7 QC TOOLS
Updated: Sep 11
1-Stratify data
2-Pareto diagram
3-Cause & effect diagram
4-Histogram
5-Scatter Diagram
6-Check Sheets
7-Control Charts
Will be explained through the creation of a QC Story
QC Story
A procedure for problem-solving
‘Story’ means ‘Logical Flow’
QC Story Steps
1. Define
-Define the problem clearly
Demonstrate the importance of the problem
Show the background of the problem
Explain with data the pain and impact of pain
Define the theme with target
Form a team and appoint a leader
Present and estimated budget
Prepare a schedule
2. Observation
Investigate data
Go to Gemba
Observe both conforming and non-conforming products/situations
How to Collect Data
1.Have Clear Defined Objectives
•Controlling and monitoring the production process
•Analysis of non-conformance
•Inspection
2. What Is Your Purpose
•Collecting as per strata
•Collecting in Pairs (correlation)
3. Are Measurements Reliable
4. Find Right Ways to Record Data
•Arrangement
•Data sheet
A-Check Sheet
What
An easy to understand form used to answer the question “How often are certain events happening?”
Why
Starts the process of translating “opinion” into “fact
When
Gathering data in order to detect patterns. Good point to start most problem-solving cycles.
Purpose of Check Sheets
Simplification of the data collection process
Reduction of recording errors
Ease of analysis
How
•Team agrees as to exactly what event is being observed.
•Decide on the time period during which data will be collected. This could range from hours to weeks.
•Design a form that is clear and easy to use making sure that all columns are clearly labeled and that there is enough space to enter the data.
•Collect the data making sure that observations/ samples are as representative as possible.
B-Pareto Principle
VilfredoPareto (1848-1923) Italian economist
20% of the population has 80% of the wealth
Juranused the term “vital few, trivial many”. He noted that 20% of the quality problems caused 80% of the dollar loss.
Pareto Analysis
What
A bar chart that helps to prioritize actions by arranging elements in descending order of occurrence. Sorts out the “vital few” from the “trivial many”.
Why
•To prioritize actions needed to solve complex problems.
•To separate important from non-important causes contributing to a problem.
When
•Many factors are impacting a problem.
•Attention needs to be directed only to the few factors that account for most of the problems.
How
•Define a problem and collect data on the factors that contribute to it.
•Historical records generally provide sufficient information.
•Classify the data by type, cost, percent, number of occurrences, or whatever is appropriate for the situation.
•Arrange the data in descending order.
How contd.
•Draw bar graph showing constituent ratio on the vertical axis.
•Connect the cumulative percentage of each bar graph to obtain the Pareto curve.
Stratification
What
Stratification is a statistical technique of breaking down values and numbers into meaningful categories or classification.
Why
To focus on corrective action or identify true causes.
When
To identify the cause of the problem if they come from a particular source.
•To analyze root cause in conjunction with other techniques like Pareto diagram histogram and graphs.
How
Regroup original data as per the source of data(e.g.. Machine wise, shift-wise, model-wise, supplier-wise)
•If required collect data a fresh after making the source from which they come.
•Recreate histogram, Pareto charts, and graphs on classified data
3. Analysis
Find out what the main causes are
Set up Hypothesis
Eliminate irrelevant causes
Brainstorming
Cause & Effect Diagram
Mark those with a higher probability
Cause Effect Matrix
Rating and Ranking
FMEA
Test the Hypothesis
Collect data or conduct experiments to the validated hypothesis
List validated causes
Histograms
Control Charts
Scatter Diagrams
A-Cause & Effect Diagram
What
•A graphic tool used to represent the relationship between an effect and the cause that influence it.
Why
•Identifies various causes affecting a process.
•Helps groups in reaching a common understanding of a problem.
•Helps reduce the incidence of subjective decision making.
When
•Looking for all potential causes of the problem
How
•Define the problem or effect clearly.
•Generate the potential cause of the problem through brainstorming.
B-Histogram
What
A bar chart displays the variation within the process. Also called a frequency distribution because the frequency of occurrence of any given value is represented by the height of the bars.
Why
•Allows one to quickly visualize what’s going on within a large amount of data.
•Provides clues to causes of problems.
•Maybe be used to show the relationship between the engineering tolerance and the capabilities of the process
When
•Capabilities studies are being performed.
•Analyzing the quality of incoming material.
How
•Collect measurements(variable data)from a process or key characteristic.
•Thirty or more measurements are preferred.
•Construct check sheet to record the data.
•Find the range by subtracting the smallest measurements from the largest.
Taking the class interval on the horizontal axis, draw the height of the bar corresponding to frequencies in the interval on the vertical axis.
C-Scatter Diagram
What
A tool used to study the possible relationship between two variables.
Why
To test for possible causes and effect relationships. Though it cannot prove that one variable causes the other, the diagram does make it clear whether a relationship exists and shows the strength of that relationship.
When:
There is a need to display what happens to one variable when another one changes in order to test that the two variables are related.
How
•Collect 50 to 100 paired samples of data believed to be related.
•Construct a data sheet.
•Draw the horizontal and vertical axis of the diagram.
•Label the axes.
•“Cause” is usually plotted on the horizontal axis and the “effect” variable on the vertical axis.
•Plot the data on the diagram. If values repeat, circle that point.
D-Control Chart
What
A control chart is a line graph used to display variation on time-ordered fashion. A centerline and control limits are placed on the graph to help analyze the pattern of the data. Why
•To separate common causes from special causes of variation.
•To help assign causes of variation
When
Measuring control characteristics.
Where
At the earliest possible point in the manufacturing process.
How
•Define process parameter to be measured.
•Define wherein the process the control characteristics will be measured.
•Select where the control chart is to be used.
•Determine sample size and frequency.
•Take measurements.
•Plot measurements on the graph.
•Connect dots.
•After 20 plot points calculate center-line and control limits.
•Analyse pattern for special cause of variation.
x –R Chart:
How to read Control Charts
1.Out of Control Limits: Points outside the limits
2.Run: Continuously on one side of centerline
•Seven-Point length of the run is abnormal
•10 Out of 11 consecutive points on one side
•12 Out of 14 consecutive points on one side
•16 Out of 20 consecutive points on one side
3. Trend: Continuous upward or downward curve
P AND Np CHART
These charts are utilized for ‘Defective’ :
P Chart: when the sample is constant /Np Chart: When the sample size is varying
C And U -CHART
These Charts are utilized for controlling ‘Defects’C: Charts are used for products of constant size .U: Charts are used for products of Varying size
4. Action
Take action to eliminate the main cause
Focus on causes and not symptoms for action
Check for any unintended/side effect
List all possible solutions and priorities based on cost-benefit analysis
Implement actions on a small scale to test the effect before horizontally deploying
5. Check
Compare ‘BEFORE’ vs. ‘AFTER’
Use same tool as used in analysis
Use same scale to show differences clearly
Convert results into Rs.
List any other tangible and intangible effects (good or bad)
6. Standardizations
To convert a statistical solution to an actual solution and hold the gains
Two types
One-time change
Time-monitored change
7. Conclusion
Review the problem solving process and plan for future work
Sum up remaining problems
Plan what is to be done and solve these problems
Document learning from project
What went wrong
What went right
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