If the two machines, M1 and M2 are turned off, and assuming that total sound pressure level is 120 dB, analyze the sound pressure level of the background noise (in decibels) and its mean square pressure (in N/m²) at the operator position. If the data from Table Q2(b) is converted to octave band as shown in Table Q2(c), examine the total sound pressure level in dB(A) and total mean square pressure (in N/m²). (iii) Describe briefly three method to control the noise if the answer in Q2(b)(iii) is SPL > 85 dB(A). (iv)

If the two machines, M1 and M2 are turned off, and assuming that total sound pressure level is 120 dB, analyze the sound pressure level of the background noise (in decibels) and its mean square pressure (in N/m²) at the operator position. If the data from Table Q2(b) is converted to octave band as shown in Table Q2(c), examine the total sound pressure level in dB(A) and total mean square pressure (in N/m²). (iii) Describe briefly three method to control the noise if the answer in Q2(b)(iii) is SPL > 85 dB(A). (iv)

Essentials of Business Analytics (MindTap Course List)

2nd Edition

ISBN:9781305627734

Author:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Publisher:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Chapter8: Time Series Analysis And_forecasting

Section: Chapter Questions

Problem 5P: Consider the following time series data: Construct a time series plot. What type of pattern exists...

See similar textbooks

Similar questions

Consider the two air conditioning systems detailed below. Use AW analysis to determine the sensitivity of the economic decision to MARR values of 4%,6%, and 8%. Work this problem (a) by hand and (b) by spreadsheet.
Consider the following data: a. Develop a frequency distribution using classes of 1214, 1517, 1820, 2123, and 2426. b. Develop a relative frequency distribution and a percent frequency distribution using the classes in part a.
Create an “Equivalent Rate Calculator” that converts an input rate that is given in one compounding frequency to an equivalent rate that is expressed in a different compounding frequency.
I drag a stick at 2 m/s through an extremely shallow rectangular box filled with oil, creating a shock wave. I measure the angle made by the wave with the line along which the stick isdragged to be 45°. What is the speed of surface waves in this box?
Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 8. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 8. Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.
Please include excel formula Using the following returns, calculate the arithmetic average returns, the variances, and the standard deviations for X and Y. Input area: Year X Y 1 13% 27% 2 26% 36% 3 7% 11% 4 -5% -29% 5 11% 16% (Use cells A6 to C11 from the given information to complete this question. You must use the built-in Excel function to answers this question. Make sure to use the “sample” Excel formulas.) Output area: Asset X: Average return Variance Standard deviation Asset Y: Average return Variance Standard deviation
Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Explain. Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.
Suppose that Motorola uses the normal distribution to determine the probability of defects and the number of defects in a particular production process. Assume that the production process manufactures items with a mean weight of 10 ounces. Calculate the probability of a defect and the suspected number of defects for a 1,000-unit production run in the following situations. a. The process standard deviation is 0.15, and the process control is set at plus or minus one standard deviation. Units with weights less than 9.85 or greater than 10.15 ounces will be classified as defects. b. Through process design improvements, the process standard deviation can be reduced to 0.05. Assume that the process control remains the same, with weights less than 9.85 or greater than 10.15 ounces being classified as defects. c. What is the advantage of reducing process variation, thereby causing process control limits to be at a greater number of standard deviations from the mean?
In a manufacturing process the assembly line speed (feet per minute) was thought to affect the number of defective parts found during the inspection process. To test this theory, managers devised a situation in which the same batch of parts was inspected visually at a variety of line speeds. They collected the following data: Develop a scatter chart with line speed as the independent variable. What does the scatter chart indicate about the relationship between line speed and the number of defective parts found? Use the data to develop an estimated regression equation that could be used to predict the number of defective parts found, given the line speed. What is the estimated regression model? Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? How much of the variation in the number of defective parts found for the sample data does the model you estimated in part (b) explain?
Ned Thompson Labs performs tests on superalloys, titanium, aluminum, and most metals. Tests on metal composites that rely upon scanning electron microscope results can be subcontracted or the labs can purchase new equipment. Evaluate the sensitivity of the economic decision to purchase the equipment over a range of ±20% (in 10% increments)of the estimates for P, AOC, R, n, and MARR (range on MARR is 12% to 18%). Use the AW method and plot the results on a sensitivity graph. For which parameter(s) is the AW most sensitive? least sensitive? First cost, P = $-180,000 Salvage, S = $20,000 Life, n = 10 years Annual operating cost, AOC=$-30,000 per year Annual revenue, R = $70,000 per year MARR = 15% per year
What is the cost, c, of a call of m minutes duration? Write the equation in both point-slope and slope-intercept form.
Consider two assets with expected return R1=0.22,R2=0.55and variance are s1=0.80, s2=0.88 and r12=0.55 respectively.A portifolio with weights W1=0.25 and W2= 0.65 is formed calculate the expected return and variance of the portifolio