Advanced Prognostics and Maintenance Optimization Methodologies for System Health Management

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For engineering systems such as oil and gas systems, pipeline systems and renewable energy systems, it is critical to ensure their reliability and reduce the overall cost so as to enhance system competitiveness, ensure safety, increase profits and protect the environment. Prognostics and health management (PHM) aims to improve system reliability and reduce operating and maintenance costs based on system health conditions. Under the PHM framework, prognostics approaches are utilized to predict equipment future health conditions and failure times. Maintenance activities can be optimized based on the predicted failure time to achieve improved reliability and minimized life-cycle cost. With the capability to focus on unit-specific health condition information, PHM presents great potential to significantly improve the reliability and reduce the overall cost. Significant advances are needed in prognostics and maintenance optimization for achieving effective PHM programs. The objective of the proposed research program is to develop accurate and efficient advanced prognostics and maintenance optimization methods and tools to support effective PHM programs, and apply them to engineering systems particularly oil and gas, renewable energy, and transportation systems. In the proposed program, we plan to develop accurate integrated prognostics methods by leveraging physical models and various condition monitoring data, prognostics methods based on deep learning tools, and efficient and accurate condition-based maintenance (CBM) optimization methods for complex systems. Their applications to rotating equipment, particularly gearboxes, and pipelines will be investigated. The proposed research program is expected to result in effective methods and tools for accurate equipment health condition and remaining useful life prediction, efficient maintenance optimization, and the capability to deal with complex equipment and systems. The results from this research will contribute to achieving highly reliable, safe and cost-effective engineering systems, and will generate major benefits for Canadian oil and gas, renewable energy, transportation, manufacturing and aerospace industries. Highly qualified personnel will be trained.