Using statistical process control to monitor inventory accuracy

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dc.contributor.author Huschka, Kyle
dc.date.accessioned 2009-05-12T18:44:00Z
dc.date.available 2009-05-12T18:44:00Z
dc.date.issued 2009-05-12T18:44:00Z
dc.identifier.uri http://hdl.handle.net/2097/1407
dc.description.abstract Inventory accuracy is critical for almost all industrial environments such as distribution, warehousing, and retail. It is quite common for companies with exceptional inventory accuracy to use a technique called cycle counting. For many organizations, the time and resources to complete cycle counting are limited or not available. In this work, we promote statistical process control (SPC) to monitor inventory accuracy. Specifically, we model the complex underlying environments with mixture distributions to demonstrate sampling from a mixed but stationary process. For our particular application, we concern ourselves with data that result from inventory adjustments at the stock keeping unit (SKU) level when a given SKU is found to be inaccurate. We provide estimates of both the Type I and Type II errors when a classic c chart is used. In these estimations, we use both analytical as well as simulation results, and the findings demonstrate the environments that might be conducive for SPC approaches. en
dc.language.iso en_US en
dc.publisher Kansas State University en
dc.subject SPC en
dc.subject Inventory en
dc.title Using statistical process control to monitor inventory accuracy en
dc.type Thesis en
dc.description.degree Master of Science en
dc.description.level Masters en
dc.description.department Department of Industrial & Manufacturing Systems Engineering en
dc.description.advisor John R. English en
dc.subject.umi Engineering, Industrial (0546) en
dc.date.published 2009 en
dc.date.graduationmonth May en


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