Amanda J. Schmitt

OR/MS Models for Supply Chain Disruptions: A Review

ABSTRACT We review the Operations Research/Management Science (OR/MS) literature on supply chain disruptions in order to take stock of the research to date and to provide an overview of the research questions that have been addressed. We first place disruptions in the context of other forms of supply uncertainty and discuss common modeling approaches. We then discuss 180 scholarly works on the topic, organized into six categories: evaluating supply disruptions; strategic decisions; sourcing decisions; contracts and incentives; inventory; and facility location. We conclude with a discussion of future research directions.

A Quantitative Analysis of Disruption Risk in a Multi-Echelon Supply Chain

We demonstrate how system resilience can be improved by focusing on a supply chain network as a whole. We analyze inventory placement and back-up methodologies in a multi-echelon network and view their effect on reducing supply chain risk. We focus on risk from both supply disruptions and demand uncertainty and compare their impacts and mitigating strategies. A simulation model developed to capture an actual network for a consumer packaged goods company is used for the analysis. We present analysis and insights for multi-echelon networks and show how network utilization and proactive planning enable reductions in supply chain disruption impact.

Infinite-Horizon Models for Inventory Control under Yield Uncertainty and Disruptions

We consider a firm facing supply chain risk in two forms: disruptions and yield uncertainty. We demonstrate the importance of analyzing a sufficiently long time horizon when modeling inventory systems subject to supply disruptions. Several previous papers have used single-period newsboy-style models to study supply disruptions, and we show that such models underestimate the risk of supply disruptions and generate sub-optimal solutions. We consider one case where a firms only sourcing option is an unreliable supplier subject to disruptions and yield uncertainty, and a second case where a second, reliable (but more expensive) supplier is available. We develop models for both cases to determine the optimal order and reserve quantities. We then compare these results to those found when a single-period approximation is used. We demonstrate that a single-period approximation causes increases in cost, under-utilizes the unreliable supplier, and distorts the order quantities that should be placed with the reliable supplier in the two-supplier case. Moreover, using a single-period model can lead to selecting the wrong strategy for mitigating supply risk.

Quantifying supply chain disruption risk using Monte Carlo and discrete-event simulation

We present a model constructed for a large consumer products company to assess their vulnerability to disruption risk and quantify its impact on customer service. Risk profiles for the locations and connections in the supply chain are developed using Monte Carlo simulation, and the flow of material and network interactions are modeled using discrete-event simulation. Capturing both the risk profiles and material flow with simulation allows for a clear view of the impact of disruptions on the system. We also model various strategies for coping with the risk in the system in order to maintain product availability to the customer. We discuss the dynamic nature of risk in the network and the importance of proactive planning to mitigate and recover from disruptions.

Sourcing Strategies to Manage Supply Disruptions

Supplier diversification and backup sourcing offer alternatives to stockpiling inventory as a means of mitigating disruption risks. In this chapter, we introduce some simple models to analyze and explore the performance of these sourcing strategies. The effectiveness of diversification depends largely on the number of suppliers, the possibility of disruption correlation, and the available spare capacity at suppliers. Most of the benefits are achieved with a small number of suppliers. The effectiveness of backup sourcing depends largely on the cost and availability of the backup source, with availability being measured as response time and capacity provided. When choosing the appropriate strategy, managers need to account for all the significant factors that influence performance, including the disruption profile, inventory costs, the fixed and variable supplier costs, capacities, response times, and disruption correlation. Crafting the best strategy relies on sound judgment aligned with suitable analysis.

Modeling and simulating supply chain schedule risk

We investigate an aerospace supply chain that is subject to various types of risks in this research. Discrete-event simulation technique is used to model the flow of product and risk factors such as potential supply chain disruptions or quality issues. The underlying goal of the model is to analyze the supply chain performance under various risk scenarios and gather insights. The validity and practical relevance of the results is emphasized as the company is using the model not only for planning, but also for execution and general project management.