Q9-08 Part 2 Student PDF Quality Control

6/12/20 Developing and Using Control Charts 1. Measuring and Controlling Quality Part 2 — 2. — — 1 Record the sample observations Calculate relevant statistics: averages, ranges, proportions… Plot statistics on chart(s) Determine initial control limits 3. 1 Choose the variable or attribute measureme...

6/12/20 Developing and Using Control Charts 1. Measuring and Controlling Quality Part 2 — 2. — — 1 Record the sample observations Calculate relevant statistics: averages, ranges, proportions… Plot statistics on chart(s) Determine initial control limits 3. 1 Choose the variable or attribute measurement Determine the basis, size, and frequency of sampling Collect Data — MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 9e, © 2014 Cengage Publishing — Compute the upper and lower control limits — Draw the center line (average) and control limits on the chart © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 2 2 Developing and Using Control Charts Control Charts for Variables Data Analyze the chart 4. — — — x-bar and R-charts — x-bar and s-charts — Charts for individuals (x-charts) Determine if it is in control Identify and eliminate out-of-control points and recompute control limits 5. Use for ongoing control — Continue collecting data and plotting on the chart(s) — Stop the process when an out-of-control condition is identified and make necessary corrections or adjustments. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 3 3 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 4 4 Constructing x-bar and R-Charts Estimating Process Capability — Collect k = 25-30 samples, with sample sizes generally between n = 3 and 10 — Estimate of standard deviation using control chart data: — Compute the mean and range of each sample — Compute the overall mean and average range: — Use this estimate in process capability index calculations — Not as accurate as calculating the standard deviation using the complete set of data. — Compute control limits: © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 5 Prepare — 5 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 6 6 1 6/12/20 Case Study: La Ventana Window Company Process Monitoring and Control — After a process is determined to be in control, the charts should be used on a daily basis to monitor performance, identify any special causes that might arise, and make corrections only as necessary. — Workers who run a process should use control charts and need to be trained to use them properly. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. — La Ventana received some complaints about narrow, 7 7 misfitting gaps between the upper and lower window sashes — The plant manager wants to evaluate the capability of a critical cutting operation that he suspects might be the source of the gap problem. — The nominal specification for this cutting operation is 25.500 inches with a tolerance of 0.030 inch. — Inspect five consecutive window panels in the middle of each shift over a 15-day period and recording the dimension of the cut © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 8 8 La Ventana Case Data Control Limit Calculations — n = 5; A2 = 0.577 and D4 = 2.114 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 9 9 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 10 Control Charts Spreadsheet Template © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 11 10 11 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 12 12 2 6/12/20 Using the Template Interpretation — You may need to rescale the vertical axis of the charts to eliminate blank space and make them more visually appealing. See the appropriate Excel help files for the version you are using. This is rarely necessary. — When a sample is deleted from a data set in the templates, do not enter zero for the data; instead, leave the cells blank (just delete the data using the (“delete” key). The charts are set up to interpolate between non-missing data points. — When deleting sample data, be sure to update the number of samples used in the calculations to compute the statistics or the control charts will not display correctly. — Sample 24 out of control in R-chart — Samples 9, 21, and 24 out of control in x-bar chart — Common characteristic: Shane was process operator — Attribute results to special cause variation and delete these samples — New control limits © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 13 13 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 14 New Production Data Revised Control Charts © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 15 15 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 16 16 Example Spreadsheet Modifications Using Templates with Additional Data — When adding additional data to the spreadsheet template In cell C9, change the formula to read: =SUMIF(B13:AE13,“>-99999”,B23:AE23)/$E$6. — C10 should be changed to: =SUMIF(B13:AE13,“>99999”,B28:AE28)/$E$6. — but to maintain the established control limits, do not change the number of samples in cell E6 on which the control limits were based. — Also, you must modify the formulas in cells C9 and C10 for the calculations of the grand average and average range to use only the column range of the original data so as not to change the calculated center lines or control limits. — The template will still chart all the data, but use control limits established from the original samples. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 17 14 17 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 18 18 3 6/12/20 Charts with Additional Data x-Bar and s-Charts — Standard deviation — s-chart control limits Increased variation — x-bar chart control limits Upward trend in average © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 19 19 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 20 20 Spreadsheet Template Charts for Individuals — Applications — Sampling from a homogeneous mixture — Low volume operations — Control limits for x-chart — Control limits for moving range-chart © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 21 21 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 22 Example 8.17 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 23 22 Charts 23 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 24 24 4 6/12/20 Fraction Nonconforming (p) Chart Charts for Attributes — Collect k samples. Let yi represent the number of nonconforming units in sample i, and ni be the size of sample i. — Compute the fraction nonconforming in each sample, pi = yi /ni — A nonconformance (defect, error) is a single nonconforming quality characteristic of a unit of work. — If a unit of work has one or more nonconformances, we term the entire unit nonconforming. — Attribute charts are used for monitoring nonconformances as well as the number nonconforming © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. — Average fraction nonconforming — Compute standard deviation — Control limits 25 25 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 26 26 Example 8.18 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. Spreadsheet Template 27 27 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 28 28 Variable Sample Size p-Chart — The p-chart will have control limits that vary with the sample size — Example © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 29 29 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 30 30 5 6/12/20 Example Spreadsheet Template © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. p-Chart With Variable Sample Size 31 31 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 32 32 p-Chart With Average Sample Size p-Chart with Average Sample Size — Use the average sample size (n-bar) to compute approximate control limits — Use the average sample size method when the sample sizes fall within 25 percent of the average. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 33 33 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 34 np-Charts for Number Nonconforming np-Chart Calculations — Average number of nonconforming items per sample (np) — Number nonconforming is easier to understand and work with than fraction nonconforming — Sample size must be constant — Only difference from p-chart is scale; form of the chart will be exactly the same © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 35 34 — Standard deviation (here, p = np/n) — Control limits 35 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 36 36 6 6/12/20 Spreadsheet Template Example 8.21 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 37 37 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 38 38 c-Chart for Nonconformances Per Unit Example — Collect samples of equal size and count the number of nonconformances — Compute the average number of nonconformances per unit, c-bar — Standard deviation — Control limits © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 39 39 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 40 40 u-Chart for Nonconformances Per Unit Spreadsheet Template — Applies if the samples are of unequal size — Collect samples and count the number of nonconformances — Compute the average number of nonconformances per unit, u-bar — Standard deviation — Control limits © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 41 41 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 42 42 7 6/12/20 Spreadsheet Template Example © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 43 43 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 44 Control Chart Selection Control Chart Formula Summary © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 45 45 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 46 46 Control Chart Design Issues Implementing SPC — A new ISO standard, 11462-1, provides guidance for — Basis for sampling — Sample size — Frequency of sampling organizations wishing to use SPC, and addresses: — Definition of SPC goals. — Conditions for a successful SPC system. — Elements of the SPC system. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 47 44 — Location of control limits 47 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 48 48 8 6/12/20 Probability of Detecting Mean Shift Sample Size — In practice, samples of about five have been found to work well in detecting process shifts of two standard deviations or larger. To detect smaller shifts in the process mean, larger sample sizes of 15 to 25 must be used. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 49 49 © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 50 50 Practical Guidelines 1. If the cost of investigating an operation to identify the cause of an apparent out-of-control condition is high, wider control limits should be adopted. Conversely, if that cost is low, narrower limits should be selected. 2. If the cost of the defective output generated by an operation is substantial, narrower control limits should be used. Otherwise, wider limits should be selected. 3. If the cost both types of errors are significant, wide control limits should be chosen and a larger sample size should be used. Also, more frequent samples should be taken to reduce the duration of any out-ofcontrol condition that might occur. 4. If past experience with an operation indicates that an out-of-control condition arises quite frequently, narrower control limits should be considered. In the event that the probability of an out-of-control condition is small, wider limits might be preferred. © 2014 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole wholeor or in part.. part. 51 51 9