Assess the effects of different operations policies on warehousing reliability

King Lun Tommy Choy, N. Sheng, H. Y. Lam, Ivan K.W. Lai, K. H. Chow, G. T.S. Ho

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)


In this study, an assessment model for analysing the reliability of a warehouse system, focusing on resource capability, under given combinations of storage, routing, batching and zoning process policies, is proposed. A reliability assessment model is developed in order to evaluate the effect of different combinations of operations policies on warehouse reliability. To better reflect the real order pick up operations at the warehouse, a simulation model based on the operation scenarios of a Hong Kong logistics service company is developed. The simulation results are used for supporting the evaluation of warehouse reliability through using the proposed reliability assessment model. The most important finding indicates that order batching together with zoning policies yields greater warehouse reliability particularly when the daily order volume is large. In addition, another important research finding shows that warehouse performance is not constant and can drop when certain combinations of operations policies are adopted. The degrading rate of the resource (forklift) when used according to a given combination of polices is also defined by the proposed assessment method. Hence, the result helps logistics service providers enhance resource durability through modifying operations policies and by implementing proper preventive maintenance policies within a dynamic operations environment.
Original languageEnglish
Pages (from-to)662-678
Number of pages17
JournalInternational Journal of Production Research
Issue number3
Publication statusPublished - 1 Feb 2014


  • order picking policy
  • reliability
  • resource-based view
  • routing policy
  • storage policy
  • warehouse operations

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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