Systematic incorporation of inherent safety in hazardous chemicals supply chain optimization

Abstract Increasing globalization has made many chemical supply chains large, interdependent and complex. Process incidents often affect the reliability of a supply chain and can cause large disruptions at different segments of the industry. We propose an optimization-based framework that systematically takes into account the trade-offs between process safety and supply chain economics for decision-making. We quantify the hazard at various supply chain echelons in the form of a safety index that takes both fire and toxic hazards into account. A mixed-integer nonlinear programming (MINLP)-based model is developed to either maximize profit for specified hazard limits, or to minimize hazard in a supply chain with multiple production plants, technological options, warehouses and distribution nodes. The MINLP model is used to generate trade-off optimal solutions for various toxic and fire hazard limits. The framework is demonstrated by applying it to an end-to-end ammonia supply chain case study which resulted in several non-intuitive observations regarding hazardous supply chain design and optimization.

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