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Cost Accounting (14th Edition)

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ASSIGNMENT MATERIAL 385<br />

A<br />

B<br />

C<br />

1 Direct material<br />

$ 200,000<br />

2 Direct manufacturing labor time for first boat<br />

15,000 labor-hours<br />

3 Direct manufacturing labor rate<br />

$ 40 per direct manufacturing labor-hour<br />

4 Variable manufacturing overhead cost<br />

$ 25 per direct manufacturing labor-hour<br />

5 Other manufacturing overhead<br />

20% of direct manufacturing labor costs<br />

6 Tooling costs a $280,000<br />

7 Learning curve for manufacturing labor time per boat<br />

90% cumulative average time b<br />

8<br />

9<br />

a Tooling can be reused at no extra cost because all of its cost has been assigned to the first deployment boat.<br />

10<br />

11<br />

ln 0.9 –0.105361<br />

Using the formula (p. 359), for a 90% learning curve, b =<br />

ln 2<br />

=<br />

0.693147<br />

= –0.152004<br />

12<br />

1. Calculate predicted total costs of producing the six PT109s for the Navy. (Nautilus will keep the first<br />

deployment boat assembled, costed at $1,575,000, as a demonstration model for potential customers.)<br />

2. What is the dollar amount of the difference between (a) the predicted total costs for producing the six<br />

PT109s in requirement 1, and (b) the predicted total costs for producing the six PT109s, assuming that<br />

there is no learning curve for direct manufacturing labor? That is, for (b) assume a linear function for<br />

units produced and direct manufacturing labor-hours.<br />

10-37 <strong>Cost</strong> estimation, incremental unit-time learning model. Assume the same information for the<br />

Nautilus Company as in Problem 10-36 with one exception. This exception is that Nautilus uses a 90% incremental<br />

unit-time learning model as a basis for predicting direct manufacturing labor-hours in its assembling<br />

operations. (A 90% learning curve means b = –0.152004.)<br />

1. Prepare a prediction of the total costs for producing the six PT109s for the Navy.<br />

2. If you solved requirement 1 of Problem 10-36, compare your cost prediction there with the one you<br />

made here. Why are the predictions different? How should Nautilus decide which model it<br />

should use?<br />

10-38 Regression; choosing among models. Tilbert Toys (TT) makes the popular Floppin’ Freddy Frog and<br />

Jumpin’ Jill Junebug dolls in batches. TT has recently adopted activity-based costing. TT incurs setup costs<br />

for each batch of dolls that it produces. TT uses “number of setups” as the cost driver for setup costs.<br />

TT has just hired Bebe Williams, an accountant. Bebe thinks that “number of setup-hours” might be<br />

a better cost driver because the setup time for each product is different. Bebe collects the following data.<br />

Required<br />

Required<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

7<br />

8<br />

9<br />

10<br />

A<br />

Month<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

7<br />

8<br />

9<br />

B<br />

Number of Setups<br />

300<br />

410<br />

150<br />

480<br />

310<br />

460<br />

420<br />

300<br />

270<br />

C<br />

Number of Setup Hours<br />

1,840<br />

2,680<br />

1,160<br />

3,800<br />

3,680<br />

3,900<br />

2,980<br />

1,200<br />

3,280<br />

D<br />

Setup <strong>Cost</strong>s<br />

$104,600<br />

126,700<br />

57,480<br />

236,840<br />

178,880<br />

213,760<br />

209,620<br />

90,080<br />

221,040

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