Question: Cost estimation, incremental unit-time learning model. Assume the same information for the Pacific Boat Company as in Problem 10-40 with one exception. This exception is that Pacific Boat uses a 90% incremental unit-time learning model as a basis for predicting direct manufacturing labor-hours in its assembling operations. (A 90% learning curve means b = -0.152004.)

1. Prepare a prediction of the total costs for producing the six PT109s for the Navy.

2. If you solved requirement 1 of Problem, compare your cost prediction there with the one you made here. Why are the predictions different? How should Pacific Boat decide which model it should use?

Problem: Cost estimation, cumulative average-time learning curve. The Pacific Boat Company, which is under contract to the U.S. Navy, assembles troop deployment boats. As part of its research program, it completes the assembly of the first of a new model (PT109) of deployment boats. The Navy is impressed with the PT109. It requests that Pacific Boat submit a proposal on the cost of producing another six PT109s. Pacific Boat reports the following cost information for the first PT109 assembled and uses a 90% cumulative average-time learning model as a basis for forecasting direct manufacturing labor-hours for the next six PT109s. (A 90% learning curve means b = -0.152004.)

1. Calculate predicted total costs of producing the six PT109s for the Navy. (Pacific Boat will keep the first deployment boat assembled, costed at $1,477,600, as a demonstration model for potential customers.)

2. What is the dollar amount of the difference between

(a) the predicted total costs for producing the six PT109s in requirement 1 and

(b) the predicted total costs for producing the six PT109s, assuming that there is no learning curve for direct manufacturing labor? That is, for (b) assume a linear function for units produced and direct manufacturing labor-hours.