7 QC Tools

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7 QC Tools

  1. 1. QUAN 6610 7 QC Tools: The Lean Six Sigma Pocket Toolbook •Flowchart [p. 33-41] •Check Sheet [p. 78-81] •Histogram [p. 111-113] •Pareto [p. 142-144] •Cause-and-Effect [p. 146-147] •Scatter [p. 154-155] •Control Chart [p. 122-135] 1 Pareto Diagram 2Process Variability Concepts 1
  2. 2. QUAN 6610 Step 1: Decide on problem, type of data, and causes or categories. 3 Step 2: Collect the data. 4Process Variability Concepts 2
  3. 3. QUAN 6610 Step 3: Order the causes or categories. 5 Step 4: Calculate the cumulative totals. 6Process Variability Concepts 3
  4. 4. QUAN 6610 Step 5: Draw and label the horizontal axis. 7 Step 6: Draw, scale, and label the vertical axis. 8Process Variability Concepts 4
  5. 5. QUAN 6610 Step 7: Draw bars for each cause or category. 9 Step 8: Draw cumulative total lines. 10Process Variability Concepts 5
  6. 6. QUAN 6610 Interpret the Pareto Chart. 11 Pareto Diagram (Using EXCEL) 1. Create a table listing the sources of defects in the first column and in the second column calculate the total number of defects per source. Error Category Jan Feb Mar Apr May Jun Total Improper credit check 2 1 1 4 Unsigned signature card 4 3 2 3 4 2 18 Starter checks not provided 4 1 1 6 Disclosures not provided 1 1 1 3 Checks not ordered 2 4 3 2 5 16 Paperwork lost at DP center 1 1 2 Incorrect data entry at DP 2 2 4 source: Brightman, Data Analysis 12Process Variability Concepts 6
  7. 7. QUAN 6610 2. Sort the table by the total number of defects in descending order. In the third column, calculate the cumulative percentage for each row in the table. Error Category Total Error Category Total Cum % Unsigned signature card 18 Unsigned signature card 18 33.96% Checks not ordered 16 Checks not ordered 16 64.15% Starter checks not provided 6 Starter checks not provided 6 75.47% Improper credit check 4 Improper credit check 4 83.02% Incorrect data entry at DP 4 Incorrect data entry at DP 4 90.57% Disclosures not provided 3 Disclosures not provided 3 96.23% Paperwork lost at DP center 2 Paperwork lost at DP center 2 100.00% 3. Create a chart with the ChartWizard (custom --- line-column on two axes). 13 Opening checking account errors 20 100.00% 15 80.00% 60.00% 10 40.00% 5 20.00% 0 0.00% ck DP ed t p DP ed d ed er no c ar nt he d id er at vi ce ov rd tc re ro try to op t pr t d edi tu en Ch gna no no cr at a ks si er st at es s ck ec lo d pe s ur ne he k pr ec or lo s ig rc Im rr sc rw co te Un Di ar In Pa St 14Process Variability Concepts 7
  8. 8. QUAN 6610 Cause and Effect Diagram 15 Step 1: Develop problem statement. 16Process Variability Concepts 8
  9. 9. QUAN 6610 Step 2: Brainstorm causes. 17 Step 2: Brainstorm causes. 18Process Variability Concepts 9
  10. 10. QUAN 6610 Step 3: Determine the major cause categories. 19 Step 4: Determine the category for Each listed cause. 20Process Variability Concepts 10
  11. 11. QUAN 6610 Step 4: Determine the category for Each listed cause. 21 Step 5: Put categories and causes On cause & effect diagram. 22Process Variability Concepts 11
  12. 12. QUAN 6610 Step 6: Identify the most likely causes. 23 “Failure to understand variation is the central problem of management.” 24Process Variability Concepts 12
  13. 13. QUAN 6610 Stable vs. Unstable process Stable process: a process in which variation in outcomes arises only from common causes. Unstable process: a process in which variation is a result of both common and special causes. 25 source: Moen, Nolan and Provost, Improving Quality Through Planned Experimentation Red Bead experiment 26Process Variability Concepts 13
  14. 14. QUAN 6610 Red Bead Experiment What are the lessons learned? 1. 2. 3. 4. 27 Statistical Process Control: Control Charts Process Parameter • Track process parameter over time - mean - percentage defects Upper Control Limit (UCL) • Distinguish between - common cause variation Center Line (within control limits) - assignable cause variation (outside control limits) Lower Control Limit (LCL) • Measure process performance: how much common cause variation is in the process while the process Time is “in control”? 28Process Variability Concepts 14
  15. 15. QUAN 6610 Conceptual view of SPC 29 source: Donald Wheeler, Understanding Statistical Process Control Process Stability vs. Process Capability Wheeler, Understanding Statistical Process Control 30Process Variability Concepts 15
  16. 16. QUAN 6610 Advantages of Statistical Control 1. Can predict its behavior. 2. Process has an identity. 3. Operates with less variability. 4. A process having special causes is unstable. 5. Tells workers when adjustments should not be made. 6. Provides direction for reducing variation. 7. Plotting of data allows identifying trends over time. 8. Identifies process conditions that can result in an acceptable product. 31 source: Juran and Gryna, Quality Planning and Analysis, p. 380-381. Identifying Special Causes of Variation source: Brian Joiner, Fourth Generation Management, pp. 260. See also Lean Six Sigma Pocket Toolbook, p. 133-135. 32Process Variability Concepts 16
  17. 17. QUAN 6610 Strategies for Reducing Special Causes of Variation • Get timely data so special causes are signaled quickly. • Put in place an immediate remedy to contain any damage. • Search for the cause -- see what was different. • Develop a longer term remedy. 33 source: Brian Joiner, Fourth Generation Management, pp. 138-139. “In a common cause situation, there is no such thing as THE cause.” Brian Joiner 34Process Variability Concepts 17
  18. 18. QUAN 6610 Improving a Stable Process • Stratify -- sort into groups or categories; look for patterns. (e.g., type of job, day of week, time, weather, region, employee, product, etc.) • Experiment -- make planned changes and learn from the effects. (e.g., need to be able to assess and learn from the results -- use PDCA .) • Disaggregate -- divide the process into component pieces and manage the pieces. (e.g., making the elements of a process visible through measurements and data.) 35 source: Brian Joiner, Fourth Generation Management, pp. 140-146. A Conversation with Joseph Juran “Take this example: In finance we set a budget. The actual expenditure, month by month, varies - we bought enough stationery for three months, and that’s going to be a miniblip in the figures. Now, the statistician goes a step further and says, ‘How do you know whether it’s a miniblip or there’s a real change here?’ The statistician says, ‘I’ll draw you a pair of lines here. These lines are such that 95% of the time, you’re going to get variation between them.’ Now suppose something happens that’s clearly outside the lines. The odds are something’s amok. Ordinarily this is the result of something local, because the system is such that it operates in control. So supervision converges on the scene to restore the status quo. Notice the distinction between what’s chronic [common cause] and what’s sporadic [special cause]. Sporadic events we handle by the control mechanism. Ordinarily sporadic problems are delegable because the origin and remedy are local. Changing something chronic requires creativity, because the purpose is to get rid of the status quo - to get rid of waste. Dealing with chronic requires structured change, which has to originate pretty much at the top.” Source: A Conversation with Joseph Juran, Thomas Stewart, Fortune, January 11, 1999, p. 168-170. 36Process Variability Concepts 18

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