduced from 80 days to one day
• Templated, automated steps and responses vs. building artifacts and work orders from scratch
• An 80% reduction in inspection costs