7OLD TOOLS AND NEW TOOLS
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Transcript of 7OLD TOOLS AND NEW TOOLS
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7 OLD(BASIC) TOOLS OF QUALITY
HISTORY In 1950, the Japanese Union of
Scientists and Engineers (JUSE) invited W. Edwards Deming to Japan and train Japanese engineers, managers and scholars in statistical process control.
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7 OLD(BASIC) TOOLS OF QUALITY
One of the members of the JUSE was Kaoru Ishikawa, the then associate professor at the University of Tokyo. Ishikawa had a desire to 'democratise quality‘
Inspired by Deming’s lectures, he formalized the Seven Basic Tools of Quality Control
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7 OLD(BASIC) TOOLS OF QUALITY What are these 7 basic tools??
1.Histograms2.Check sheets 3.Cause and Effect Diagrams4.Pareto Diagrams5.Stratification analysis6.Scatter diagrams &7.Control Charts
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HISTOGRAM
Tool for summarizing, analyzing, and displaying data.
To show the different frequencies in a process.
Identify trends and relationships. Graphical representation of the
amount of variation found in a set of data.
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HISTOGRAM
CONSTRUCTING HISTOGRAM:1.Data collection2.Calculate the range of the sample data3.Select class scale4.Calculate the size of the class interval.
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HISTOGRAM
CONSTRUCTING HISTOGRAM:4. Determine the class boundary5. Calculate the number of data points
(frequency) that are in each class.6. Draw the Histogram
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HISTOGRAM
33
65
812
0 0 10
10
20
30
40
50
60
70
1 2 3 4 5 6 7
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HISTOGRAM
LIMITATION1.Histograms do not give solutions to
problems. They only provide a starting point for the improvement process.
2.Results obtained from any histogram will depend on the date which the histogram is made.
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CHECKSHEET
To collect data from a process in an easy, systematic, and organized manner.
Steps to be taken before data collection.
I. Purpose of collecting dataII.Type of data to be collectedIII.Who is going to collect data and when
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CHECKSHEET
TYPES OF CHECKSHEET:
1.Defective Item Check Sheet2.Defective Location Check Sheet3.Defective Cause Check Sheet4.Checkup Confirmation Check Sheet
Data collected using check sheets can be used as input data for other quality tools such as Pareto diagrams
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CAUSE AND EFFECT DIAGRAM
Tool that enables the user to set down systematically a graphical representation of the trail that leads ultimately to the root cause of a quality concern or problem.
Also known as fishbone diagram that relates the symptom or problem under question to the factors or causes driving it.
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CAUSE AND EFFECT DIAGRAM
Consists primarily of two sides. 1. Right side/effect side, lists the
problem or the quality concern under question. can also include a desired effect the user wishes to achieve
2. Left side/cause side, lists the primary causes of the problem.
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CAUSE AND EFFECT DIAGRAM
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CAUSE AND EFFECT DIAGRAM
CONSTRUCTING CAUSE AND EFFECT DIAGRAM
Select the team members. Identify quality concern Brain-storming Identify, for each main cause, its related
sub-causes that might effect our quality concern or problem
Focus on one or two causes for which an improvement action(s) can be developed
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CAUSE AND EFFECT DIAGRAM
Importance of cause and effect diagram: The structured nature of the method
forces the user to consider all the likely causes of a problem, not just the obvious ones, by combining brainstorming techniques with graphical analysis.
Also useful in unraveling the convoluted relationships that may drive the problem.
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PARETO CHART (OR) PARETO ANALYSIS
A Pareto chart is a bar graph. The height of the bars represent frequency or cost (time or money), and are arranged with highest bars on the left and the shortest to the right.
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The Pareto 80 / 20 rule80 % of the problems are produced by 20
% of the causes. To identify the ‘VITAL FEW FROM
TRIVIAL MANY’ and to concentrate on the vital few for improvement
A Pareto diagram indicates which problem we should solve first in eliminating defects and improving the operation.
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WHEN TO USE When analyzing data about the frequency of problems or causes in a process. When there are many problems or causes and you want to focus on the most significant. When analyzing broad causes by looking at their specific components. When communicating with others about your data.
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SCATTER DIAGRAM (OR) SCATTER PLOT
The scatter diagram graphs pairs of numerical data, with one variable on each axis, to look for a relationship between them.
If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line.
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When you have paired numerical data. When trying to determine whether the
two variables are related, such as when trying to identify potential root causes of problems.
After brainstorming causes and effects using a fishbone diagram, to determine objectively whether a cause and effect are related.
WHEN TO USE
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STRATIFICATION
Stratification is a technique used in combination with other data analysis tools.
When data from a variety of sources or categories have been lumped together, the meaning of the data can be impossible to see
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When to Use
Before collecting data. When data come from several sources or
conditions, such as shifts, days of the week, suppliers or population groups.
When data analysis may require separating different sources or conditions.
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Process Control Charts
Control charts are tools used to determine whether a process is in a state of control.
Used when the quality of the product depends on some measurable quantity like height, length, diameter etc.
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Control Chart
11 22 33 44 55 66 77 88 99 1010Sample numberSample number
UpperUppercontrolcontrol
limitlimit
ProcessProcessaverageaverage
LowerLowercontrolcontrol
limitlimit
Out of controlOut of control
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Conditions for Process Control There should be no sample points
outside the upper and lower control limits
Most points should be near the average process line
Points appear randomly distributed
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Types of Control Charts
Attributes p-chart c-chart
Variables range (R-chart) mean (x bar – chart)
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Control Charts for Attributes p-charts
uses portion defective in a sample c-charts
uses number of defects in an item
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p-Chart
UCL = p + zp
LCL = p - zp
z = number of standard deviations from process averagep = sample proportion defective; an estimate of process averagep = standard deviation of sample prop
pp = p = p(1 - (1 - pp)/n)/n
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c-Chart
UCL = UCL = cc + + zzcc
LCL = LCL = cc - - zzcc
cc = = c c
where c = number of defects per sample
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List Of Seven New Tools of Quality Control Affinity Diagram Relationship Diagram Tree Diagram Matrix Diagram Arrow Diagram Process Decision Program Charts Matrix Data Analysis
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History of Seven New Tools Committee set up by Union of Japanese
Scientists and Engineers. - 1972 Aim was to develop more QC techniques with
design approach Work in conjunction with original Basic Seven
Tools Developed to organize verbal data
diagrammatically. Basic 7 tools effective for data analysis,
process control, and quality improvement (numerical data)
Used together increases TQM effectiveness
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AFFINITY DIAGRAM
Tool that gathers large amounts of verbal data (ideas, opinions, issues)and organizes them into groups.
Organization based on natural relationships
This makes it feasible for further and analysis and to find a solution to the problem.
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Sample Affinity Diagram
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Why Affinity Diagrams…
Good way to get people to work on a creative level to address difficult issues.
Can be used in situations unknown or unexplored by a team.
Fosters team spirit. Raises team awareness
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How to construct Affinity Diagrams(Group Method Approach) Select a topic Collect verbal data by brainstorming Discuss collected info until everyone
understands it thoroughly Write each item on a separate data card Organize data cards into groups of similar
themes(natural affinity) Combine statements on data cards to new
Affinity statement Make new cards with affinity statement Complete the diagram
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RELATIONSHIP DIAGRAM
Also known as inter-relationship diagram
Used to depict the relationship between different issues
Helps to untangle and find logical relations among complex intertwined causes and effects
Allows for multidirectional thinking rather than lateral thinking
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Advantages of Relationship Diagram Useful at planning stage for obtaining
perspective on overall situation Facilitates consensus among team Assists to develop and change people’s
thinking Enables priorities to be identified
accurately Makes the problem recognizable by
clarifying the relationships among causes
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A Sample Relationship Diagram
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How to Construct a relationship Diagram
Express the problem List the causes affecting the problem Write each item on a card Move the cards into similar groups explore the cause-effect relationships, and divide the cards
into primary, secondary and tertiary causes Connect all cards by these relationships Further discuss until all possible causes have been
identified Review whole diagram looking for relationships among
causes Connect all related groups Complete the diagram
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TREE DIAGRAM
It starts with one item that branches into two or more, each of which branch into two or more, and so on. It looks like a tree, with trunk and multiple branches.
It is used to break down broad categories into finer and finer levels of detail. Developing the tree diagram helps you move your thinking step by step from generalities to specifics.
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When to use a tree diagram When an issue is known or being addressed in
broad generalities and you must move to specific details.
When developing actions to carry out a solution or other plan.
When analyzing processes in detail. When probing for the root cause of a problem. When evaluating implementation issues for
several potential solutions. After an affinity diagram or relations diagram
has uncovered key issues. As a communication tool, to explain details to
others.
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Procedure Determine the main goal Be concise Brainstorm the main tasks involved in
solving the problem and add them to the tree
Brainstorm subtask that can also be added to the tree
Do this until all possibilities have been exhausted
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To Accomplish
3rd means
3rd means
Primary means
3rd means
3rd means
Primary means
Secondary means
Secondary means
Secondary means
Secondary means
3rd means
3rd means
3rd means
3rd means
4th means
4th means
4th means
4th means
4th means
4th means
4th means
4th means
4th means
4th means
4th means
4th means
Example
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PROCESS DECISION PROGRAM CHART (PDPC) It is a good tool to use for contingency
planning. It identifies what might go wrong in a
plan under development. We can either revise the plan to avoid
the problems or be ready with the best response when a problem occurs.
Example :
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Procedure
List the steps in the process you wish to
analyze
List what could go wrong at each step
List the counter measures to the problems
Evaluate the counter measures by placing
an O for feasible or an X for not feasible
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MATRIX DATA ANALYSIS
One of the most rigorous, careful and time-consuming of decision-making tools
It is an L-shaped matrix that uses pair-wise comparisons of a list of options to a set of criteria in order to choose the best option(s).
Based solely on numerical data
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Procedure
Identify your goal Place selection in order of importance Apply percentage weight to each option Sum individual ratings to establish overall
ranking Rank order each option with respect to
criterion Multiply weight by associated rank in Matrix Result is Importance Score Add up Importance Scores for each option
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Particulars
CustomerD
CustomerM
CustomerR
CustomerT
Purity % > 99.2 > 99.2 > 99.4 > 99.0
Trace metals (ppm)
< 5 — < 10 < 25
Water (ppm)
< 10 < 5 < 10 —
Viscosity (cp)
20-35 20-30 10-50 15-35
Color < 10 < 10 < 15 < 10
Drum
Truck
Railcar
Example – Customer requirements
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Matrix Diagram
The matrix diagram shows the relationship between
two, three or four groups of information. It also can
give information about the relationship, such as its
strength, the roles played by various individuals or
measurements
Six differently shaped matrices are possible: L, T, Y,
X, C, R and roof-shaped, depending on how many
groups must be compared.
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When do we use each Shape
An L-shaped matrix relates two groups of items to each other (or one group to itself).
A T-shaped matrix relates three groups of items: groups B and C are each related to A. Groups B and C are not related to each other.
A Y-shaped matrix relates three groups of items. Each
group is related to the other two in a circular fashion.
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A C-shaped matrix relates three groups of items all together simultaneously, in 3-D.
An X-shaped matrix relates four groups of items. Each group is related to two others in a circular fashion.
A roof-shaped matrix relates one group of items to itself. It is usually used along with an L- or T-shaped matrix. (Used in QFD)
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TYPES OF MATRICES
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ARROW DIAGRAM (OR) NETWORK DIAGRAM (OR) CPM (CRITICAL
PATH METHOD) CHART
The arrow diagram shows the required order of tasks in a project or process, the best schedule for the entire project, and potential scheduling and resource problems and their solutions.
When scheduling and monitoring tasks
within a complex project or process with interrelated tasks and resources.
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When you know the steps of the project or process, their sequence and how long each task.
When project schedule is critical, with serious consequences for completing the project late or significant advantage to completing the project early.
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R CHART AND X BAR CHART An X-bar and R (range) chart is a pair of control
charts used with processes that have a subgroup size of two or more.
The standard chart for variables data, X-bar and R charts help determine if a process is stable and predictable.
The X-bar chart shows how the mean or average changes over time and the R chart shows how the range of the subgroups changes over time.
It is also used to monitor the effects of process improvement theories. As the standard, the X-bar and R chart will work in place of the X-bar and s or median and R chart
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Used for measurement data Assumes population is normally distributed. Upper and lower control limits usually 3
standard deviations above and below the mean of the process.
Collect small samples in equally spaced intervals over time.z
Usually 20-30 periods n is the sample size collected each time k is the number of samples collected over time
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For each sample, calculate the mean A.M x = x/N For each sample, calculate the range range = xlargest – xsmallest Calculate the grand or overall mean by
averaging all the sample means. This becomes the center line of the x-
bar chart.
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