431990 Flexible Turnaround Planning in Integrated Chemical Site Networks

Thursday, November 12, 2015: 5:21 PM
Salon F (Salt Lake Marriott Downtown at City Creek)
Sreekanth Rajagopalan1, Nick Sahinidis2, Bikram Sharda3, Satyajith Amaran3 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

An integrated chemical site is a network of plants interacting with each other.  Each plant fulfills one or more roles in the network producing raw materials, intermediates, and/or producing to external markets. The plants or sites are typically grouped based on specific business envelopes, but may interface across multiple businesses, envelopes or even other sites. Though each plant or envelope runs its own preferred routine and preventive maintenance over short time horizons, planning and coordinating large-scale preventive maintenance tasks across the entire integration network has significant potential benefits.

Amaran et al. [1] demonstrated long-term (1-5 years) turnaround planning for continuous processes by modeling a rolling horizon maintenance scheme as a mixed integer linear programming (MILP) problem. The benefits include long term productivity improvements across the network, lower peak manpower utilization, novel schedules that consider practical limitations like contract-based manpower, availability and other seasonal constraints. Amaran et al. [2] captured uncertainties in turnaround duration and its effect on manpower allocation, production planning and downstream inventory build-up prior to turnarounds. This was demonstrated in a medium-term (6-12 months) planning framework with a combination of robust optimization and multi-stage stochastic programming. This helped to refine grouped turnaround schedules from the long-term planning model.

This paper addresses a methodology of how to make adjustments to an existing turnaround plan in order to respond to unexpected changes in the system over a short and medium-term horizon, such as rapidly changing market conditions, manpower availability, variability in production rates over time, and unplanned outages. In practice, plants are constantly monitored as the processes and markets change with time. The states of the systems may diverge more than that anticipated at the time of the original turnaround planning. For example, a plant may maintain high catalyst activity longer than usual and the rescheduling of an upcoming turnaround may have the highest economic benefit for that individual plant, but other plants in the network may actually be impacted by a delayed turnaround. In another scenario, the demand for products and market prices for raw materials could change sufficiently to prompt ramp-up in production. The converse market conditions would prompt a ramp-down in production and also change turnaround economics. Therefore, the capability to evaluate flexibility in the turnaround schedule is needed.

However, re-planning the turnaround schedule in response to endogenous and exogenous factors brings about risks. Mathematical programming techniques naturally lend themselves to understanding the trade-off of these risks with both impacts on site integration and the possibility of replenishing production through turnaround investments. In this work, we rely primarily on a decision-rule based approach to incorporate flexibility in rescheduling a turnaround. At each intermediate time period, a decision as to whether to (i) continue operation, or (ii) perform a “pit-stop” turnaround, or (iii) perform a full turnaround is sought based on the associated risk of loss. Each task has its own associated costs, benefits, resources and probabilities of occurrence.

We propose a flexible turnaround framework that assesses the sensitivity of turnaround schedules, justifies and supplements site-wide approximations in long-term and medium-term models, and offers a holistic framework for maintenance and turnaround planning in integrated chemical sites. The methodology is demonstrated through a case study on a large example site network.


  1. Amaran, S., N. V. Sahinidis, B. Sharda, M. Morrison, S. J. Bury, S. Miller and J. M. Wassick, Long-term turnaround planning for integrated chemical sites, Computers and Chemical Engineering, 72, 145-158, 2015.
  2. Amaran, S., T. Zhang, N. V. Sahinidis, B. Sharda and S. J. Bury, Medium-term maintenance turnaround planning under uncertainty for integrated chemical sites, Computers and Chemical Engineering, submitted, 2015.

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