0Hence the total cost 8265960 1 point Alternate solution Labour hour 600043392

# 0hence the total cost 8265960 1 point alternate

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387,540.0 Hence, the total cost = \$826,596.0 (1 point) Alternate solution Labour hour = 6,000(4.3392-1.9000) = 14,635.2 Materials, equipment usage and supplies = 200,000(3.7377-1.8000) = \$387,540. Question 3: (8 points) Observed weekly sales of ball peen hammers at the town hardware store over a five-week period have been 16, 12, 28, 24, 32. a. (3 points) Suppose that three-week moving averages are used to forecast sales, Determine the one-step-ahead forecasts for weeks 4 and 5. 67 18 3 28 12 16 4 . = + + = F 33 21 3 24 28 12 5 . = + + = F b. (3 points) Suppose that exponential smoothing is used to with a smoothing constant of . 20 . 0 = α Find the exponential smoothing forecasts for weeks 4 and 5. (To get the method started, use the same forecast for week 4 as you used in part a .) 67 18 4 . = F ( 29 736 19 67 18 24 20 0 67 18 5 . . . . = - + = F c. (2 points) Based on the MAD, which method did better? 8 2 33 21 32 67 18 24 = - + - = . . MAD MA 797 8 2 736 19 32 67 18 24 . . . MAD ES = - + - = Thus, moving average is better. 4
Name:_________________________________________________ ID:_________________________ Question 4: (10 points) Lakeroad, a manufacturer of hard disks for personal computers, was founded in 2005 and has sold the following number of disks: Year Numbers Sold (in 000s) 2005 24 2006 35 2007 47 a. (7 points) Calculate the exponential smoothing with trend component forecast for years 2006 and 2007 using an initial trend forecast ( T 1 ) of 12, an initial exponential smoothing forecast ( F 1 ) of 13, an α of 0.20, and a δ of 0.20. Year t Actual F t T t FIT t 2005 24 13 12 13+12 = 25.00 2006 35 0.20(24)+0.80(25) = 24.80 (2 points) 0.20(24.80-13)+0.80(12) = 11.96 (2 points) 24.80+11.96 = 36.76 (2 points) 2007 47 0.20(35)+0.80(36.76) = 36.408 0.20(36.408-24.80)+0.80(11.96) = 11.89 36.408+11.89 = 48.298 (1 point) b. (3 points) What is the sales forecast for the year 2009 made at the end of 2007? ( 29 ( 29 ( 29 ( 29 8266 71 89408 11 2 0384 48 89408 11 89 11 8 0 408 36 0384 48 20 0 0384 48 298 48 80 0 47 20 0 2009 2008 2008 2008 . . . . . . . . . . . . . , = × + = = + - = = + = FIT T F Question 5: (15 points) Use regression analysis on deseasonalized demand to forecast demand in Fall 2007, given the following historical demand data: Year Season Actual Demand 2005 Winter 61 Spring 77 Summer 79 Fall 64 2006 Winter 69 Spring 86 Summer 90 Fall 76 5
Name:_________________________________________________ ID:_________________________ Quarterly average demand = (61+77+79+64+69+86+90+76)/8 = 75.25 Season Average demand Seasonal Index Winter (61+69)/2 = 65.0 65.0/75.25 = 0.8640 Spring (77+86)/2 = 81.5 81.5/75.25 = 1.0830 Summer (79+90)/2 = 84.5 84.5/75.25 = 1.1230 Fall (64+76)/2 = 70.0 70.0/75.25 = 0.9300 4.0000 Period x Demand Deseasonalized Demand y xy 2 y 1 61 70.6 70.6 1 2 77 71.1 142.2 4 3 79 70.4 211.1 9 4 64 68.8 275.2 16 5 69 79.9 399.4 25 6 86 79.4 476.4 36 7 90 80.1 561.0 49 8 76 81.7 653.6 64 x =36 y =602.0 xy =2789.5344 2 y =204 X =4.5 Y =75.25 ( 29 ( 29 ( 29 ( 29 ( 29 9175 1 0 336 2752 644

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