Introduction to Integrity Operating Windows
Integrity Operating Windows (IOWs) and Reliability Operating Windows (ROWs) provide safe operating ranges for various process variables within asset-intensive process facilities. If equipment were operated according to design there would be fewer leaks and reliability issues. Unfortunately, that scenario is not realistic, and things do go “bump in the night.” IOWs and ROWs let operators know when conditions are outside of safe and reliable operating boundaries, i.e., when equipment is being damaged and at what rate). Said damage to equipment could lead to loss of containment and/or loss of functionality.
What Are Integrity Operating Windows?
Integrity Operating Windows (IOWs) are limits and ranges placed on key process variables to make sure equipment integrity and safe operations are maintained. Should the process operation deviate from these established limits for a predetermined amount of time, the integrity of the operational assets can be compromised. However, maintaining assets within prescribed operating conditions reduces the risk of early failure by preventing acceleration of asset degradation and unplanned loss of containment. In addition, there will be certain parameters that cannot be re-adjusted, for example crude feed or sulfur content, but it is just as important to know the degradation rates and plan for inspection, repairs or replacement in a timely manner or change operating conditions, such as pressure or temperature, etc.
What are Reliability Operating Windows?
Reliability Operating Windows (ROWs) are identified parameters placed on a process operation. To set the ROW parameters, acceptable operating ranges are defined. These operating ranges do not lead to a loss of primary containment (LOPC) event but do affect equipment reliability. Examples include corroding a vortex breaker, or a pump impeller, or consuming trays in a tower—immediately affecting mass transfer efficiencies, power draw on a compressor, flow velocities, etc. These situations lead to loss profit opportunity and, eventually, failure of the parts, which leads to repairs and sometimes loss of containment.
Challenges Associated with Managing IOWs and ROWs
Some of the challenges the industry faces with monitoring operating windows involve having the right data and being able to appropriately analyze it. First, industry is challenged in “pulling it all together.” Gathering data needed for effective and timely decision making is challenging, as this data may come from disparate sources (e.g. instrumentation on equipment, gauge readings, results of laboratory tests, manual tests on equipment such as voltage readings on anode beds, etc.). Secondly, having the capability to appropriately analyze the data is important to minimize false alarms.
What Does the Future of Reliability Look Like?
Advancements in data acquisition, warehousing, modeling, and analytics are now opening the door for the next leap in reliability analysis. These capabilities allow greater reliability improvements, combined with decreased total maintenance and inspection spend.
This leap is being made possible through Quantitative Reliability Optimization (QRO). QRO is an approach to reliability modeling which connects every relevant reliability data point at a complex facility to one integrated model, allowing for near real-time complex decision making.
Ideally, a facility wants neither too few or too many IOWs and ROWs. QRO uses the latest in analytical data science, automated learning, and digital technology to optimize operating windows. It also takes a holistic look at which data needs to be watched and defines the actions needed when ROW and IOW boundaries are breached for specified time periods. On top of that, it’s logic and functionality helps in managing and analyzing data to limit false alarms.
In regard to operating windows, QRO allows users to do things like:
- Drive effective economic decisions in the event of reliability based operating excursions.
- Minimize unplanned downtime.
- Be better prepared for turnarounds (less discovery work, as conditions will be anticipated and work can be planned well in advance of the shutdown).
- Minimize or eliminate LOPCs.
- Fully digitize content currently contained in corrosion control documents so that these parameters are automatically evergreened.
Learn more about Quantitative Reliability Optimization (QRO).