EBK PRODUCTION AND OPERATIONS ANALYSIS
EBK PRODUCTION AND OPERATIONS ANALYSIS
7th Edition
ISBN: 9781478628385
Author: Olsen
Publisher: WAVELAND PRESS (ECONTENT)
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Chapter 12.2, Problem 11P

a

Summary Introduction

Interpretation:The value ofa for the control chart is to be calculated.

Concept Introduction:Control charts are used to measure the effectiveness of the process determining the average value and control limits of the process. The Upper Control Limit (UCL) is the larger value and the Lower Control limit (LCL) is the smaller value of the sample. These limits gives a range to the data available.

b

Summary Introduction

Interpretation:The value of UCL and LCL based on three − sigma limits are to be calculated.

Concept Introduction:Control charts are used to measure the effectiveness of the process determining the average value and control limits of the process. The Upper Control Limit (UCL) is the larger value and the Lower Control limit (LCL) is the smaller value of the sample

c

Summary Introduction

Interpretation:The probability that the shift is detected on the first subgroup after the shift has occurred is to be determined.

Concept Introduction:Control charts are used to measure the effectiveness of the process determining the average value and control limits of the process. The Upper Control Limit (UCL) is the larger value and the Lower Control limit (LCL) is the smaller value of the sample

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Arana is a company that produces homemade Rotini pasta. They use statistical process control to monitor the manufacturing process. The company collects five samples, each containing six packs of pasta. Below is the sample data, but the standard deviation of the process output is unknown. If an R chart is created using three-sigma limits (i.e., z = 3) to monitor the variability of products, what would be the upper control limit for this R chart? Sample 1 Sample 2 Sample 3 Pack 1 452.3 451.6 448.6 Sample 4 454.7 Sample 5 448.9 7.614 9.328 11.653 13.427 Pack 2 452.8 451.2 455.6 451.7 453.4 Pack 3 456 454.6 456.5 451 456.7 Pack 4 457.2 455.3 451.9 452.6 456.3 Pack 5 457.8 452.2 455.6 454.7 452.4 Pack 6 451.8 451.9 448.3 458.4 456
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
Refer to Table S6.1 - Factors for Computing Control Chart Limits (3 sigma) for this problem. Twelve samples, each containing five parts, were taken from a process that produces steel rods at Emmanual Kodzi's factory. The length of each rod in the samples was determined. The results were tabulated and sample means and ranges were computed. The results were: Sample Mean (in.) Range (in.) Sample Sample Sample Mean (in.) Range (in.) 1 9.404 0.044 7 9.403 0.021 2 9.402 0.051 8 9.405 0.058 3 9.393 0.042 9.395 0.039 4 9.404 0.037 10 9.401 0.038 9.399 0.048 11 9.401 0.054 9.397 0.053 12 9.404 0.061 For the given data, the x = inches (round your response to four decimal places). Based on the sampling done, the control limits for 3-sigma x chart are: Upper Control Limit (UCL;) = inches (round your response to four decimal places). Lower Control Limit (LCL;) = inches (round your response to four decimal places).
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