Managing disruptions in a refinery supply chain using agent-based technique

Abstract

With growing competition in the economy and concomitant business trends such as globalization, single sourcing, outsourcing, and centralized distribution, supply chain networks are increasingly becoming more complex and vulnerable to disruptions. Disruptions can have significant impact on the economics and the operability of any company, therefore timely and adequate response is essential for supply chain resilience. This is a complex problem where the suddenness of changes, short response times and resource constraints limit the flexibility availability for integrated decision-making. In this work, we present a structured model-based framework and a generic decision support approach for managing abnormal situations in supply chains. The proposed approach involves an agent-based disruption management system and a separate supply chain simulation. The main challenges in disruption management are disruption detection, their diagnosis, seeking rectifications, optimization of rectification options and implementation of corrective actions. DMS employs two methods for controlling disruptions, namely feedback and feedforward. The variety of case studies shows that both control methods are important for handling disruptions in a supply chain. This framework is implemented for a refinery supply chain using case studies based on crude transportation disruption, product demand fluctuation disruptions, crude quality disruptions and operation facility disruptions.