Problem 10-4 (Static)Software upgrade times (in minutes) are being evaluated. Samples of five observations each have been taken, and the results are aslisted.179.278.880.078.481.0Number ofObservationsin Subgroup,n2456789Click here for the Excel Data FileFactors for three-sigma control limits for and Rcharts101113121314SAMPLE24380.5 79.6 78.978.781.0 80.4 79.779.6 79.480.479.480.180.615161718192080.380.8Factor forI Chart,A21.881.020.730.580.480.425680.579.779.680.680.4 80.580.8 80.078.881.10.370.340.310.290.270.250.240.220.210.200.190.190.18FACTORS FOR R CHARTSLowerUpperControlLimit,D3ControlLinit,D43.272.572.282.112.001.921.861.821.781.741.721.691.671.651.641.621.611.601.59080000.080.140.180.220.260.280.310.330.350.360.380.390.400.41 a. Using factors from above table, determine upper and lower control limits for mean and range charts. (Round your intermediatecalculations and final answers to 2 decimal places. Leave no cells blank - be certain to enter "0" wherever required.)UCLLCLMean ChartRange Chartb. Decide if the process is in control.O The process is in control.O The process is not in control.

A control chart is a statistical tool which helps to identify the process controllability using…

Answered: a. Using factors from above table,…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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4. Problem 8.29 The number of imperfections in bond paper produced by a paper mill is observed over a period of several days. Table 8-28 shows the area inspected and the number of imperfections for 25 samples. Construct a control chart for the number of imperfections per square meter. Revise the limits, if necessary, assuming special causes for the out-of-control points. TABLE 8-28 Area Area Sample Inspected (m?) Imperfections Sample Inspected (m²) Imperfections 1 150 6 14 300 8 2 100 8 15 300 12 3 200 5 16 200 6 4 150 4 17 150 4 250 10 18 200 7 6. 100 11 19 150 14 7 150 20 100 4 8 200 5 21 100 8 9 300 10 22 200 10 250 10 23 300 12 11 100 24 250 7 12 200 4 25 200 5 13 250 12
The operations manager of thebooking services departmentof Hometown Bank is concerned about the number ofwrong customer account numbers recorded by Hometownpersonnel. Each week a random sample of 2,500 depositsis taken, and the number of incorrect account numbers is recorded. The results for the past12 weeks are shown in thefollowing table. Is the bookingprocess out of statistical control? Use three-sigma controllimits, which will provide a typeI error of 0.26 percent.
Auto 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= 156.76 mm (round your response to two decimal places). b) What is the value of R? Day 1 2 3 4 5 Mean x (mm) 158.9 155.2 155.6 157.5 156.6 R = 4.40 mm (round your response to two decimal places). c) What are the UCL and LCL using 3-sigma? Upper Control Limit (UCL) = mm (round your response to two decimal places). Range R (mm) 4.2 4.4 4.3 4.8 4.3 Ç
Auto 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= mm (round your response to two decimal places). Day 1 2 3 4 5 Mean x (mm) 158.9 155.2 155.6 157.5 156.6 Range R (mm) 4.2 4.4 4.3 4.8 4.3
BlueMoon Bottlers has a bottle-filling process with a mean value of 64 ounces and a standard deviation of 8 ounces. Suppose the upper and lower specification limits are 71 and 57 ounces, respectively. What is the process capability index of this process? (Note: You MUST show every single step and detailed derivation for full credit)
6. A critical dimension of the service quality of a deposit collection booth is the waiting time of atransaction to get money from the employee. Periodically, random samples of four customer aremeasured for waiting time. The results of the last five samples are in the following table:Sample Time (sec) from Four Customers1 525 510 495 5142 512 520 508 5243 505 458 504 5054 450 495 521 5125 498 510 480 521Required:i. Assuming that the management is willing to use three-sigma control limits and using onlyhistorical information of the standard deviation of the process distribution is 6.85 thatcontained in the five samples, show that the ATM Booth waiting time is in statistical control.ii. Suppose that the standard deviation of the process distribution is 6.85. If the specification forthe waiting time are 510±35sec., is the process capable? Why or why not? Assume Threesigma performance is desired by the management.
Production phase After the pre-production phase, the product entered the production phase without introducing any changes in the process. Since it seemed to be stable SPC was not performed for several months, with process stability and variability being assessed by the level of nonconformities it it produced. However, after a time, an increasing number of customer complaints due to products supplied outside the specification/. The Quality Engineer decided to take 20 samples from the process with regular spacing between samples. Each sample is made up of 3 parts. The data obtained for the highlighted dimension samples are presented in Table 2 below: measurements in mm for critical sample dimension number 1 2 3 4 5 6 7 8 9 Observations 2 3 50.767 1 50.972 50.785 50.956 50.97 50.914 51.066 50.933 51.086 50.917 51.081 51.092 50.948 50.828 51.054 50.859 51.083 50.789 50.984 50.961 50.943 51.013 51.02 50.734 50.898 50.956 50.885 51.004 50.984 50.839 Table 2: Measurements in mm for critical…
. Inspection results of video-of-the-month shipments to customers for 25 consecutive days are given in the following table. What central line and control limits should be established and posted if it is assumed that any out of-control points have assignable causes? The number of inspections each day is constant and equals 1750. Date Nonconforming Date Nonconforming July 6 47 July 23 37 7 42 26 39 8 48 27 51 9 58 28 44 12 32 29 61 13 38 30 48 14 53 Aug 2 56 15 68 3 48 16 45 4 40 19 37 5 47 20 57 6 25 21 38 9 35 22 53
In a sausage factory, quality managers are studying the compliance of the sausages with the requirements. Any sausage having pin holes, air pockets, deformation or breakage in its casings is counted as defective and total number of such defective sausages alone is noted in each shift. The following data represents the number of defective sausages in samples of 200 sausages taken from 10 shifts. Sample Defectives Percent Defective 1 40 20% 2 28 14% 3 15 8% 4 23 (a) 5 20 10% 6 21 11% 7 19 10% 8 15 8% 9 16 8% 10 17 9% Calculate the value for (a) in the table above. Calculate p-bar based on the samples above. What is the UCL and LCL for a p chart based on the data provided and a desired control level of 99.74%? Use your control limits from part b along with the data provided to draw a p-chart. Is the process in control? Why or why not? If not in control, suggest some potential reasons.
standard Deviation (σ) = SQRT(Variance) = SQRT(6) = 2.45 This is not clear for me. How did you do it?
A shirt manufacturer buys clothes by the 100-yard roll from a supplier. For setting a control chart to manage the irregularities (e.g., loose threads and tears), the following data were collected from a sample provided by the supplier. Sample 1 2 3 4 5 6 7 8 9 10 Irregularities 3 5 2 6 5 4 6 3 4 5 Which type of control chart should be used? Construct a control chart with two-sigma control limits. Suppose the next five rolls from the supplier had three, two, five, three, and seven irregularities. Is the supplier process under control? Explain and show work
A process is in statistical control with = 202,5 y s = 2,0. Specifications are atLSL = 196 and USL = 206.a) Estimate the process capability with an appropriate process capability ratio.b) What is the potential capability of this process?c) Items that are produced below the lower specification limit must bescrapped, while items that are above the upper specification limit can bereworked. What proportion of the process output is scrap and whatproportion is rework?d) Because scrap is more expensive than rework, the process has been centered closer to the upper specification limit. If scrap is twice as expensive as rework, is the process mean at the best possible location? What value of the process target would you recommend?

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