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Statistically monitoring inventory accuracy in large warehouse and retail environments

Master of Science / Department of Industrial & Manufacturing Systems Engineering / John English / This research builds upon previous efforts to explore the use of Statistical Process Control (SPC) in lieu of cycle counting. Specifically a three pronged effort is developed. First, in the work of Huschka (2009) and Miller (2008), a mixture distribution is proposed to model the complexities of multiple Stock Keeping Units (SKU) within an operating department. We have gained access to data set from a large retailer and have analyzed the data in an effort to validate the core models. Secondly, we develop a recursive relationship that enables large samples of SKUs to be evaluated with appropriately with the SPC approach. Finally, we present a comprehensive set of type I and type II error rates for the SPC approach to inventory accuracy monitoring.

Identiferoai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/13157
Date January 1900
CreatorsHuschka, Andrew
PublisherKansas State University
Source SetsK-State Research Exchange
Languageen_US
Detected LanguageEnglish
TypeThesis

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