# Parts Emporium

Topics: Inventory, Normal distribution, Holding cost Pages: 3 (537 words) Published: December 6, 2012
CASE: PARTS EMPORIUM
• Sue McCaskey, the new materials manager of a wholesale distributor of auto parts. • She seeks ways to cut the bloated inventories while improving customer service. • Back orders with excessive lost sales are all too frequent. Inventories were much higher than expected when the new facility was built, even though sales have not increased.

CASE: PARTS EMPORIUM
• Summary data on inventory statistics, such as inventory turns, are not available. • McCaskey decides to begin with a sample of two products to uncover the nature of the problems: the EG151 exhaust gasket and the DB032 drive belt.

CASE: PARTS EMPORIUM
• Either a continuous review system (Q system) or a periodic review system (P system), for two inventory items. • Enough information is available to determine the EOQ and R for a continuous review system – P and T for a periodic review system

• Because stockouts are costly relative to inventory holding costs, a 95% cycle-service level is recommended.

CASE: PARTS EMPORIUM
• Inventory holding costs are 21% of the value of each item (expressed at cost). • The ordering costs: \$20 for exhaust gaskets and \$10 for drive belts – The ordering costs should not be increased to include charges for making customer deliveries. – These charges are independent of the inventory replenishment at the warehouse and are reflected in the pricing policy.

Analysis

EG151 Exhaust Gasket
• Estimating annual demand and the variability in the demand during the lead time for this item. – Use the weekly demands for the first 21 weeks of 2001 and assuming 52 business weeks per year

• Weekly demand average = 102 gaskets/week • Annual demand (D) = 102*52 = 5,304 gaskets • Holding cost = \$1.85 per gasket per year (= 0.21*(1-0.32)*\$12.99) • Ordering cost = \$20 per order

Analysis

EG151 (continued)
• Normal distribution  a 95% cycle-service level corresponds to a z = 1.645 • Standard deviation in weekly demand = ? • Standard deviation in...

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