Assume the same information for the Blue Seas Company as in Problem 10- 35 with one exception. This exception is that Blue Seas 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.)

In Problem 10- 35, The Blue Seas 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 Blue Seas submit a proposal on the cost of producing another six PT109s. Blue Seas 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. Prepare a prediction of the total costs for producing the six PT109s for the Navy.
2. If you solved requirement 1 of Problem 10- 35, compare your cost prediction there with the one you made here. Why are the predictions different? How should Blue Seas decide which model it shoulduse?

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Direct material Direct manufacturing labor rate Variable manufacturing overhead cost $ 43lper direct manufacturing labor-hour $24per direct manufacturing labor-hour Other manufacturing overhead Tooling costs Learning curve for manufacturing labor time per boat Tooling can be reused at no extra cost because all of its cost has been assigned to the first deployment boat 15%)of direct manufactunng labor costs S281,000 90%!cumulative average time n 0.9-0.105361 Using the formula (page 390), for a 90% learning curve, b T 2 . in 26931470.152004