385398 Optimal Short-Term Scheduling of Turnarounds in an Integrated Site

Thursday, November 20, 2014: 1:12 PM
406 - 407 (Hilton Atlanta)
Tong Zhang1, Satyajith Amaran2, Nick Sahinidis2, Bikram Sharda3 and Scott J. Bury4, (1)Carnegie Mellon University, Pittsburgh, PA, (2)Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, (3)The Dow Chemical Company, Freeport, TX, (4)The Dow Chemical Company, Midland, MI

Integrated sites involve material flow in process networks. The disruption of flow due to planned maintenance turnarounds on some process units affects production rates in both upstream as well as downstream units. Due to this, long-term maintenance planning often recommends the alignment of a subset of the turnarounds around the same time in order to make use of synergistic effects.

In this paper, we consider a short-term maintenance scheduling setting, where we focus on a time scale of a few months within which a number of turnarounds are scheduled to take place. A major concern during the time leading up to a set of turnarounds is the planning for inventory build-up in anticipation of a turnaround, so as to try and maintain normal operation and satisfy demands during these long outages. Another issue is the allocation of maintenance manpower among various subtasks, which is a scarce resource that has been negotiated for months in advance.

The goal of this work is to provide an optimization formulation that will take into account operational level detail and suggest optimal maintenance schedules of these units while negotiating resource constraints, within a time interval that spans the recommended maintenance durations of a subset of the production units. In particular, we study the short-term scheduling of detailed maintenance tasks and subtasks, ramping up and down of unit production, allocation of available maintenance manpower, use of intermediate storage, and the effect on material flow in the entire site network. Not only maintenance task and manpower work schedules, but also site-wide short-term production plans and inventory policy decisions fall out of the optimization framework. We use an industrial-size site network example to illustrate the results.


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