Reference no: EM13905577

Your immediate superior on your new job is VP-Operations for one plant of a major home appliance producer. Her responsibilities cover over 8000 WIP and Raw Materials items used in making home appliances. The VP prides herself on employee accessibility and bottom-up communication. She takes regular walks through the plant, greeting employees and listening to problems and suggestions from line workers. While on a walk-through one Friday morning, with you and a few others in tow, she was stopped by the foreman of a fabrication department. "You know, ma'am, we're losing a lot of money on production of the 4387's," he said referring to a WIP item by its part number.   "We make 'em on this old machine we've had for 25 years. It’s slow and we never know how long it'll take to set it up when we start a run. I think if you replaced this machine we'd be a lot more efficient out here in the plant." Not really believing there was a problem with the 4387's but needing to look like she was taking the foreman seriously, she turned to you and said "Why don't you look into this and let me know Monday how big the problem is."

All day that Friday you talked to the foreman, product designers, equipment engineers, and purchasing agents. From these people and company data on cost and setups you found out:

4387's are used in one model of product in your plant. Demand fluctuates with a daily average of 125 units and a standard deviation of 20.   Holding costs are 35% of item value, and your plant runs 250 days per year. Plant-wide, everyone strives for a service level of 99.7%.

The old machine the foreman talked about produces only 4387's on a batch basis. It runs at the rate of 250 units per day, with each unit being worth $75. Setting up the machine to produce a batch of 4387's is the problem that caught the foreman's eye. According to setup records, the average machine setup for this item is 3 days, but the setup times are unpredictable and the standard deviation is .5 days. Setups cost in labor and a consumed material is $3000. The equipment engineers say the unreliable setups are due to the old, inefficient design of the machine. The foreman says it's age. "This thing is old and stubborn and works when it wants to."

The engineers tell you new equipment can be purchased to replace the stubborn machine. The new equipment could produce 600 units per day at $75 per unit. Setups should only cost $500 on this machine and take an average of 2 days. The standard deviation of these setups is .1 days.

The product designers and purchasing agents tell you an outside supplier can provide acceptable 4387's. The supplier the purchasing agent has in mind would sell 4387's for $75 each, with a 1.25% discount per unit on all orders of 4000 units or more. The ordering cost would be only $100, with 4 days lead time required on orders. The standard deviation of this lead time is estimated by the purchasing agent to be .15 days. Your firm has never done business with this supplier before and has no experience with their quality or ability to meet shipment dates.

By late Friday afternoon you began the task of trying to make sense of the data you'd gathered.   Your task was to 1) determine if the foreman's stated problem with 4387 really existed and, if it did, 2) decide how the acquisition of the part should be changed. Complete the analysis using what you know about order point and order quantity models, then write a short memo to the VP-Operations presenting and explaining your analysis and recommending a course of action. In arriving at your recommendation consider both your quantitative analysis and other non-quantitative factors you think are important to the decision.