Exam 21: Statistical Process Control

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Assembly Line Random samples of 200 parts were taken on an assembly line every hour for the past 25 hours.The number of defective parts is shown in the accompanying table. Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 Number af Defectives 5 2 4 10 2 6 8 2 0 5 12 11 Sample 14 15 16 17 18 19 20 21 22 23 24 25 Number of Defective5 10 5 13 7 5 7 11 3 16 3 2 10 -{Assembly Line Narrative} Calculate the centerline and control limits for the p chart.

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Samples Production The mean of the sample means and the pooled standard deviation of 40 samples of size 8 taken from a production process under control are xˉˉ=215.6\bar{\bar { x } }= 215.6 ,and S = 14.5,respectively. -{40 Samples Production Narrative} Calculate the centerline and control limits for the xˉ\bar { x } chart.

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For an xˉ\bar { x } chart,the lower and upper control limits are usually set at three standard errors from the centerline.

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What do you look for to determine when a process is in a state of statistical control?

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The mean of the sample means and the pooled standard deviation of 40 samples of size 5 taken from a production process under control are found to be 400 and 15,respectively.The lower control limit for the xˉ\bar { x } chart is:

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The lower control limit for the xˉ\bar { x } ,p,and R charts must be zero or above.

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To ensure that a manufacturing process is under control,40 samples of size 900 were drawn,and the number of defectives in each sample was counted.The mean of the sample proportion was .025.Then,the lower and upper control limits for the p chart are .0094 and .0406,respectively.

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Diaper Delivery Wrap-M-Up,a Ft.Lauderdale diaper Service,has 10 delivery men who each deliver diapers to 50 customers every day.Wrap-M-Up decides to record the proportion of diapers delivered on time for a 10-day period and construct a p chart to see whether the proportion is too erratic.The data are shown below: Day 1 2 3 4 5 6 7 8 9 10 Prapartion of Dingers .916 .894 .928 .900 .864 .968 .914 .988 .952 .936 Delivered an Time -{Diaper Delivery Narrative} Find the numerical value of the lower control limit for the p chart.

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____________________ is the term used when the standard deviation of a process distribution increases.

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In statistical process control,a Type II error occurs if we conclude that the process is in control when it actually isn't.

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If a p chart finds fourteen sample proportions in a row that alternate up and down,this could be an example of assignable cause variation called a(n)____________________.

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The process capability index is defined as Cp = (USL - LSL)/ 6,where USL and LSL are the upper and lower specification limits.

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A malfunction in the process goes unnoticed and later causes great expense in terms of operator and machine downtime.What type of error was caused here and how could it be decreased?

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When estimating the population standard deviation,you typically use the sample standard deviations.However,for a variety of reasons,statistical process control frequently uses the ____________________ instead of the standard deviation.

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Samples Manufacturing The mean of the sample means and the pooled standard deviation of 40 samples of size 5 taken from a production process under control are xˉ=518.7\bar { x } = 518.7 ,and S = 11.5,respectively. -{40 Samples Manufacturing Narrative} Suppose you take a sample of size 5 and find the mean to be 502.80.What do you conclude?

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When the purpose of sampling is to detect when a process becomes too variable,the control chart of choice will be an S chart.

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A process capability index (Cp)of 2.0 describes a production process where the specification limits are equal to 3 standard errors above and below the centerline.

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In statistical process control,a Type I error occurs if we conclude that the process is in control when it actually isn't.

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What is the average run length (ARL)until an xˉ\bar { x } control chart signals a false alarm if the control limits are set at ±\pm 2.5 standard errors from the centerline?

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The lower and upper control limits for the p chart are based on the standard deviation of the process.

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