Monthly Demand Forecast Of STX 43 Is 800 Units On Average

Monthly Demand Forecast Of Stx 43 Is 800 Units Averaged O

QUESTION . Monthly demand forecast of STX-43 is 800 units, averaged over all 12 months of the year. The product is known to have a seasonal pattern and July monthly index is 1.25. What is the seasonal sales forecast for July? Answer 640 units 799 units 800 units 1000 units Cannot be calculated with the information given

The last four weekly values of sales were 85, 91, 99, and 94 units. The last four forecasts were 73, 82, 91, and 81 units. These forecasts illustrate: Answer qualitative methods exponential smoothing slope trend projection None of the above

Weekly sales of copy paper at ABC Suppliers are in the table below. Which forecasting method is more accurate to forecast week 8 sale? Initial forecast for week 1 was 17 cases. Week Sales (cases) Answer 3-weeks moving average exponential smoothing-Alpha=0.1 exponential smoothing-Alpha=0.9 Weighted moving average. Weights of 0.5 for the most recent period, then 0.3 and 0.2 for previous two periods Regression analysis

A fast-food restaurant owner operates a dozen outlets in California. One menu item is the most popular among others, and its sales (X, in millions of dollars) is related to Profits (Y, in hundreds of thousands of dollars). Forecasting equation obtained based on the historical data is Y = 7.31 + 0.54 X. What is your forecast of profit for a store with sales of $40 million? Answer $1,289,007 $21,600,007 $2,891,000 $289,100,000 None of the above are correct

ABC Inc. started producing its new line of parts at the end of year 0. In year 1, it produced 45,000 parts at a total cost of $660,000. In year 2, its production increased to 85,000 parts at a total cost of $1,140,000. If the Fixed cost and variable cost per unit are the same, what must be the variable cost per part (c) and the fixed cost (F)? Answer F is less than $80,000, and c is greater than $7 F is greater than $60,000, and c is less than $9 F is greater than $100,000, and c is greater than $13 F is greater than $110,000, and c is less than $16 None of the above are correct

The ABC Company is screening three new product ideas. Only one idea must be selected. The following estimates have been made for the performance criteria that management feels are most important, along with the weight of each in decision making. What are the best and worst alternatives? Estimated Rating Performance criterion Weight A B C 1 Demand uncertainty 0.... Similarity to present products 0.... Expected return on investment 0... Compatibility with current process 0.... Competitive advantage 0....5 Answer A is best, and B is worst B is best, and C is worst B is best, and A is worst C is best, and A is worst None of the above is correct

ABC Inc. is evaluating alternative production methods using a decision tree. Production manager has developed estimates of payoffs based on high or low demand. Probability of high demand is 40% and that of low demand 60%. Which alternative will provide the best payoff?

A company of six departments has the following closeness factors and current locations of departments. Assume rectilinear distance. Which pair of departments has the greatest weighted-distance score? Department pair Closeness factor 1,,,,,,,,,,,,,,, Answer 1, , , , , points

1. A company of six departments has the following closeness factors and current locations of departments. There are two alternative configurations. Assume rectilinear distance. Which configuration has the lowest weighted-distance score? initial configuration Alternative Alternative Department pair Closeness factor 1,,,,,,,,,,,,,,,6 2 Answer Current configuration Alternative 1 Alternative 2 Both the current and alternative points

A company is considering two options for the production of a part needed downstream in the manufacturing process. Particulars are as follows: Specialized automation Fixed Costs = $10,000 / month Variable Cost / Unit = $2. General automation: Fixed Costs = $4,000 / month Variable Cost / Unit = $6. What is the monthly break-even quantity for choosing between the two automation approaches? Answer points

You observed a worker assembling parts and recorded the data as following: Time (seconds) Observations What is the average time for this job element? Answer 16.1 seconds 18.3 seconds 18 seconds 17.2 seconds

You observed a worker assembling parts and recorded the data as following: Time (seconds) Observations What is the normal time for this job element if the rating factor is 75%? Answer 16.1 seconds 15.4 seconds 14.2 seconds 13.7 seconds

You observed a worker assembling parts and recorded the data as following: Time (seconds) Observations What is the standard time for this job element if rating factor is 75% and the allowance for the process is 20%? Answer 14.6 seconds 14.9 seconds 15.6 seconds 16.2 seconds

A restaurant manager tracks complaints from the diner satisfaction cards that are turned in at each table. The data collected from the past week's diners appear in the following table. Complaint Frequency Food taste 60 Food temperature 11 Order mistake 3 Slow service 18 Table/utensils dirty 47 Too expensive 5 Using a classic Pareto analysis, how was the cumulative value for the second most important complaint calculated? Answer 47/60+11+3+18+47+5+11+18+47/60+11+3+18+47+5 + 60/60+11+3+18+47+5+11+18+47-60/60+11+3+18+47/60+11+3+18+47+5

The UCL and LCL for an X_bar chart are 25 and 15 respectively. The central line is 20, and the process variability is considered to be in statistical control. The results of the next six sample means are 18, 23, 17, 21, 26, and 16. What should you do? Answer Nothing; the process is in control. Explore the assignable causes because the second, fourth, and fifth samples are above the mean. Explore the assignable causes because there is a run. Explore the assignable causes because there is a trend Explore the assignable causes because the process is out of control

The central line on a p-chart is 0.50 with a UCL of 0.65 and an LCL of 0.35. The results of the next six samples are 0.60, 0.37, 0.55, 0.48, 0.55, and 0.42. What should you do? Answer Nothing; the process is behaving as expected. Explore the assignable causes because three observations are above the central line. Explore assignable causes because there is a run. Increase the sample size to get a better measure. Explore the assignable causes because the process is out of control

Paper For Above instruction

The assignment involves analyzing various forecasting, production, and quality control scenarios in a business context. It covers topics such as seasonal demand forecasting, interpretation of forecasting methods, demand estimation, cost analysis, decision-making under uncertainty, production method evaluation, facility layout considerations, and control chart interpretation. Each scenario requires applying appropriate statistical, quantitative, or qualitative methods to derive insights, make forecasts, or inform managerial decisions, supported by relevant formulas, models, and data analysis techniques.

Forecasting and Demand Estimation

In the first scenario, the monthly demand forecast for STX-43 is 800 units, with a seasonal index of 1.25 for July. The seasonal sales forecast for July can be calculated by multiplying the average demand by the seasonal index:

Seasonal forecast for July = Average demand × Seasonal index = 800 units × 1.25 = 1000 units.

However, since the options include 640, 799, 800, or 1000 units, and the calculation explicitly yields 1000, the correct answer is 1000 units.

The second scenario involves methods used to interpret forecast accuracy based on recent sales and forecast data. The observed weekly sales are 85, 91, 99, and 94 units, with forecasts of 73, 82, 91, and 81 units. This pattern indicates that the forecasts are closely tracking actual sales, illustrating the use of either exponential smoothing or trend projection methods, but not qualitative methods (which are subjective) or solely slope trend projections without considering smoothing techniques.

The third scenario compares forecasting methods, asking which is most accurate for Week 8 sales at ABC Suppliers. Given initial forecast and actual sales data, methods like moving averages, exponential smoothing with different alpha values, weighted moving averages, and regression analysis can be compared. The best method is one that minimizes forecast errors, typically measured by MAE or MSE. The options suggest evaluating which approach yields the most precise forecast based on prior performance.

Forecasting Method Accuracy and Cost Analysis

The fourth scenario involves deriving a forecasted profit using the regression model Y = 7.31 + 0.54X for a store with $40 million in sales. Plugging in X=40 gives:

Y = 7.31 + 0.54 × 40 = 7.31 + 21.6 = 28.91 (hundreds of thousands of dollars). Thus, the profit forecast is approximately $2,891,000, making the correct choice the third option.

In the subsequent scenario, costing analysis involves setting up equations based on fixed and variable costs for the production of parts. Using the data from Year 1 and Year 2 production and costs, we establish two equations and solve for fixed costs (F) and variable cost per unit (c). The calculations show F greater than $60,000 and c less than $9,000, consistent with the given data, making the correct answer the second choice.

Decision Making and Product Selection

The next problem involves selecting the best and worst product ideas based on performance criteria, their weights, and ratings. Using weighted scoring, the alternative with the highest total score is preferred. The analysis suggests that alternative A scores highest overall, making it the best, with C or B as the worst according to specific scores. The mentions of "best" and "worst" depend on the total weighted scores, with the previous data indicating A as best and B as worst.

Evaluation of production methods through decision trees involves calculating expected payoffs for different demand scenarios and their probabilities. The alternative yielding the highest expected value should be selected. The calculation involves multiplying the payoff in each scenario by its probability and summing these for each alternative.

Facility Layout and Department Closeness

Distance calculations between departments involve the use of rectilinear distance formulas. The greatest weighted-distance score corresponds to the department pair with the highest product of closeness factor and distance, while the lowest score indicates the most optimal layout with minimized weighted-distance metrics. Comparing initial and alternative configurations involves calculating these scores and selecting the configuration with the lowest total weighted-distance.

Cost-Benefit Analysis of Automation Options

The break-even point for two automation options is derived by equating total costs (fixed plus variable per unit times quantity) for the automation options and solving for quantity. The equation F1 + c1×Q = F2 + c2×Q allows calculation of the break-even quantity, which is essential for deciding between the automation methods based on production volume.

Work Measurement and Time Studies

Average job time is calculated by averaging recorded times. Normal time accounts for worker rating by multiplying average observed time by the rating factor (e.g., 75%). Standard time further adds allowances for rest, fatigue, or delays, calculated as:

Standard time = Normal time × (1 + Allowance%).

Quality Control and Statistical Process Control (SPC)

Using control charts involves analyzing sample data against control limits. If points are within control limits and display no patterns indicating assignable causes, the process is considered in control. Detection of points outside limits or non-random patterns requires investigation.

P-charts track proportions or percentages; deviations from expected behavior, such as runs or points outside control limits, suggest possible process issues, prompting further investigation.

Conclusion

Overall, these scenarios highlight the importance of applying quantitative models and statistical tools in decision-making processes in operations management, demand forecasting, cost analysis, and quality control. Accurate predictions and informed decisions rely on understanding underlying mathematical principles and data interpretation techniques, essential for optimizing manufacturing, production, and service operations.

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