Utilizing Quantitative Reliability Optimization to Better Drive Facility-Wide Reliability and Maintenance Budgets
Inspectioneering Journal, May/June 2021 Issue
Current reliability methodologies such as risk-based inspection (RBI), reliability-centered maintenance (RCM), and reliability availability maintainability (RAM) have helped the industry make great advances in managing reliability. While proper deployment of these methodologies adds ample value, reliability and operational leaders today still struggle to objectively answer macro- level reliability questions across their facilities. For example, how can facility leaders defend their maintenance and reliability budgets going into the next fiscal year? How can leaders decide which areas of their budget to adjust when asked to reduce their spending across their operations? These budgets are comprised of smaller reliability programs and budgets ranging from predictive maintenance to fixed equipment inspection, and therefore making objective decisions in how to make a broad reduction challenging and arduous even with the best methodologies.
Quantitative Reliability Optimization (QRO) is an approach that enables reliability and operations leaders to make smarter and more confident reliability decisions for their facilities. This approach both evolves and integrates the best elements of current models and methodologies while introducing novel analysis concepts to quantitatively balance process safety availability targets with maintenance and reliability investments. QRO takes large volumes of reliability and economic data, analyzes system reliability performance using cutting-edge data science, and delivers continually optimized reliability plans.
In this article, we’ll discuss how QRO is the industry’s next step in reliability by looking at three industry challenges and how QRO addresses them:
- Identifying failure modes across different asset and failure types
- Quantifying the failure curve
- Connecting individual assets to facility performance and driving better plans
Identifying Failure Modes
Meet the Authors
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