3 Step 1: Decide on problem, type of data, and causes or categories.
4 Step 2: Collect the data.
5 Step 3: Order the causes or categories.
6 Step 4: Calculate the cumulative totals.
7 Step 5: Draw and label the horizontal axis.
8 Step 6: Draw, scale, and label the vertical axis.
9 Step 7: Draw bars for each cause or category.
10 Step 8: Draw cumulative total lines.
11 Interpret the Pareto Chart.
12 Pareto Diagram 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. (Using EXCEL)
13 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. 3.Create a chart with the ChartWizard (custom --- line-column on two axes).
15 Cause and Effect Diagram
16 Step 1: Develop problem statement.
17 Step 2: Brainstorm causes.
18 Step 2: Brainstorm causes.
19 Step 3: Determine the major cause categories.
20 Step 4: Determine the category for Each listed cause.
21 Step 4: Determine the category for Each listed cause.
22 Step 5: Put categories and causes On cause & effect diagram.
23 Step 6: Identify the most likely causes.
24 “Failure to understand variation is the central problem of management.”
25 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. source: Moen, Nolan and Provost, Improving Quality Through Planned Experimentation
26 Red Bead experiment
27 Red Bead Experiment What are the lessons learned?
28 Time Process Parameter Upper Control Limit (UCL) Lower Control Limit (LCL) Center Line Track process parameter over time - mean - percentage defects Distinguish between - common cause variation (within control limits) - assignable cause variation (outside control limits) Measure process performance: how much common cause variation is in the process while the process is “in control”? Statistical Process Control: Control Charts
29 Conceptual view of SPC source: Donald Wheeler, Understanding Statistical Process Control
30 Process Stability vs. Process Capability Wheeler, Understanding Statistical Process Control
31 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. source: Juran and Gryna, Quality Planning and Analysis, p
32 Identifying Special Causes of Variation source: Brian Joiner, Fourth Generation Management, pp See also Lean Six Sigma Pocket Toolbook, p
33 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. source: Brian Joiner, Fourth Generation Management, pp
34 “In a common cause situation, there is no such thing as THE cause.” Brian Joiner
35 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.) source: Brian Joiner, Fourth Generation Management, pp
36 “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.” A Conversation with Joseph Juran Source: A Conversation with Joseph Juran, Thomas Stewart, Fortune, January 11, 1999, p