(428d) An Agent-Based Simulation Model Towards Mitigating Domino Effects of Maritime Disruptions in LNG Supply Chains

Logistics is central in ensuring the uninterrupted functioning of supply chains (SC), enabling the transport of commodities from the suppliers to the various end customers. Maritime trade has evolved to serve as the backbone of logistics allowing for a globalized market through augmented SC linkages and timely delivery of products over long distances. Marine trade handles approximately 80% of global merchandise by volume (United Nations Conference on Trade and Development, 2021) owing to its sheer cargo-handling capacity and fleet size, which is the highest compared to any mode of transport utilized for the shipment of goods. Though it offers better interconnectivity among different SC entities and promotes economic interdependency, vulnerabilities do exist in maritime trade that can eventually manifest to disrupt normal SC operations. While perturbations can occur at any segment of the SC (for example, supply uncertainty due to political crisis at the export facility and operational and maintenance issues at the import facility), the transportation segment in itself has faced critical disruptions sending large supply shocks, the consequence (or impact) of which propagates as domino effects downstream across the SC causing significant economic downfalls along with damaging organizational reputations. Hence, it becomes essential to study the effect of supply shocks induced in SCs due to maritime logistic disruptions.

Maritime trade is susceptible to accidents or delays induced by turbulent weather conditions, piracy, terror attacks, and other human errors. It is understood that while weather-induced delays temporarily hamper normal operations, disruptions due to accidents or piracy can either result in delay or complete loss of shipment along with associated safety concerns. There have been several instances of marine disruptions, with the most recent being induced due to the CoVID-19 pandemic. In October 2021, container ships were seen maneuvering a few miles offshore in holding mode, unable to offload shipment at the stipulated time in Port of Los Angeles, California. This SC gridlock was attributed to a sudden surge in demand; however, an inadequate workforce at the port resulted in almost 200,000 shipping containers stationed off-coast over a span of a week (California Gridlock, October 2021). Additionally, global marine trade has a number of critical chokepoints, such as the Strait of Panama, Suez, and Malacca (US EIA Maritime Chokepoints, 2017) that can potentially disrupt supply chains. Recent examples of such disruptions include the Suez Canal Crisis in early 2021 due to Ever-Given blocking the narrow strait for about a week, making about 400 other shipments (oil tankers, gas carriers, container ships) to either wait in queue for clearance, or reroute around Cape of Good Hope taking up a more circuitous route. This compounded global SC woes already constrained due to the pandemic and resulted in a loss of around $95 million in revenue to the canal authorities, apart from inflicting about $54 billion in losses to global trade (Suez Canal nightmare, 2021). Further, cyclone Shaheen impacted the export of oil and gas from Oman and Qatar during its passage along the strait of Hormuz (Saadi and Anupam, 2021). The aforementioned real-world examples motivate us to develop mitigative strategies that can enhance SC resilience. Specifically, we consider LNG SC, given its potential to serve in global energy transitions being a low-carbon fossil. Further, with almost 73% of global LNG demand arising from the Asia-Pacific region (GIIGNL Annual Report, 2022), it is of greater importance to enhance resilience and improve energy security for Asian regions having higher import dependencies. Hence, the objective of this work is to study and quantify the impact of unplanned events (disruptions) in maritime transport and the associated shock propagation across an LNG receiving terminal. This further encourages to design appropriate countermeasures that help alleviate its adverse consequences.

From the perspective of an LNG importer, the LNG supply chain (LNG SC) comprises NG liquefaction, LNG shipment, storage & regasification, and distribution. Here, we develop an agent-based dynamic simulation model of the LNG supply chain that emulates the different participating entities like LNG suppliers (exporter), LNG carriers, receiving terminals (importer), end-customers (for example, regasified LNG, retail LNG, and reloading LNG). All entities and their internal departments are modeled as autonomous actors that are capable of making their own decisions. Each actor coordinates with one another and seeks to maximize their individualistic objectives. Several hazards that can potentially hamper normal operations were identified using the HAZOP technique and appropriate recovery options were proposed to be utilized during disruptive events. A number of countermeasures involving strategic safeguards, tactical planning, and operational policy-based decisions were considered depending on the severity and duration of the disruptive event. The dynamics of disruptions were initiated as stochastic factors affecting the normal SC dynamics through the activities of the respective agents, and the associated cascading impacts and emergent phenomena were analyzed.

In order to assess the impacts of disruptions, a case study involving maritime transportation delays of LNG carriers in transit was conducted for different delay magnitudes and durations. Due to the diverse operational decisions and management, an annual simulation horizon was considered with hourly operational time steps. In this case, the delay was introduced around the mean carrier transit duration, i.e., with a positive standard deviation of +3.5 days (high severity) and a duration lasting maximum for a month. It was observed to have significant impacts on the operations of the receiving terminal, specifically facing demurrage penalties due to increased waiting time of LNG carriers that have arrived for unloading. Additionally, delays in carrier arrival resulted in frequent plant shutdowns due to inventory shortfalls as a result of delayed replenishments. This eventually leads to reduced product send-outs, negatively impacting customer service quality. It is noted that a combination of the aforementioned domino effects amounted to a $350 million loss for the receiving terminal. We implemented feedback-control-based recovery actions (e.g., LNG emergency sourcing or spot procurement) that can minimize the losses due to the cascading effects of maritime disruption. Through this, we were able to achieve a recovery of around 70% due to the reduction in plant shutdown duration without the requirement of any policy intervention. The developed agent-based model of the LNG supply chain has been implemented in AnyLogic, a business simulation tool with a realistic case study involving a real-world operational facility of a specific company based in India. We believe in its capability to serve as a robust decision support tool that helps evaluate and quantify the impacts of a variety of disruptions and also analyze the effectiveness of adopted countermeasures towards enhancing supply chain resilience.

Keywords: LNG Supply Chain, maritime disruptions, domino effects, countermeasures, enhancing resilience, decision support tool

References

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