6 Sample RangeThe following table provides analysis output from a process control and process capability analysisdone using Minitab® for a soft drink bottling operation.Xbar ChartCapability HistogramUCL-12.0012712.0012.06412.04LCL-12.0572151712.000 12.016 12.0 1204 12.004 12.000 12.0 12.i219R ChartNormal Prob PlotAD: 1.226, P: <0.005UCLHO.12010.100.05-0.00LCL-015 1712.0012.0512.101215Last 20 SubgroupsCapability PlotWthinWthinStDev 0.02442830.68OveralSDev 0.02952512.00CpCpkCCpk0.712.06Overal0.570.58PokCpmSpecs12.03-0.680.6610SampleInterpreting the relevant information from this output, please provide a yes/no decision on whetherthe process is in statistical control and please list the specific aspects from the output that you usedto make your decision.

A process is supposed to be in control or stable, assuming that it is in factual control. A process…

Answered: Valuns Sample Mean Sample Range The…

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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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)
The following table contains the measurements of the key length dimension from a fuel injector. These samples of size five were taken at one-hour intervals. Use three-sigma control limits. Use Exhibit 10.13. SAMPLE NUMBER OBSERVATIONS 1 2 3 4 5 1 0.486 0.499 0.493 0.511 0.481 2 0.499 0.506 0.516 0.494 0.529 3 0.496 0.500 0.515 0.488 0.521 4 0.495 0.506 0.483 0.487 0.489 5 0.472 0.502 0.526 0.469 0.481 6 0.473 0.495 0.507 0.493 0.506 7 0.495 0.512 0.490 0.471 0.504 8 0.525 0.501 0.498 0.474 0.485 9 0.497 0.501 0.517 0.506 0.516 10 0.495 0.505 0.516 0.511 0.497 11 0.495 0.482 0.468 0.492 0.492 12 0.483 0.459 0.526 0.506 0.522 13 0.521 0.512 0.493 0.525 0.510 14 0.487 0.521 0.507 0.501 0.500 15 0.493 0.516 0.499 0.511 0.513 16 0.473 0.506 0.479 0.480 0.523 17 0.477 0.485 0.513 0.484 0.496 18 0.515 0.493 0.493 0.485 0.475 19 0.511 0.536 0.486 0.497 0.491 20 0.509 0.490 0.470 0.504 0.512 Calculate the mean and range for the above samples.…
Janice Sanders, CEO of Pine Crest Medical Clinic, is concerned over the number of times patients must wait more than 30 minutes beyond their scheduled appointments. She asked her assistant to take random samples of 64 patients to see how many in each sample had to wait more than 30 minutes. Each instance is considered a defect in the clinic process. The table below contains the data for 15 samples.Sample Number of Defects1 52 23 14 35 16 57 28 3 9 6 10 3 11 9 12 9 13 5 14 2 15…
A production manager at a Contour Manufacturing planthas inspected the number of defective plastic molds in 5 randomsamples of 20 observations each. Following are the number ofdefective molds found in each sample:SampleNumber ofDefectsNumber ofObservationsin Sample11202220322041205020Total 6 100Construct a 3-sigma control chart (z 3) with this information
A medical facility does MRIs for sports injuries. Occasionally a test yields inconclusive results andmust be repeated. Using the following sample data and n = 200, determine the upper and lowercontrol limits for the fraction of retests using two-sigma limits. Is the process in control?SAMPLE1 2 3 4 5 6 7 8 9 10 11 12 13Number of retests 1 2 2 0 2 1 2 0 2 7 3 2 1
Aspen Plastic produce plastic bottles to customer order. The quality inspector randomly selects four-bottles from the bottle machine and measures the outside diameter of the bottle neck. a critical quality dimension that determines whether the bottle cap will fit properly. The dimensions (in Inches) from the last six sampes are Bottle Sample 1 2 3 4 1 0.594 0.622 0.598 0.590 2 0.587 0.611 0.597 0.613 3 0.571 0.580 0.595 0.602 4 0.610 0.615 0.585 0.578 5 0.580 0.624 0.618 0.614 6 0.585 0.593 0.607 0.569 Assume only these six samples are sufficient, and use the data to determine control limits for an R- and an X-chart
Webster Chemical’s nominal weight for filling tubes of caulk is 8.00 ounces ± 0.60 ounces. The target process capability ratio is 1.33. The current distribution of the filling process is centered on 8.054 ounces with a standard deviation of 0.192 ounces. Compute the process capability ratios Cp and Cpk to assess whether the filling process is capable and set properly.
Using samples of 200 credit card statements, an auditor found the following:Sample 1 2 3 4Number with errors 4 2 5 9a. 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?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 arethe 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 twosigma control limits. Is the process in control?
Make an np chart for the following data: n non-conforming 400 12 400 10 400 8 400 14 400 21 400 16 400 18 400 15 400 12 400 17
Jim’s Outfitters, Inc., makes custom fancy shirts for cowboys. The shirts could be flawed in various ways, including flaws in the weave or color of the fabric, loose buttons or decorations, wrong dimensions, and uneven stitches. Jim randomly examined 10 shirts, with the following results:Shirt Defects1 82 03 74 125 56 107 28 49 610 6a. Assuming that 10 observations are adequate for these purposes, determine the three-sigma control limits for defects per shirt.b. Suppose that the next shirt has 13 flaws. What can you say about the process now?
"The table below is data on telephone usage time by operators to serve customer requests that will be used to explain the use of Xbar and R-chart". Question: a. Create UCL and LCL with Limit Control Factor A2b. Create UCL and LCL with Limit Control Factor D3 and D4
Statistical process control (SPC) is a quality-control technique that primarily involves using statistics _____. A. To monitor production quality during the production process B. To improve the production quality of products C. To look fo defects in the random sampling process D. To find out ways to limit defects to 30,400 per million operations

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