Optimal Decision Rules for Product Recalls

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MATHEMATICS OF OPERATIONS RESEARCH, vol.37, no.3, pp.399-418, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 3
  • Publication Date: 2012
  • Doi Number: 10.1287/moor.1120.0545
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.399-418
  • Keywords: product recalls, quality risk, supply chain risk, optimal stopping, stochastic optimal control, point processes, filtration shrinkage, sequential analysis, dynamic programming, Bayesian analysis
  • Middle East Technical University Affiliated: Yes


We consider a hypothetical company that is assumed to have just manufactured and sold a number of copies of a product. It is known that, with a small probability, the company has committed a manufacturing fault that will require a recall. The company is able to observe the expiration times of the sold items whose distribution depends on whether the fault is present or absent. At the expiration of each item, a public inspection takes place that may reveal the fault, if it exists. Based on this information, the company can recall the product at any moment and pay back each customer the price of the product. If the company is not able to recall before an inspection reveals the fault, it pays a fine per item sold, which is assumed to be much larger than the price of the product. We compute the Optimal recall time that minimizes the expected cost of recall of this company. We then derive and solve a stationary limit recall problem and show that the original problem converges to it as the number of items initially sold increases to infinity. Finally, we propose two extensions of the original model and compute the optimal recall times for these. In the first extension, the expired items are inspected only if they expire earlier than expected; in the second extension, the company is able to conduct internal/private inspections on the expired items. We provide numerical examples and simulation results for all three models.