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Stochastic comparisons in production yield management

Research output: Contribution to journalArticlepeer-review

Abstract

Manufacturing firms routinely commit resources to increase yield rates through product- and process-improvement initiatives. Champions of such yield-improvement projects may assume that stochastically larger yield rates are beneficial. In this note, we show that this need not hold, even when the contingent production lot sizes are chosen optimally. We employ stochastic comparison techniques to show that a yield rate that is smaller in the convex order ensures higher expected profit, and we provide a distribution-free bound on the size of increase in expected profit. We also identify properties of yield-rate distributions that do make stochastically larger yield rates beneficial.

Original languageEnglish (US)
Pages (from-to)377-384
Number of pages8
JournalOperations research
Volume53
Issue number2
DOIs
StatePublished - Mar 2005

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Random yield
  • Stochastic order relations

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