57. A manufacturer of large appliances maintains a p chart for the production of washingmachines. The machines may be rejected because of cosmetic or functional defectives.Based on sampling 30 machines each day for 50 consecutive days, the current estimateof p is .0855.a. What are the control limits for a p chart? (Assume 3ơ limits.)b. Suppose that the percentage of defective washing machines increases to 20 per-cent. What is the probability that this shift is detected on the first day after itoccurs?c. On average, how many days would be required to detect the shift?

Hence, the UCL and LCL are 0.2387 and 0.

Answered: 57. A manufacturer of large appliances…

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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Jamison Kovach Supply Company manufactures paper clips and other office products. Although inexpensive, paper clips have provided the firm with a high margin of profitability. Sample size is 50. Results are given for the last 10 samples. Sample 1 2 3 4 5 6 7 8 9 10Defectives 5 8 3 5 6 5 5 4 1 11 a) Establish the control limits to include of the random variation in defectives. UCLp = [ ? ] (enter your response as a number between 0 and 1, rounded to three decimal places). LCLp = [ ? ] (enter your response as a number between 0 and 1, rounded to three decimal places). c) If the sample size were 100 instead, how would your limits and conclusions change? UCLp = [ ? ] (enter your response as a number between 0 and 1, rounded to three decimal places). LCLp = [ ? ] (enter your response as a number between 0 and 1, rounded to three…
14. A manufacturer of photographic film produces an average of 12,000 rolls of vari- ous types of film each day. An inspector samples 25 from each day's production and tests them for accuracy of color reproduction and overall film quality. During 12.3 Control Charts for Attributes: The p Chart 687 23 consecutive production days, the inspector rejected the following numbers of rolls of film: Day Number Rejected Day Number Rejected 1 2 13 1 2 3 3 14 1 15 16 4 1 3 17 4 18 2 3 7 7 19 8 20 21 22 1 1 2 2 10 11 23 1 12 a. Based on these observations, compute three-sigma limits for a p chart. b. Do any of the points fall outside the control limits? If so, recompute the three-sigma limits after eliminating the out-of-control points. mm
Management at Webster Chemical Company is concerned as to whether caulking tubes are being properly capped. If a significant proportion of the tubes are not being sealed, Webster is placing its customers in a messy situation. Tubes are packaged in large boxes of 135. Several boxes are inspected, and the following numbers of leaking tubes are found: View an example Sample 1 2 3 Get more help. 4 Tubes 7 7 8 5 1 5 6 7 Calculate p-chart three-sigma control limits to assess whether the capping process is in statistical control. The UCL, equals 1 Sample 8 8 9 10 11 12 13 14 Tubes 7 2 4 8 6 9 MacBook Pro 3 Sample 15 16 17 18 19 20 Total Tubes 8 3 3 5 and the LCL equals (Enter your responses rounded to three decimal places. If your answer for LCL, is negative, enter this value as 0.) 3 6 104 Clear all Check answer O
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.
2) The specification for a Lindemann’s stainless steel chimney liner requires a thickness of 7.1 mm ± 0.1 mm. The firm’s quality analyst determines that the liner process operates at a mean thickness of 7.13 mm with the standard deviation of the process being 0.02 mm. a) Calculate the upper and the lower limits for the stainless steel chimney liner. b) Calculate the Cpand Cpkfor this process. Hint: Cp = (Upper Specification Limit – Lower Specification Limit)/6sigma Cpk = minimum of [(Upper Specification Limit – Xbar)/3sigma], [(Xbar – Lower Specification Limit)/3sigma]
A normally distributed process uses 66.7% (i.e. the +/- 3 ? from the mean) ofthe specification band. It is centered at the nominal dimension, located halfway between theupper and lower specification limits.(a) Estimate Cp and Cpk Interpret these ratios.(b) What fallout level (fraction defective) is produced?
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 excel
Suppose you constructed control charts for the time spent by customers in a retail checkout lane, computing UCL, CL, and LCL based upon a large number of historical observations. Using those control limits, you decide to plot the most recent 12 data points as shown below. Given the following range chart, which general conclusion is most appropriate? (link to image here). Range Chart Sample Range 140 120 100 80 60 40 20 0 1 2 3 4 5 6 7 Sample Number 8 The process is capable The process is not capable The process is in control The process is out of control 9 10 11 12
73) please please help me with this question I don't know how to do it A metal fabricator produces connecting rods with an outer dlameter that has a 1 0.05 inch specification. A machine operator takes several sample measurements over time and determines the sample mean outer diameter to be 1.004 inches with a standard deviation of 0.020 inch. Calculate the process capability index for this example. Note: Round your answer to 3 decimal places.
1. An ad agency tracks the complaints, by week received, about the billboards in its city: Week No. of Complaints 1 8 2 4 3 11 4 16 5 8 6 9 This exercise contains only parts a, b, and c. a) The type of control chart that is best to monitor this process is c minus chartc−chart . b) Using z = 3, the control chart limits for this process are (assume that the historical complaints rate is unknown): UCLc =?complaints per week (round your response to two decimal places). LCLc =?complaints per week (round your response to two decimal places).
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 0.061
3.6. One of the stages in the process of making denim cloth at the Southern Mills Company is to spin cotton yarn onto spindles for subse- quent use in the weaving process. Occasionally the yarn breaks during the spinning process, and an operator ties it back together. Some num- ber of breaks is considered normal; however, too many breaks might mean that the yarn is of poor quality. In order to monitor this process, the quality-control manager randomly selects a spinning machine each hour and checks the number of breaks during a 15-minute period. Following is a summary of the observations for the past 20 hours: Number of Number of Sample Breaks Sample Breaks 1 3 11 3 2 12 4 3 4 13 4 1 14 7 5 15 8. 16 7 17 4 18 7. 8 19 8 9. 20 6. 10 Construct a c-chart using 3ơ limits for this process and indicate if the process was out of control at any time. ohoin when orders come into 3. 6

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