OPS 330 Week 3 Inventory and Supply Chain Control Example

Axles, Aluminum and a Missing Box of Hinges: Inventory and Supply Chain Control at a Build-to-Order Trailer Plant

[Student Name]

University of Phoenix

OPS/330: Strategic Operations and Logistics

Week 3 Assignment

[Instructor Name]

[Date]

Red Dirt Trailer Works, its items, costs and demand figures are composites written for a model paper.

Red Dirt Trailer Works, the made-up southern Oklahoma builder of aluminum livestock and horse trailers, has found that welding limits its output and is planning an integrated planning system. Inventory sits underneath both issues. In the last six months welding stopped 14 times because parts were missing, losing about 30 trailer-hours each time, while the warehouse held almost five months of supply of some slow-moving fittings. Purchasing works from experience and a whiteboard. This paper sets inventory policies and supply chain controls.

Classifying the Items

Red Dirt buys about 600 different items. ABC analysis ranks them by annual spending. Class A, about 55 items or 9 percent, accounts for about 75 percent of spending: aluminum extrusions and sheet, axles, tires and wheels, lighting kits and gooseneck couplers. Class B, about 120 items, accounts for about 18 percent: doors, windows, dividers and paint. Class C, the remaining 425 or so, accounts for about 7 percent: bolts, rivets, hinges, latches and wiring connectors. Flores and Whybark (1986) argued that classification by spending alone can miss items that are cheap but critical, and proposed adding other criteria. Red Dirt therefore moved two cheap but critical items, the welding wire for aluminum and the gooseneck safety chains, into close control despite their low spending.

Class A: Axles and the Economic Order Quantity

Axles are bought from one supplier at about $480 each. Each trailer uses two, and the plant builds about 22 trailers a week for 50 weeks, so annual demand is about 2,200 axles. Placing and receiving an order costs about $120 in purchasing time, freight scheduling and receiving. Holding an axle for a year costs about 20 percent of its price, or $96, covering capital, space and handling. The economic order quantity, a model Harris first published in 1913 and reprinted much later (Harris, 1990), balances ordering cost against holding cost; with these inputs it works out to √(2 × 2,200 × 120 ÷ 96), about 74 axles. That is about 34 orders a year, roughly two trailers' worth of axles every week and a half.

Class A: Aluminum and the Reorder Point

Aluminum extrusions arrive from a mill distributor in Texas with a three-week lead time. Weekly use averages about 38,000 pounds, with a standard deviation of about 6,000 pounds because trailer sizes vary. For a 95 percent chance that aluminum lasts until the next delivery arrives, the plant needs safety stock of about 1.65 standard deviations of demand over the lead time: 1.65 × 6,000 × the square root of 3, or about 17,100 pounds. The buyer's trigger level adds that cushion to the aluminum the plant expects to use while an order is in transit: 3 × 38,000 + 17,100, or about 131,000 pounds. When on-hand plus on-order aluminum falls below that level, the buyer orders.

The cheapest box of hinges in the building can stop the most expensive bay in the plant.

Class C: A Two-Bin Kanban

Hardware such as rivets, bolts and hinges moves to a two-bin system at each work area. Each bin holds about two weeks of use. When a bin empties, the worker places its card in a collection box; the stockroom refills it from bulk stock, and the buyer reorders bulk stock weekly from the cards collected. This removes daily counting of hundreds of cheap items and puts parts within reach of the people who use them.

The Bullwhip Effect

Red Dirt's orders from dealers swing more than ranchers' actual purchases. In spring, dealers order heavily to stock their lots; in summer they stop. Lee et al. (1997) showed that order variability tends to grow as orders move up a supply chain, through causes such as demand forecast updating, order batching, price fluctuations and shortage gaming, so that manufacturers and suppliers see larger swings than end customers. Red Dirt's purchases from its aluminum distributor swing even more than dealer orders, because buyers pad orders when they fear shortages.

Supply Chain Controls

Three controls dampen the swings. First, Red Dirt will share a rolling 12-week build schedule with its aluminum distributor and axle supplier, so they can plan capacity rather than react to padded orders. Second, it will ask its top 20 dealers for monthly retail sales reports, giving visibility of real demand. Third, it will stop padding orders by using the calculated reorder point and order quantity, which build in a planned safety margin.

Who Does What

The buyer owns Class A policies and reviews reorder points monthly as demand changes. Stockroom staff own the two-bin replenishment and cycle counts. The production manager reports any parts stoppage at welding the same day, with its cause, so the buyer can adjust the policy for that item. Policies are written on one page for each class so that a new buyer could follow them.

When the Models Do Not Fit

The formulas assume steady demand, which a build-to-order plant does not have in every item. Options such as living-quarters packages are ordered only for specific trailers and arrive on their own schedule; for those, the plant orders per trailer when the build sheet is released rather than holding stock. The economic order quantity also assumes the supplier will ship any quantity, but the axle supplier offers a price break at 100 units; at that volume the total yearly cost of the larger order should be compared with the calculated quantity before the policy is fixed.

Measures

Inventory turns for Class A items, targeting a rise from about 7 to 10 a year; parts stoppages at welding, target zero; fill rate from the stockroom, target 98 percent; and inventory accuracy, target 97 percent by cycle counts of Class A items monthly.

Connecting to the Bottleneck

Every policy is designed to protect welding. A shortage that stops a non-bottleneck step may cost nothing, since that step has spare capacity; a shortage at welding costs trailers that can never be made up. That is why the aluminum safety stock is set at a high service level while low-cost hardware relies on simple bins.

Conclusion

Classifying 600 items, setting an order quantity for axles, a reorder point with safety stock for aluminum and a two-bin kanban for hardware gives Red Dirt policies matched to each item's value and risk. Sharing schedules with suppliers and sales data from dealers addresses the bullwhip effect that amplifies the plant's own swings. Measured by turns, stoppages and fill rates, these controls protect the bottleneck that sets the plant's output.

References

Flores, B. E., & Whybark, D. C. (1986). Multiple criteria ABC analysis. International Journal of Operations & Production Management, 6(3), 38-46. https://doi.org/10.1108/eb054765

Harris, F. W. (1990). How many parts to make at once. Operations Research, 38(6), 947-950. https://doi.org/10.1287/opre.38.6.947 (Original work published 1913)

Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546-558. https://doi.org/10.1287/mnsc.43.4.546