Data and analytics silos in industrial organisations, such as energy producers, arise due to technological and business processes performed by decentralised business units. However, the creation of dynamic risk models requires a seamless analysis cycle incorporating operational reliability model outputs into evaluations of maintenance planning and, in turn, refining reliability estimates using maintenance activities. Such dynamic risk models provide major benefits to risk management and cost-effective maintenance in asset intensive industries, with improved maintenance strategies leading to 5-30 percent reductions in total maintenance costs, according to various sources.
The FEnEx CRC Project 21.RP3.0106 (Asset Reliability and Risk Interoperability to Optimise Maintenance Execution and Improve Risk Management of Energy Producers) developed an initial framework to bridge siloed reliability and risk models and perform maintenance planning optimisation using dynamic risk analyses. Challenges remain in areas of scalability (e.g., an entire facility and its equipment, not only major systems) and the availability of reliability data for all included equipment.
This project aims to address these challenges to better support dynamic risk models based on changing operational parameters. It will develop an enhanced ARRI framework and maintenance optimisation approach incorporating desired risk elements. It will investigate means to alleviate the lack of reliability data needed for dynamic risk-based analyses. Scalability will be demonstrated by application of work order prioritisation to a large facility. Leveraging dynamic risk models is expected to result in improved risk management capabilities and maintenance efficiencies, aiming for 5%-10% reduction in total maintenance costs.
Partners: Adelaide University, INPEX Holdings Australia Pty Ltd
Project Leader: Prof. Markus Stumptner
Duration: 2 years