3. What is Cause Effect diagram
A Cause-and-Effect diagram is a tool that
helps to identify, sort and display possible
causes of a specific problem or quality
characteristic. It graphically illustrates
the relationship between a given outcome
and all the factors that influence the
outcome. This type of diagram is often
termed as “Ishikawa diagram” after the
name of it’s inventor Kaoru Ishikawa, or
“fishbone diagram” because of the way it
looks.
4. Cause and Effect Diagram
Professor Kaoru Ishikawa created Cause and Effect
Analysis in the 1960s. The technique uses a diagram-
based approach for thinking through all of the possible
causes of a problem. This helps you to carry out a
thorough analysis of the situation.
There are four steps to using the tool.
Identify the problem.
Work out the major factors involved.
Identify possible causes.
Analyze your diagram.
5. Uses of Cause and effect analysis
Displays all the possible causes of a particular problem in a
simple, easy to read graphical way.
Captures the relationships between the potential causes
and shows them in the chart.
A great tool for solving complex problems where many
factors have to be taken into consideration.
Stimulates an in-depth analysis and evaluation because
allows you to explore possible causes in details.
Gives you a bigger picture and better understanding of the
problem.
Boosts and frameworks brainstorming about the possible
reasons.
Stimulates in-depth discussion among team members about
the problem.
Helps in maintaining team focus.
Identify where a process isn’t working.
6. Basic benefits of Cause-effect
diagram
Helps determine root causes.
Encourages group participation.
Uses an orderly, easy-to-read format.
Indicates possible causes of variation.
Increases process knowledge.
7.
8. FISHBONE DIAGRAM PROCEDURE
Materials needed: marking pens and flipchart or whiteboard.
Agree on a problem statement (effect). Write it at the center
right of the flipchart or whiteboard. Draw a box around it and
draw a horizontal arrow running to it.
Brainstorm the major categories of causes of the problem. If
this is difficult use generic headings:
Methods
Machines (equipment)
People (manpower)
Materials
Measurement
Environment
9. FISHBONE DIAGRAM PROCEDURE
Write the categories of causes as branches from the main
arrow.
Brainstorm all the possible causes of the problem. Ask
"Why does this happen?" As each idea is given, the
facilitator writes it as a branch from the appropriate
category. Causes can be written in several places if they
relate to several categories.
Again ask "Why does this happen?" about each cause.
Write sub-causes branching off the causes. Continue to
ask "Why?" and generate deeper levels of causes. Layers
of branches indicate causal relationships.
When the group runs out of ideas, focus attention to
places on the chart where ideas are few.
10.
11. Pareto Principles
Pareto Principle is an unscientific “law” that states: 80% of
effects come from 20% of causes.
The principle comes from the Pareto distribution and illustrates
that many things don’t have an even distribution. It was
originally written by Italian economist Vilfredo Pareto in 1896,
who stated that 20% of the population in Italy holds 80% of the
wealth. In the 1930s-1940s.
Dr. Joseph Juran recognized the principle can be applied
universally to almost any situation where there is an uneven
distribution. For example:
80% of output is produced by 20% of workers.
20% of customers produce 80% of the revenue.
80% of retail sales are made by 20% of brands.
80% of your website’s traffic comes from 20% of your posts.
12. Pareto Analysis and the Pareto Diagram
Pareto analysis is a statistical way to identify the 20% of tasks
or problems that you should be concentrating on.
The Pareto diagram lists categories of what is taking up the
time/resources along with a relative frequency (adding up to
100%). The Pareto diagram is basically a vertical bar chart with
categories listed in order of magnitude, from left to right. This
allows you to easily see which tasks or resources make up the
top 20%.
13. Suppose a poll was taken of 200 people who were late for work, and
they were asked to explain why they were late. The chart below
shows the responses to this poll.
In this poll, there were ten different reasons given for being late for
work. But, note that many of these reasons were only claimed by
one or two people. The vast majority of the respondents gave
"Woke Up Late" or "Bad Weather" as their excuse. We can use
Excel to create a Pareto chart of this information and get the graph
shown below.
14. In this example, we can see that 80% of the reasons for
being late came from two excuses (or 20% of the total
number of excuses).
15. Histograms
A histogram is a bar graph that shows frequency data.
Histograms provide the easiest way to evaluate the
distribution of data.
A histogram is an accurate representation of the
distribution of numerical data. It was first introduced by
Karl Pearson.
16. Example of a Histogram
Jeff is the branch manager at a local bank. Recently, Jeff’s been receiving
customer feedback saying that the wait times for a client to be served by a
customer service representative are too long. Jeff decides to observe and write
down the time spent by each customer on waiting. Here are his findings from
observing and writing down the wait times spent by 20 customers:
17. The corresponding histogram with 5-second bins (5-
second intervals) would look as follows:
•There are 3 customers waiting between 1 and 35 seconds
•There are 5 customers waiting between 1 and 40 seconds
•There are 5 customers waiting between 1 and 45 seconds
•There are 5 customers waiting between 1 and 50 seconds
•There are 2 customers waiting between 1 and 55 seconds
Jeff can conclude that the majority of customers wait between 35.1 and 50 seconds.
18. Flow Charts
Flow Charts Defined – A flow chart is a pictorial representation
showing all of the steps of a process.
Creating a Flow Chart –
First, familiarize the participants with the flow chart symbols. –
Draw the process flow chart and fill it out in detail about each
element. – Analyze the flow chart. Determine which steps add
value and which don’t in the process of simplifying the work.
19. Benefits of Using Flowcharts
Promote process understanding
Provide tool for training
Identify problem areas and improvement opportunities
21. Run Charts
Run charts are used to analyze processes according to time or
order.
A run chart, also known as a run-sequence plot is a graph
that displays observed data in a time sequence. Often, the
data displayed represent some aspect of the output or
performance of a manufacturing or other business process. It
is therefore a form of line chart.
22. Creating a Run Chart
Gathering Data
• Some type of process or operation must be available to take
measurements for analysis.
Organizing Data
• Data must be divided into two sets of values X and Y.
X values represent time and values of Y represent the measurements
taken from the manufacturing process or operation.
Charting Data
• Plot the Y values versus the X values. –
Interpreting Data
• Interpret the data and draw any conclusions that will be beneficial to
the process or operation.
23. An Example of Using a Run Chart
An organization’s desire is to have their product arrive to their
customers on time, but they have noticed that it doesn’t take
the same amount of time each day of the week. They decided
to monitor the amount of time it takes to deliver their product
over the next few weeks.
24. Control Charts
Control charts, also known as Shewhart charts (after Walter A.
Shewhart) or process-behavior charts, are a statistical process
control tool used to determine if a manufacturing or business
process is in a state of control.
A control chart always has a central line for the average, an upper
line for the upper control limit, and a lower line for the lower
control limit. These lines are determined from historical data. By
comparing current data to these lines, you can draw conclusions
about whether the process variation is consistent (in control) or is
unpredictable (out of control, affected by special causes of
variation).
26. When to use a control chart
• When controlling ongoing processes by finding and correcting
problems as they occur
• When predicting the expected range of outcomes from a process
• When determining whether a process is stable (in statistical
control)
• When analyzing patterns of process variation from special causes
(non-routine events) or common causes (built into the process)
Counting the number of defective products or services • Do you
count the number of defects in a given product or service?
Is the number of units checked or tested constant?
27. Control Chart Basic
Procedure
Choose the appropriate control chart for your data.
Determine the appropriate time period for collecting and
plotting data.
Collect data, construct your chart and analyze the data.
Look for "out-of-control signals" on the control chart. When one
is identified, mark it on the chart and investigate the cause.
Document how you investigated, what you learned, the cause
and how it was corrected.
28. Out-of-control signals
A single point outside the control limits. In Figure 1, point sixteen
is above the UCL (upper control limit
29. Scatter Diagrams
Scatter Diagrams are used to study and identify the
possible relationship between the changes observed in
two different sets of variables
30. Constructing a Scatter Diagram
– First, collect two pieces of data and create a summary table of
the data.
– Draw a diagram labeling the horizontal and vertical axes.
• It is common that the “cause” variable be labeled on the X
axis and the “effect” variable be labeled on the Y axis.
– Plot the data pairs on the diagram.
– Interpret the scatter diagram for direction and strength
31. An Example of When a
Scatter Diagram Can Be Used
A scatter diagram can be used to identify the
relationship between the production speed of an
operation and the number of defective parts made.
Displaying the direction of the relationship will
determine whether increasing the assembly line speed
will increase or decrease the number of defective parts
made. Also, the strength of the relationship between
the assembly line speed and the number of defective
parts produced is determined.
32. Draw the scatter diagram for the given pair of variables and
understand the type of correlation between them.
No. of Students
Marks obtained
(out of 100)
12 40-50
10 50-60
8 60-70
7 70-80
5 80-90
2 90-100
33. Here, we take the two variables for consideration as:
M: The marks obtained out of 100
S: Number of students
Since the values of M is in the form of bins, we can use the
centre point of each class in the scatter diagram instead.
So let us first choose the axes of our diagram.
X-axis – Marks obtained out of 100
Y-axis – Number of Students
34. The data points that we need to plot according to the
given dataset are –
(45,12), (55,10), (65,8), (75,7), (85,5), (95,2)
From the shape of the curve, clearly, only a fewer number of students
get high marks. This implies a negative correlation between the two
variables we have considered here
35. Activity
Process Flow Chart for Finding the Best Way Home
Construct a process flow chart by making the best
decisions in finding the best route home.