: About the Author
Pinnacle
Headquartered in Pasadena, Texas, Pinnacle is exclusively focused on helping industrial facilities in the oil and gas, chemical, mining, and water and wastewater industries better leverage their data to improve reliability performance, resulting in increased production, optimized reliability and maintenance spend, and improved process safety and environmental impact.
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Published Articles
Embracing technology alone isn't the answer in industry problem-solving. A synergy of data-driven approaches and human expertise unlocks true potential.
By optimizing the scarce SME resource time and focusing their efforts, SMEs can spend time on the things that are most important, such as why a problem occurs, as well as identifying possible solutions to problems.
An approach such as LVC can help enhance API 581 POF calculations for thinning. This method has proven to increase accuracy, precision, and has the flexibility to handle one-off cases that are handled manually today.
The addition of data science into traditional reliability methods allows models to evolve continually and learn, preventing results from becoming stagnant.
This blog will dive into the “next steps” of maximizing RBI programs, specifically how to better quantify the value of inspections and improve inspection handling.
This improved data can help us better predict failure, plan inspections in terms of time and coverage, and identify when inspections aren’t necessarily the right solution for mitigation.
The results of the analysis demonstrate the exciting possibilities for how “Big Data” can be used to empower the reliability and corrosion engineer to solve real-world reliability challenges faster and more accurately than current industry practices.
Acting as a reliability twin, QRO is a new dynamic reliability approach that bridges existing first principles-based reliability models with advanced data science principles and system-based optimization to drive improved facility performance.
While collecting more data may seem like the solution, the key to successfully forecasting system availability is building a strong program based on existing data. This can be accomplished through Quantitative Reliability Optimization (QRO).
As the industry continues to collect more data, many facilities are unable to confidently leverage it to drive better reliability decisions because they do not collect the correct type or amount of data, which leads to unknown risks.
Decision makers are being asked to reduce cost while maintaining reliable operations. While it can be difficult to easily identify areas to reduce budget and resources, there are a variety of cost reduction opportunities available.
Here is four-step process for developing effective and efficient piping management strategies that can help optimize costs, refocus resources, and reduce risk.
This blog will walk through practical steps for managing IOWS and will demonstrate what successful IOW management can look like.
