Factoring probabilistic evaluations in traditionally qualitative multi-attribute decisions, such as plant turnarounds

April 17, 2024 8:30am - April 17, 2024 9:15am

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Co-Presenting: Luis Mendoza (Decision Frameworks), Ellen Coopersmith & Ashley Corso (Decision Frameworks)

Abstract:

What is the true cost of a plant turnaround? How can we better inform our decision when selecting a plant turnaround strategy?

Plant turnarounds are scheduled plant shutdowns in which preventive maintenance and equipment upgrades are conducted in order to ensure safe and compliant operation, improve competitiveness, etc. Teams are often tasked to think strategically about which improvements, beyond the required maintenance, will better position the company to gain competitive advantage and thrive in changing market conditions. However, this strategic thinking often focuses on qualitative multi-attribute analysis to reach consensus and ignores probabilistic quantitative evaluations to better illustrate the trade-offs between competing strategies.

The cost of the turnaround involves the operating cost of executing the maintenance itself and unplanned (surprise) fixes that only become apparent when the plant/factory is shutdown, as well as the capital cost of equipment replacements and upgrades. Furthermore, a significant cost is in the disruption of operations and loss of profits during the shutdown as well as the degradation in operating efficiency over time between turnarounds.

Multi-attribute analysis is an important tool in framing compelling alternatives and assessing them qualitatively. This paper/presentation focuses on the value to be gained by enhancing traditionally qualitative decisions with quantitative analysis using a simple model with well-defined uncertainties and decisions and iterating the permutations using decision analysis software to gain insight into the quantifiable trade-offs.