Medium-term maintenance turnaround planning under uncertainty for integrated chemical sites

被引:23
作者
Amaran, Satyajith [1 ,2 ]
Zhang, Tong [1 ]
Sahinidis, Nikolaos V. [1 ]
Sharda, Bikram [2 ]
Bury, Scott J. [2 ]
机构
[1] Carnegie Mellon Univ, Dept Chem Engn, Pittsburgh, PA 15213 USA
[2] Dow Chem Co USA, Core R&D, Engn Sci, Proc Optimizat, Midland, MI 48674 USA
关键词
Maintenance scheduling; Mixed integer linear programming; Uncertainty; Stochastic programming; Robust optimization; OPTIMIZATION;
D O I
10.1016/j.compchemeng.2015.09.007
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Plant maintenance poses extended disruptions to production. Maintenance effects are amplified when the plant is part of an integrated chemical site, as production levels of adjacent plants in the site are also significantly influenced. A challenge in dealing with turnarounds is the difficulty in predicting their duration, due to discovery work and delays. This uncertainty in duration affects two major planning decisions: production levels and maintenance manpower allocation. The latter must be decided several months before the turnarounds occur. We address the scheduling of a set of plant turnarounds over a medium-term of several months using integer programming formulations. Due to the nature of uncertainty, production decisions are treated through stochastic programming ideas, while the manpower aspect is handled through a robust optimization framework. We propose combined robust optimization and stochastic programming formulations to address the problem and demonstrate, through an industrial case study, the potential for significant savings. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:422 / 433
页数:12
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