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C. Control Charts - One of 7 Old QC Tools, used in statistical process control (SPC) transferring quality control to production personnel's (closest to process
C. Control Charts - One of 7 Old QC Tools, used in statistical process control (SPC) transferring quality control to production personnel's (closest to process & with responsibility for the process (remember artisan's self-inspection) Measurements of gain in decibels are made on an electronic circuit with the following results. Small samples of size 5 were taken from the process each hour to monitor the process quality. Do the control charts indicate that the process is in control? Interpret the control charts and discuss. a. What is the sample size, n, in this example? b. What is the quality attribute in this example? What is the total number of data in the example? d. What is the number of subgroups in the process study? e. Explain briefly how would you draw a histogram to describe the process using the available data? (Note: You are not required to draw the histogram) f. Why is histogram not suitable in monitoring the process quality? 8. Using the data collected at 10.00 and 11.00 pm, explain what you understand by 'rational subgroup'. h. Determine the current process capability? i. What is your assumption before you can calculate the process capability in 10? j. Explain clearly what is a 'chance cause' using the given example? k. What control charts would you suggest for the production to use? I. Calculate the process average? m. Calculate the process dispersion?| n. Calculate the trial control limits for the data collected? 0. explain clearly why you would like to apply control charts in the process? p. How would you describe the process in the example? Subgroup Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 08:00 09:00 10:00 11:00 12:00 13:00 1 2 3 4 5 6 11.1 9.6 9.7 10.1 12.4 10.1 9.4 10.8 10.0 8.4 10.0 10.2 11.2 10.1 10.0 10.2 10.7 10.2 10.4 10.8 9.8 9.4 10.1 10.2 10.1 11.0 10.4 11.0 11.3 10.1 14:00 7 11.0 11.5 11.8 10.0 11.3 15:00 8 11.2 10.0 10.9 11.3 11.0 16:00 17:00 9 10 10.6 8.3 10.4 10.0 10.5 8.8 10.5 9.5 10.9 9.8 18:00 11 10.6 9.9 10.7 10.2 11.4 14 15 17 Subgroup Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 19:00 20:00 21:00 22:00 23:00 00:00 01:00 02:00 03:00 12 13 16 18 19 20 10.8 10.7 11.3 11.4 10.1 10.7 11.9 10.8 12.4 10.2 10.7 11.4 11.2 10.1 10.7 11.9 10.8 12.4 10.5 10.8 10.4 11.4 9.7 11.2 11.6 11.8 10.8 8.4 8.6 10.6 10.1 9.8 11.2 12.4 9.4 11.0 9.9 11.4 11.1 11.6 10.5 11.3 11.4 11.6 11.9 C. Control Charts - One of 7 Old QC Tools, used in statistical process control (SPC) transferring quality control to production personnel's (closest to process & with responsibility for the process (remember artisan's self-inspection) Measurements of gain in decibels are made on an electronic circuit with the following results. Small samples of size 5 were taken from the process each hour to monitor the process quality. Do the control charts indicate that the process is in control? Interpret the control charts and discuss. a. What is the sample size, n, in this example? b. What is the quality attribute in this example? What is the total number of data in the example? d. What is the number of subgroups in the process study? e. Explain briefly how would you draw a histogram to describe the process using the available data? (Note: You are not required to draw the histogram) f. Why is histogram not suitable in monitoring the process quality? 8. Using the data collected at 10.00 and 11.00 pm, explain what you understand by 'rational subgroup'. h. Determine the current process capability? i. What is your assumption before you can calculate the process capability in 10? j. Explain clearly what is a 'chance cause' using the given example? k. What control charts would you suggest for the production to use? I. Calculate the process average? m. Calculate the process dispersion?| n. Calculate the trial control limits for the data collected? 0. explain clearly why you would like to apply control charts in the process? p. How would you describe the process in the example? Subgroup Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 08:00 09:00 10:00 11:00 12:00 13:00 1 2 3 4 5 6 11.1 9.6 9.7 10.1 12.4 10.1 9.4 10.8 10.0 8.4 10.0 10.2 11.2 10.1 10.0 10.2 10.7 10.2 10.4 10.8 9.8 9.4 10.1 10.2 10.1 11.0 10.4 11.0 11.3 10.1 14:00 7 11.0 11.5 11.8 10.0 11.3 15:00 8 11.2 10.0 10.9 11.3 11.0 16:00 17:00 9 10 10.6 8.3 10.4 10.0 10.5 8.8 10.5 9.5 10.9 9.8 18:00 11 10.6 9.9 10.7 10.2 11.4 14 15 17 Subgroup Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 19:00 20:00 21:00 22:00 23:00 00:00 01:00 02:00 03:00 12 13 16 18 19 20 10.8 10.7 11.3 11.4 10.1 10.7 11.9 10.8 12.4 10.2 10.7 11.4 11.2 10.1 10.7 11.9 10.8 12.4 10.5 10.8 10.4 11.4 9.7 11.2 11.6 11.8 10.8 8.4 8.6 10.6 10.1 9.8 11.2 12.4 9.4 11.0 9.9 11.4 11.1 11.6 10.5 11.3 11.4 11.6 11.9
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