You are a process analyst at Telecom Systems Inc. TSI is a fictitious contract electronics manufacturer (CEM). Like other CEMs such as Jabil Circuit and Flextronics, TSI provides manufacturing capacity for producing branded electronics products such as Research in Motion's Blackberry and DIRECTV receivers.

One of the processes that you are supporting is preparing to produce portable hard drives for several customers. This is new business for TSI although other CEMs have produced this product in the past. Initial estimates are for a flow time of 18 hrs per unit and an average completion rate of 75 hard drives per hr. The production manager is would like to produce this order with a work in process inventory of about 500 units.

Something about these numbers bothers you, so you decide to some analysis. Here's some of the things your analysis should consider:

• Is the production manager's 500 unit WIP realistic?
• If not, how would flow time and/or average completion rate need to change in order to achieve a 500 unit WIP?
• What SCM practices might be employed in order to better achieve the 500 WIP goal? Cite some examples.
• What's a conservative next step?
• Be sure to explain your method adequately.

Write a memo to the production managers that presents your findings and analysis.

1-The initial estimates of flow time of 18 hrs/unit and average completion rate of 75 units/hr suggest that work in process (WIP) should be approximately:

2- Based on the initial flow time and average completion rate estimates, the production managers goal of 500 units of work-in-process seems realistic.

3- If the production process maintained an 18 hr/unit flow time, what would the average completion rate need to be in order to achieve 500 units of WIP?

4-If the production process maintained an average completion rate of 75 units/hr, what would the flow time need to be in order to achieve 500 units of WIP?

5-If TSI wants to reduce its WIP, which of the following likely holds the most promise?

6-In service sector applications, the variable in Littles Law that can be used to approximate the number of customers waiting in line is: