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Medium-term maintenance turnaround planning under uncertainty for integrated chemical sites
Affiliation:1. Department of Chemical Engineering, Carnegie Melon University, Pittsburgh, PA 15232, United States;2. Business and Supply Chain Optimization, Linde.digital, Linde plc, Tonawanda, NY 14150, United States;1. Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213 United States;2. Smart Operations, Linde plc., Tonawanda, NY 14150 United States;1. Department of Production Engineering, Federal University of Pernambuco, Brazil;3. COMPESA, Companhia Pernambucana de Saneamento, Brazil
Abstract: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.
Keywords:Maintenance scheduling  Mixed-integer linear programming  Uncertainty  Stochastic programming  Robust optimization
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