Operations Management: Processes and Supply Chains (12th Edition) (What's New in Operations Management)
12th Edition
ISBN: 9780134741062
Author: Lee J. Krajewski, Manoj K. Malhotra, Larry P. Ritzman
Publisher: PEARSON
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Chapter 10, Problem 12P
Gemini Inc. is using the Sales and Operations Planning with Spreadsheets Solver in OM Explorer to develop a 5-nioiith production plan. Use the provided derived outputs and calculated costs to specify the model’s inputs. (Hint: Don’t forget that the
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Students have asked these similar questions
Whitebridge Hardware Store
Whitebridge Hardware Store has a monthly demand for lawn fertilizer listed below. The gardening season starts in early spring when people want to fertilize their lawns.
Period
Demand
Jan
59
Feb
68
March
91
April
145
May
182
June
212
July
193
Aug
174
Sept
144
Oct
89
Nov
74
Dec
55
Answer Questions 1 – 5 below. [Be sure to watch the video on how to complete your forecasting problem, in the content module.] Everything must be typed including the graph.
You need to complete this assignment in Excel. For the narrative answers, you can include them in Excel in one or more of the empty cells. If you know how to add an extra worksheet, you can add your answers on a new worksheet. Or you can type them in a Word document Please include your name somewhere.
In the Assignments area, a…
After plotting demand for four periods, an emergency room manager has concluded that a trendadjusted exponential smoothing model is appropriate to predict future demand. The initial estimate oftrend is based on the net change of 30 for the three periods from 1 to 4, for an average of +10 units.Use α = .5 and β = .4, and TAF of 250 for period 5. Obtain forecasts for periods 6 through 10.Period Actual Period Actual1 210 6 2652 224 7 2723 229 8 2854 240 9 2945 255 10
The table below comprises of demand from the last 10 months:
Month
Demand
1
31
2
34
3
33
4
35
5
37
6
36
7
38
8
40
9
40
10
41
Calculate the exponential smoothing with trend forecast for the second month using a alpha and delta of 0.3 each. Take the initial exponentially smoothed forecast (F1) of 30 and initial trend forecast (T1) of 1.
Note: I have tried solving this question and I got 31, but unfortunately it was the wrong answer.
Chapter 10 Solutions
Operations Management: Processes and Supply Chains (12th Edition) (What's New in Operations Management)
Ch. 10 - List the types of costs incurred when employees...Ch. 10 - Prob. 2DQCh. 10 - Prob. 3DQCh. 10 - Explain why management should be concerned about...Ch. 10 - The Barberton Municipal Division of Road...Ch. 10 - Bob Canton’s golf camp estimates the following...Ch. 10 - Prob. 3PCh. 10 - Prob. 4PCh. 10 - Management at the Kerby Corporation has determined...Ch. 10 - Gretchen’s Kitchen is a fast-food restaurant...
Ch. 10 - Prob. 7PCh. 10 - Tax Prep Advisers, Inc. has forecasted the...Ch. 10 - Climate Control, Inc. makes expedition-quality...Ch. 10 - Prob. 11PCh. 10 - Gemini Inc. is using the Sales and Operations...Ch. 10 - Gerald Glynn manages the Michaels Distribution...Ch. 10 - Cara Ryder manages a ski school in a large resort...Ch. 10 - Prob. 15PCh. 10 - Prob. 17PCh. 10 - The Hickory Company manufactures wooden desks....Ch. 10 - Prob. 19PCh. 10 - The Mowry Machine Shop still has five jobs to be...Ch. 10 - If we use the same number of workers in each...Ch. 10 - Prob. 2AMECh. 10 - Prob. 3AMECh. 10 - Suppose the overtime cost is $3,300. What happens...Ch. 10 - Suppose the undertime cost is the same as the...Ch. 10 - Prob. 6AMECh. 10 - Prob. 1VCCh. 10 - Does Starwood employ a chase, level, or mixed...Ch. 10 - How would staffing for the opening of a new hotel...Ch. 10 - Explain the alternatives available to Darlene Fry...Ch. 10 - Prob. 2C
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- The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?arrow_forwardThe file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?arrow_forwardThe file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?arrow_forward
- The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?arrow_forwardThe quarterly demand for smartphones at a retailer is as show. Year Quarter Demand 1 I 513 1 II 932 1 III 1509 1 IV 1902 2 I 693 2 II 1163 2 III 1857 2 IV 2469 Forecast the quarter 1 demand for year 3 using the following models: 4-quarter simple moving average. Simple exponential smoothing with α = 0.1. We assume that the forecasted value of quarter 1 is 500. Which method is the most accurate and why?arrow_forward1. Using MAD as the criterion, which of the following models would you use for thegiven time series data? Why?A. Naïve approach;B. 5-month SMA model;C. WMA model with weights 0.1, 0.3, and 0.6; orD. ES model with α = 0.5 and a forecast of 3,500 liters in the first month.NOTE: In answering Item 1, mention the whole description of the model; i.e., not just“SMA model”, but “SMA model with n = ...”; not just “WMA model”, but “WMA modelwith weights ...”; not just “ES model”, but “ES model with α = ...”.arrow_forward
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