Concept explainers
a)
To determine: The mean of each sample.
a)
Answer to Problem 20P
Explanation of Solution
Given information:
Sample | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Calculation of mean of each sample:
Sample | ||||
Sl. No. | 1 | 2 | 3 | 4 |
1 | 4.5 | 4.6 | 4.5 | 4.7 |
2 | 4.2 | 4.5 | 4.6 | 4.6 |
3 | 4.2 | 4.4 | 4.4 | 4.8 |
4 | 4.3 | 4.7 | 4.4 | 4.5 |
5 | 4.3 | 4.3 | 4.6 | 4.9 |
Mean | 4.3 | 4.5 | 4.5 | 4.7 |
Table 1
Excel Worksheet:
Sample 1:
The mean is calculated by adding each sample points. Adding the points 4.5, 4.2, 4.2, 4.3 and 4.3 and dividing by 5 gives mean of 4.3. The same process is followed for finding mean for other samples.
Hence, the mean of each sample is shown in Table 1
b)
To determine: The mean and standard deviation when the process parameters are unknown.
b)
Answer to Problem 20P
Explanation of Solution
Given information:
Sample | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Calculation of mean and standard deviation:
Table 1 provides the mean for each sample points.
The mean is calculated by adding each mean of the samples. Adding the points 4.3, 4.5, 4.5 and 4.7 and dividing by 4 gives mean of 4.5.
The standard deviation is calculated using the above formula and substituting the values of mean in the above formula and the resultant of 0.192 is obtained.
Hence, the mean and standard deviation when the process parameters are unknown are 4.5 and 0.192.
c)
To determine: The mean and standard deviation of the sampling distribution.
c)
Answer to Problem 20P
Explanation of Solution
Given information:
Sample | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Calculation of mean and standard deviation of the sampling distribution:
From calculation of mean of each samples, the mean for sampling distribution can be computed, the mean for sampling distribution is 4.5 (refer equation (1)).
The standard deviation of the sampling distribution is calculated by dividing 0.192 with the square root of 5 which gives the resultant as 0.086.
Hence, the mean and standard deviation of the sampling distribution is 4.5 and 0.086 respectively.
d)
To determine: The three-sigma control limit for the process and alpha risk provided by them.
d)
Answer to Problem 20P
Explanation of Solution
Given information:
Sample | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Calculation of three-sigma control limit for the process:
The three-sigma control limits for the process is calculated by multiplying 3.00 with 0.086 (refer equation (2)) and the resultant is added with 4.5 to get an upper control limit which is 4.758 and subtracted to get lower control limit which is 4.242. Using z-factor table z = +3.00 corresponds to 0.4987.
The alpha risk is calculated to be as 0.0026.
Hence, the three-sigma control limits for the process are 4.758 and 4.242.
e)
To determine: The alpha risk for control limits of 4.14 and 4.86.
e)
Answer to Problem 20P
Explanation of Solution
Given information:
Sample | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Formula:
Calculation alpha risk for control limits of 4.14 and 4.86:
The alpha risk is calculated by dividing the difference of 4.86 and 4.5 with 0.086 which gives +4.19 which is the risk is close to zero.
Hence, the alpha risk for control limits of 4.14 and 4.86 is +4.1
f)
To determine: Whether any of the sample means are beyond the control limits.
f)
Answer to Problem 20P
Explanation of Solution
Given information:
Sample | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Determination of whether any of the sample means are beyond the control limits:
Table 1 provides the sample means for each sample. From observation, it can be found that each sample mean are within the control limit of 4.14 and 4.86. Therefore, each sample means lies within the control limits of 4.14 and 4.86.
Hence, there are no sample means which lies beyond the control limits.
g)
To determine: Whether any of the samples are beyond the control limits.
g)
Answer to Problem 20P
Explanation of Solution
Given information:
SAMPLE | |||
1 | 2 | 3 | 4 |
4.5 | 4.6 | 4.5 | 4.7 |
4.2 | 4.5 | 4.6 | 4.6 |
4.2 | 4.4 | 4.4 | 4.8 |
4.3 | 4.7 | 4.4 | 4.5 |
4.3 | 4.3 | 4.6 | 4.9 |
Formula:
Mean Chart:
Range Chart:
Calculation of upper and lower control limits:
SAMPLE | ||||
1 | 2 | 3 | 4 | |
4.5 | 4.6 | 4.5 | 4.7 | |
4.2 | 4.5 | 4.6 | 4.6 | |
4.2 | 4.4 | 4.4 | 4.8 | |
4.3 | 4.7 | 4.4 | 4.5 | |
4.3 | 4.3 | 4.6 | 4.9 | |
Mean | 4.3 | 4.5 | 4.5 | 4.7 |
Range | .3 | .4 | .2 | .4 |
From factors of three-sigma chart, A2 = 0.58; D3 = 0; D4 = 2.11.
Mean control chart:
Upper control limit:
The Upper control limit is calculated by adding the product of 0.58 and 0.325 with 4.5 which yields 4.689.
Lower control limit:
The Lower control limit is calculated by subtracting the product of 0.58 and 0.325 with 4.5 which yields 4.311.
The UCL and LCL for mean charts are 4.686 and 4.311. (4)
A graph is plotted using the UCL and LCL and mean values which shows the points are within the control limits.
Range control chart:
Upper control limit:
The Upper control limit is calculated by multiplying 2.11 with 0.325 which yields 0.686.
Lower control limit:
The lower control limit is calculated by multiplying 0 with 0.325 which yields 0.0.
A graph is plotted using the UCL, LCL and Range values which shows that the points are within the control region.
Hence, all points are within control limits.
h)
To explain: The reason for variations in control limits.
h)
Answer to Problem 20P
Explanation of Solution
Reason for variations in control limits:
The control limits vary because in equation (3) and (4) because of the use of different measure for dispersion to measure the standard deviation and range.
Hence, the difference arises due to the use of different measures for dispersion to the measure the standard deviation and range.
i)
To determine: The control limits for the process and whether the process will be in control.
i)
Answer to Problem 20P
Explanation of Solution
Given information:
Determination of control limits of the process:
Sample mean is given in Table 1.
To calculate the control limits 0.18 is divided by root of 5 and is multiplied by 3 and the resultant is added to 4.4 to give UCL which is 4.641 and subtracted from 4.4 to get the LCL which is 4.159.
The graph shows that the some of the points are above the control limits which make the process to be out of control.
Hence, the process is out of control with UCL=4.641 and LCL=4.159.
Want to see more full solutions like this?
Chapter 10 Solutions
OPERATIONS MANAGEMENT W/ CNCT+
- Using samples of 200 credit card statements, an auditor found the following: Sample 1 2 3 4 Number with errors 4 2 5 9 a. Determine the fraction defective in each sample. b. If the true fraction defective for this process is unknown, what is your estimate of it? c. What is your estimate of the mean and standard deviation of the sampling distribution of fractions defective for samples of this size? d. What control limits would give an alpha risk of .03 for this process? Page 457 e. What alpha risk would control limits of .047 and .003 provide? f. Using control limits of .047 and .003, is the process in control? g. Suppose that the long-term fraction defective of the process is known to be 2 percent. What are the values of the mean and standard deviation of the sampling distribution? h. Construct a control chart for the process, assuming a fraction defective of 2 percent, using two-sigma control limits. Is the process in control? Can you show me the steps and formulas using excelarrow_forwardplease answer in 30 mins.arrow_forwardAuto pistons at Wemming Chung's plant in Shanghai are produced in a forging process, and the diameter is a critical factor that must be controlled. From sample sizes of 5 pistons produced each day, the mean and the range of this diameter have been as follows: Day Mean (mm) Range R (mm) 158 4.3 151.2 4.4 155.7 4.2 153.5 4.8 156.6 4.5 What is the UCL using 3-sigma?(round your response to two decimal places). 1. 2. 4.arrow_forward
- A machine is used to fill cans of motor oil additive. A single sample can is selected every hour and the net weight of the can is obtained. Since the filling process is automated, it has very stable variability, and long experience indicates that s = 0.02 oz. The process target (process mean when in control) is 8.02 oz. A tabular cusum is being used for this process with standardized values h=4.5 and k=0.5. If the values of Cumulative sums at the end of measurement 7 were C," + = 0.030 and C,¯ = 0.0 , and measurement 8 is equal to Xg = 8.071, what will be the Cumulative sum at the end of measurement 8, that is C3 + = ? 0.041 0.071 0.051 0.046 0.061arrow_forwardsniparrow_forwardThe overall average on a process you are attempting to monitor is 60.0 units. The process population standard deviation is 1.72. Sample size is given to be 4. Part 2 a) Determine the 3-sigma x-chart control limits. Upper Control Limit (UCLx)=enter your response here units (round your response to two decimal places). Part 3 Lower Control Limit (LCLx)=enter your response here units (round your response to two decimal places). Part 4 b) Now determine the 2-sigma x-chart control limits. Upper Control Limit (UCLx)=enter your response here units (round your response to two decimal places). Part 5 Lower Control Limit (LCLx)=enter your response here units (round your response to two decimal places). Part 6 How do the control limits change? A. The control limits are tighter for the 3-sigma x-chart than for the 2-sigma x-chart. B. The control limits for the 2-sigma x-chart and for the 3-sigma x-chart are the same. C. The control limits…arrow_forward
- The temperature of a burrito served to a customer in a local Mexican restaurant A: Discrete B; Continousarrow_forwardAuto pistons at Wemming Chung's plant in Shanghai are produced in a forging process, and the diameter is a critical factor that must be controlled. From sample sizes of 10 pistons produced each day, the mean and the range of this diameter have been as follows: a) What is the value of x? = x= 155.56 mm (round your response to two decimal places). b) What is the value of R? R 4.48 mm (round your response to two decimal places). c) What are the UCL; and LCL; using 3-sigma? Day 1 2 3 4 5 Upper Control Limit (UCL) = 156.94 mm (round your response to two decimal places). Lower Control Limit (LCL-) = 154.18 mm (round your response to two decimal places). d) What are the UCLR and LCLR using 3-sigma? Upper Control Limit (UCL) = 7.96 mm (round your response to two decimal places). Mean x (mm) 154.9 153.2 155.6 155.5 158.6 Range R (mm) 4.0 4.8 3.9 5.0 4.7 Lower Control Limit (LCL) = 1.00 mm (round your response to two decimal places). e) If the true diameter mean should be 155 mm and you want…arrow_forwardThe IRS is concerned with improving the accuracy of tax information given by its representatives over the telephone. Previous studies involved asking a set of 25 questions of a large number of IRS telephone representatives to determine the proportion of correct responses. Historically, the averageproportion of correct responses has been 72 percent. Recently, IRS representatives have been receiving more training. On April 26, the set of 25 tax questions were again asked of 20 randomly selected IRS telephone representatives. The numbers of correct answers were 18, 16, 19, 21, 20, 16,21, 16, 17, 10, 25, 18, 25, 16, 20, 15, 23, 19, 21, and 19. a. What are the upper and lower control limits for the appropriate p-chart for the IRS? Use z = 3. b. Is the tax information process in statistical control?arrow_forward
- Sample size (n) is 16, mean of the sample means ( ) is 15, mean of the sample ranges ( ) is 6, and population standard deviation ( ) is not known. Calculate the UCL and LCL of the mean chart (x-Chart) for this process. Group of answer choices Cannot be calculated UCL=33.0, LCL=-3.0 UCL=13.73, LCL=16.27 UCL=16.27, LCL=13.73 UCL=33.0, LCL=0arrow_forwardAn airline operates a call center to handle customer questions and complaints. The airline monitors a sample of calls to help ensure that the service being provided is of high quality. Ten random samples of 100 calls each were monitored under normal conditions. The center can be thought of as being in control when these 10 samples were taken. The number of calls in each sample not resulting in a satisfactory resolution for the customer is as follows. (a) What is an estimate of the proportion of calls not resulting in a satisfactory outcome for the customer when the center is in control? 0.04 (b) Construct the upper and lower limits for a p chart for the manufacturing process, assuming each sample has 100 calls. (Round your answers to four decimal places.) UCL = 0.0988 ✓ X LCL = 0.0188 (c) With the results of part (b), what conclusion should be made if a sample of 100 has 13 calls not resulting in a satisfactory resolution for the customer? Since p = is outside of ✔✔✔ the control…arrow_forwardDistinguish between a sampling error and a nonsampling error.How can each be reduced?arrow_forward
- Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,Operations ManagementOperations ManagementISBN:9781259667473Author:William J StevensonPublisher:McGraw-Hill EducationOperations and Supply Chain Management (Mcgraw-hi...Operations ManagementISBN:9781259666100Author:F. Robert Jacobs, Richard B ChasePublisher:McGraw-Hill Education
- Purchasing and Supply Chain ManagementOperations ManagementISBN:9781285869681Author:Robert M. Monczka, Robert B. Handfield, Larry C. Giunipero, James L. PattersonPublisher:Cengage LearningProduction and Operations Analysis, Seventh Editi...Operations ManagementISBN:9781478623069Author:Steven Nahmias, Tava Lennon OlsenPublisher:Waveland Press, Inc.