This document provides an overview of tools and methods for quality improvement teams using the PDCA cycle. It discusses selecting a theme to improve, planning the schedule, grasping the current status through data collection, setting targets, analyzing causes and determining corrective actions, implementing and evaluating results, and standardizing successful processes. Specific quality tools covered include checksheets, cause and effect diagrams, Pareto diagrams, histograms, control charts, scatter diagrams, and stratification.
4. SELECT THE THEME
From:-
• Customer
complaints.
• Department’s
objectives.
• The big ‘Q’
• The small ‘q”PLAN
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5. PLAN THE SCHEDULE
• List all the 8 steps
in the PDCA cycle.
• Indicate the
expected time
frame.
• Use the milestone
chart.
PLAN
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6. GRASP THE CURRENT STATUS
Obtain and review
data using
checksheet.
Study the effects of
the problem from
various perspectives.
Present available data
in graphs, and Pareto
charts.PLAN
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7. SET THE TARGET
• Indicate clearly the
statement of result
to be achieved.
• Target must be
reasonable and
realistic.
• Use SMART
concept.
PLAN
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8. ANALYSE THE CAUSE &
DETERMINE CORRECTIVE ACTION
• Prepare cause and
effect diagram.
• Prepare hypothesis
and verify most
probable causes.
• Determine
corrective action.
PLAN
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9. IMPLEMENT CORRECTIVE
ACTION
• Take immediate action
by following exactly as
planned.
• Collect data on results
and record any
deviations.
• Provide adequate
training.
DO
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10. EVALUATE THE RESULT
• Check the effect of
the corrective
action.
• Compare results
with target
• Use paired Pareto
Chart.
CHECK
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11. STANDARDISE THE PROCESS
• Document as
standard operating
procedure (SOP).
• Set parameters to
monitor and control
the successful
process.
• Ensure appropriate
training on the new
methods.
ACTION
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13. CHECKSHEET
• A Checksheet is used
to gather relevant data
in a simple,
standardised format.
The use of checksheet
makes the collection of
data easier and more
systematic.
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14. CHECKSHEET
Description 1 2 3 4 5 6 7 8 9 T
1 Poor coordination and
communication
25
2 No review on test run 22
3 Insufficient
information
28
4 Errors in report 39
5 Inaccuracy of report 37
Total 34 17 19 10 12 29 7 13 10 151
Observed by:
Frequency: Daily
Checksheet on: Generation of Final Report Date: 13TH
JAN 09
Location: IKRAM PAVES (Case study)
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15. CAUSE AND EFFECT DIAGRAM
• The Cause and Effect
diagram helps us to
find out all possible
causes, to sort them
out, and to organise
their inter-relationship.
Typically, the causes
are brainstormed in a
free-flowing session.
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16. CAUSE AND EFFECT DIAGRAM
MAN
METHODMACHINE
MATERIAL
Lack
Manpower
Error in
Report
Generation
Lack of training
Tight Dateline
Time wasted
Data entry
error
Insufficient
skill
Paper wastage
(Cost)
Graphics
module not on
line
No reference
materials
(Guide book)
Unable to
cater complex
reports
No proper
evaluation of
equipment
(vendor)
Take over of
vendor
No user
requirement
No proper
planning
No review during testing
Redundant work
Two individuals
processing same data
Manual to computer
format
Shipping delay
Holiday season
No inter dept
communication
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17. PARETO DIAGRAM
• A Pareto diagram is
constructed to show the
relative importance of
different categories in a
process. The vital few is
separated from the
trivial many. This will
ensure that focus is
made on the what is
important.
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18. PARETO DIAGRAM
Observed by:
Frequency: Daily
100151Total
100.014.622No review on test run5
85.416.625Poor communication & coordination
4
68.818.528Insufficient information3
50.324.537Inaccuracy in report2
25.825.839Errors in report1
Cum
%
%TOTDescription
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20. HISTOGRAM
• A histogram is used to
summarise the
frequency of
occurrence of
something from a
sample of data. The
shape of distribution is
displayed and
descriptive statistics
can be calculated.
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22. CONTROL CHART
• A control chart has a
center line
corresponding to the
average quality at
which the process
should perform. An out
of control situation and
other unnatural
patterns can be
detected from the
chart
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24. SCATTER DIAGRAM
• A scatter diagram is a
special type of graph
which shows the
relationship between
two variables. If there
is an empirical
relationship between
the two variables it can
be easily seen.
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26. STRATIFICATION
• Stratification is the
technique of analysing
data by separating it
into several groups
with similar
characteristics. The
data must be stratified
by group to better
understand the
differences
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Note:
What Is the Objective of This Step?
To clearly identify the problem to be resolved or the area to be improved.
How Do We Identify Problem Areas or Areas to Be Improved?
We do this by selecting issues from your departmental objectives, customer complaints, big Q [quality, service,delivery and cost], or small q [housekeeping, morale, training and safety]. Once you have identified an issue, select a project theme. For example if the issue involves:-
Quality, then we can have a theme that reads, “Providing quality products is first amongst equals.”
Service, then we can have a theme that reads, “Fulfilling requirements efficiently and effectively.”
Delivery, then we can have a theme that reads, “Ensuring prompt and expeditious delivery at all times.”
Cost, then we can have a theme that reads, “Reducing failure cost by doing things right the first time.”
Note:
What is the Objective of this Step?
To gather as much relevant information as possible relating to the issue so as to have a general understanding of the problem situation.
How Do We Gather Information?
We do this by collecting and collating as much data and information as possible and record them in the checksheet. Data and information gathering should be done over a period of time depending on the nature of the problem. It is imperative that sufficient data and information are gathered to ensure that nothing is amiss.
What Do We Do with the Information?
To make sense of the data and information gathered, we have to transfer them to a Pareto chart to make them more meaningful for us to study the problem situation. The Pareto chart will show the ‘vital few and the trivial many’ nature of the problems in the form of vertical bars. Usually the first two bars contribute to the greatest percentage of the whole problem.
Note: According to Pareto 80/20 rule, 20 percent of the defects contribute to 80 percent of the whole problem.
Note:
What is the objective of this step?
We need to indicate clearly the statement of result to be achieved. Such a statement contains three major elements.
An accomplishment verb
A single measurable key result
A date or time period within which the result is to be accomplished.
For example:
“To reduce the submission time of monthly report by 100% from 4 days to 2 days by 31st July 2003”
Use the SMART concept when setting target:
S = Specific [Make sure that the target is specific]
M = Measurable [Target must be quantified]
A = Action-oriented [A plan of action must be prepared]
R = Realistic [This must be balanced with available resources]
T = Time-bound [Ensure that the target has a set deadline]
Note:
Step 1: The time period for the collection of data must be determined. It could be as brief as a few hours, or it may require days or even a few months. This may partly be determined by how you would like to organise the data. The time period will also enable you to compare changes in a problem, like comparing one time period against another. Often problems are a result of start-up or shut-down procedures, vacations schedules, job changes, or just seasonal differences. In order to solve the problem, this must be taken into consideration.
Step 2: Determine how you want to organise the data. The data on a specific problem could be ordered under different headings. Do you want to order it by defect, by department, by employee, or by location. This is an important step and members should be encouraged to participate. Remember, when organising the data, the idea is not to pick the easiest method but the one that is likely to portray the problem in a a manner the we can solve it.
Step3: Design the checksheet that will enable you to gather the most imformation using the latest effort.
Step 4: Collect and record the data on the checksheet. In this step you must determine where you go to collect data. It depends of course, on what day you decide to collect and under what heading you are placing it. But be rest assured that there are many sources of information.
Note:
Step 1: State the problem. It is important that the problem should be define as precisely as possible.
Step 2: The major groupings for possible causes to be identified are determined. Any number of such groupings is permissible, although the 4M’s are the most commonly used: Man, Method, Machine, Material.
Step3: All members get involved by participating in a brainstorming session. Brainstorming works best when specified rules are observed. The team leader reviews this before each session.
Step 4: All the ideas that are collected during the brainstorming session are critically examined to identify those that best described the causes to the problem. Doing this can be a time consuming process involving a critical analysis of the pros and cons of each. The process can however be greatly hastened by giving members the opportunity to vote for each cause they believe to be important.
Step 5: The most likely causes are now ranked in order of importance. To do this, the members look only at those causes that have been voted and circled.
Step 6: The most likely causes is then tested in an attempt to verify it. A good way to conduct verification is to brainstorm for supporting evidences, obtain feedback from process owners, or get documents that can support the authenticity of the likely causes in question.
Note:
Step 1: Decide how the problem information should be classified. By employee? By defect? By workstation? By department?
Step 2: Select a time period for your observation. The time period during which data is collected may be only a few hours, or a few days, or even a few months. Develop a checksheet to cover the specified time period.
Step3: Organise the data into table by ranking them according to the frequency and calculate percentages of each item relative to all other items.
Step 4: Draw a horizontal and vertical axes on a graph paper. Divide the horizontal axis into equal segments, one for each item. Scale the vertical axis in such a way that the top represents the total. Construct a bar graph with the most frequency first and the least frequency last.
Step 5: Next is to plot the cumulative line that sums up each column with the previous one. On the right hand side of the vertical axis, scale it from 0 to 100% which must correspond to the numbers on the left hand axis, the numbers and percentage of which can be obtained from the checksheet. The process for plotting each item must be done in relation to the bar graph drawn earlier. The cumulative line is complete when it reaches the 100% level as per the percentage scale on the right side. A legend may be added so that anyone reading the chart can understand.
Note:
Step 1: Calculate the range. Range=Largest Observed Value minus Smallest Observed Value.
Step 2: Determine Class Interval
Step3: Prepare the frequency table.
Step 4: Calculate mid value I.e: Upper limit plus lower limit divided by 2.
Step 5: Draw horizontal and vertical axis on a piece of graph paper. On the vertical axis indicate all class intervals.
Step 6: Transfer the data from the frequency table to the graph.
Class Interval
Mid
Value
Frequency Tally
Frequency
Trucks turn around time
Tally
Number of Trucks
(frequency)
10
6
15
9
20
33
25
46
30
65
35
40
40
26
45
8
50
5
Note:
Step 1: Take samples from lots. eg. Day 1 - 25 we have 25 different lots for purposes of analysing quality. Let the sample size be 10.
Step 2: Each day, we compute the mean i.e. add up and divide by 10
Step3: Each day, we calculate the range i.e Upper limit minus lower limit.
Step 4: We are now in a position to draw or construct a variable control chart.
Note:
Step 1: Collect paired samples of data whose relationship you wish to investigate
Step 2: Draw a horizontal and vertical axes of the graph with appropriate scale. If the relationship of the two variables are that of a cause and effect values on the vertical axis.
Step3: Plot the data on the graph. If data values are repeated and fall on the same point, make a circle.