ORDER PICKING OPTIMIZATION

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World-Class Warehousing and Material Handling

■ ■ Weight ■ ■ Units per carton ■ ■ Cartons per pallet ■ ■ Base unit of measure

This information should be readily available from the product or item master file. Just the process of evaluating the accuracy and availability of the data is helpful as a data-integrity audit. For each customer order, we need the customer ID, the unique items requested on the order and the quantities of each, and order date and time. This information should be available from the sales and/or order-history file. The sample size required depends heavily on the seasonality of the industry. If there are large annual surges of demand, such as in the mail order and retailing industries, then a 12-month sample is necessary. If the demand is fairly stable over the course of a year, as in automotive service parts, then a three- to six-month sample will be appropriate. Compute Slotting Statistics Once the raw data are captured, the computation of slotting statistics is fairly straightforward. Unfortunately, the natural interpretations and application of the results may be counterintuitive and misleading (Table 8.4). These statistics appear on the surface to be self-explanatory. However, there are some subtle but critical issues surrounding the interpretation of each statistic. For example, popularity is often incorrectly measured in dol lar or unit sales. The popularity P of an item, like the popularity of a song on a jukebox, should be measured by the number of times it is requested. This indicator is critical because it is a measure of the number of potential times an operator will visit the location for a particular item. Because most of the work in a warehouse is traveling to, from, and between warehouse locations, knowledge of the potential location visits for individual and

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