George Kyparisis makes bowling balls in his Miami plant. With recent increases in his costs, h interest in efficiency. George is interested in determining the productivity of his organization. H his organization is maintaining the manufacturing average of a 3% increase in productivity. He representing a month from last year and an equivalent month this year: Last Year 4.500 Now 4.500
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- At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.The Grand Bakery produces 60 special sourdough rolls every day. Any rolls that are not sold each day are given to the employees. They have collected sales data from the past week: Day Rolls sold 1 50 2 50 3 48 4 60 5 53 6 60 What is the value of F6 if they use a 3-day weighted moving average with W1 = 0.6, W2 = 0.2, and W3 = 0.2? Using the data from above, calculate the forecast for period 7 using a four-period moving average:A Lighting company seeks to study the percentage of the defective glass shells being manufactured. Theoretically, the percentage of defectives is dependent on temperature, humidity, and the level of artisan expertise. Complete historical data are available for the following variables on a daily basis for a year.a. Temperature (high, normal, low)b. Humidity (high, normal, low)c. Artisan expertise (expert, average, mediocre)Some experts feel that defectives also depend on productive supervisors. However, data on supervisors in charge are available for only 242 of the 365 days. How should you conduct this study?
- An auditor used regression analysis to evaluate the relationship between utility costs andmachine hours. The following information was developed using a computer softwareprogram: Intercept 2,050 Standard error of estimate 200Regression 0.825 Number of observations 36Correlation coefficient 0.800 How much is the utility cost if the company’s 10 machines will use 2,400 hours next month?a. ₱3,830b. ₱3,970c. ₱4,030d. ₱4,050An exponential smoothing is being used to forecast demand. Which of the following alpha value (or error weight) should be used if the demand is highly sensitive to the current events and external factors? a. 0.75 b. 0.05 c. -1.5 d. 0.0 e. 1.75Calculate the sales forecasted for the year 2021 using Exponential smoothing given a weight a of o.45, and assuming that the forecasted value for the year 2020 was KWD 1000 and actual value is KWD 1200. i - B I II
- Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year -1 2 Registrations (000) 5.0 5.0 Year Forecast 4 4.3 This exercise contains only parts a and b. a) Using a 3-year moving average, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to one decimal place): 5 4.6 4 3 3.0 5 6 6.6 7 8 4 5 6 9 10 6.0 11.0 9.0 7.0 9.0 13.0 16.0 6 7 8.7 8 9 7 9 8.3 b) Using a 3-year weighted moving average in which the registrations in the most recent year are given a weight of 2, and registrations in the other 2 years are each given a weight of 1, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to one decimal place): Year Forecast 8 10 9.6 9 11 12.6 10 12 15.3 11 11 17.0 12A company is planning to launch a new product. It currently has four possible new products under consideration to invest in but it must select one. It has estimated the following data: Product Expected annual demand Unit cost of production Unit selling price Fixed cost incurred before production Expected product life in years A 500 Product B Product A Product C Product D £700 £900 £150,000 2 years B 700 £900 £1300 £350,000 2.5 years C 850 £1000 £1400 £450,000 3 years D 1000 £1200 £1500 £550,000 3.25 years On the basis that the main selection criterion is the product that offers the largest safety margin between break even quantity and expected product life select the safest product to invest in.A ski resort has recorded its recent sales as follows (in $$). Season 2 years ago Last year This year Spring 700 950 900 Summer 450 500 400 Fall 1,150 1,100 1,350 Winter 1,400 1,500 1,600 The resort estimated that the annual demand for the next year will be 4,800. What would be the forecast for next Fall? Answer: _______
- Exercise 5: Use the following provided information about sales to determine: a) Trend line b) Predicted value for 2022 Year Units sold 2015 100 2016 110 2017 122 2018 130 2019 139 2020 152 2021 164 To minimize the calculations, it would be better to transform the x value (time) in easier numbers. For instance, it would be better to name year 2015 as year 1, 2016 as year 2 and so on.Mop and Broom Manufacturing has tracked the number of units sold of their most popular mop over the past 24 months. This is shown. Month 1 2 3 4 5 6 7 8 Sales Month 238 249 254 267 277 282 402 296 9 10 11 12 13 14 15 16 Sales 300 327 346 349 353 364 373 363 Month + 17 18 19 20 21 22 23 24 Sales 361 381 375 383 384 401 409 403 a. Develop a linear trend line for the data. (Round your answers to 2 decimal places, e.g.,25.28.) Sales = (month) b. Compute a correlation coefficient for the data and evaluate the strength of the linear relationship. (Round your answer to 2 decimal places, the tolerance is +/-0.01.) Correlation coefficient is . It indicates linear relationship. (Use not rounded amounts to answer this question.) c. Using the linear trend line equation, develop a forecast for the next period,month 25. (Round your answer to 2 decimal places, the tolerance is +/-0.01. Do not round intermediate results used to achieve this answer.) Forecast for month 25 =The number of heart surgeries performed at HeartvilleGeneral Hospital has increased steadily over the past sev-eral years. The hospital’s administration is seeking the bestmethod to forecast the demand for such surgeries in year 6.The data for the past 5 years are shown. The hospital’s administration is considering the followingforecasting methods. Begin error measurement in year 3 soall methods are compared for the same years.i. Exponential smoothing, with a = 0.6. Let the initial fore-cast for year 1 be 45, the same as the actual demand.ii. Exponential smoothing, with a = 0.9. Let the initial fore-cast for year 1 be 45, the same as the actual demand.iii. Trend projection with regression.iv. Two-year moving average.v. Two-year weighted moving average, using weights 0.6 and0.4, with more recent data given more weight.vi. If MAD is the performance criterion chosen by the admin-istration, which forecasting method should it choose?vii. If MSE is the performance criterion chosen by the…