1. Deming qualitymanagement
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I. Contents of deming quality management
==================
W. Edwards Deming created a 14-point philosophy to be used by business, schools, hospitals —
any organization in which people work together to accomplish a task. The fourteen points
comprise a complete system. They are meant to be used together, because all are equally
important. When Deming was describing his system, he told people that they has a choice:
dedicate themselves to implementing the complete system — or none of it. There were no other
possibilities.
Influence of the Deming Philosophy
Deming’s influence is all around us. In 1981, when the Ford Motor Company advertised that
“Quality Is Job One!”, this sentence was part of a quality management program that Deming
helped Ford to create. General Motors and Toyota have also used Deming’s ideas. To build the
fabulous 777 jet, Boeing used a number of Deming concepts in a new management philosophy
called Working Together. Companies, hospitals, churches, and schools are all using Deming’s
Fourteen Points. The Department of the Navy has saved millions of dollars with the Deming
approach!
During the years that Deming helped companies, the expression “a Deming company” arose.
THNC would be honored if, from the beginning of our operations, we would also become known
as “a Deming company”, even in the absence of his personal involvement.
The Fourteen Points
1. Create Constancy of Purpose
You have to answer two questions: What are we doing? Why are we doing it? You must have a
long-term aim, something that every member of the organization knows and can understand.
2. Learn the New Philosophy
2. The old philosophy was to compete. The new philosophy is to cooperate in the organization so
that everyone can win.
3. Cease Dependence on Mass Inspection
Inspection does not add quality. Inspections tell you if quality is there. It is or is not, and
inspection cannot change it either way.
4. Don’t Buy on Price Tag Alone
This one used to send purchasing agents into fits, but more and more companies are finding out it
actually works.
5. Improve Constantly Every Process
This point is often misunderstood. You do get those leap-forward improvements using the
Deming management system, but you also get the smaller improvements between the leaps.
6. Institute Training for Skills
Part of training is about how to do the job and another part is about why the job is being done.
Unless everyone knows why they are doing a job, they cannot do it well.
7. Institute Leadership for People
Training for management must include training for leadership, an altogether different skill from
what has normally been required, which is supervision.
8. Drive Out Fear — Build Trust
To lead a company focused on improvements requires a whole different set of values and
attitudes and relationships than leading an organization focused on control.
9. Break Down Barriers Between Staff Areas
Build a system within your organization for win-win. This means cooperation. It means
abolishment of competition.
10. Eliminate Slogans, Exhortations, & Targets
How are you going to increase productivity? If the supplies are shoddy, the work force untrained
and fearful, the machines out of control, and the management system chaotic, productivity is not
going to be increased.
11. Eliminate Numerical Goals & Quotas
Deming told a story about the person with two job requirements… satisfying the calling
customers and taking 25 calls each hour. You can do either; you cannot do both.
12. Remove Barriers that Rob People of Joy
Abolish the annual rating or merit system which ranks people, creates competition, conflict.
13. Program of Education & Self-Improvement
Do not confuse education with training (point 6). Education has to do with anything whatever to
keep people’s minds developing.
14. Accomplish the Transformation
Knowing all that you now know does you no good at all if you do not put it to use. You must
develop a critical mass of associates who also believe it will work.
Learn more about Deming’s work…
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3. III. Quality management tools
1. Check sheet
The check sheet is a form (document) used to collect data
in real time at the location where the data is generated.
The data it captures can be quantitative or qualitative.
When the information is quantitative, the check sheet is
sometimes called a tally sheet.
The defining characteristic of a check sheet is that data
are recorded by making marks ("checks") on it. A typical
check sheet is divided into regions, and marks made in
different regions have different significance. Data are
read by observing the location and number of marks on
the sheet.
Check sheets typically employ a heading that answers the
Five Ws:
Who filled out the check sheet
What was collected (what each check represents,
an identifying batch or lot number)
Where the collection took place (facility, room,
apparatus)
When the collection took place (hour, shift, day
of the week)
Why the data were collected
2. Control chart
Control charts, also known as Shewhart charts
(after Walter A. Shewhart) or process-behavior
charts, in statistical process control are tools used
to determine if a manufacturing or business
process is in a state of statistical control.
If analysis of the control chart indicates that the
process is currently under control (i.e., is stable,
with variation only coming from sources common
4. to the process), then no corrections or changes to
process control parameters are needed or desired.
In addition, data from the process can be used to
predict the future performance of the process. If
the chart indicates that the monitored process is
not in control, analysis of the chart can help
determine the sources of variation, as this will
result in degraded process performance.[1] A
process that is stable but operating outside of
desired (specification) limits (e.g., scrap rates
may be in statistical control but above desired
limits) needs to be improved through a deliberate
effort to understand the causes of current
performance and fundamentally improve the
process.
The control chart is one of the seven basic tools of
quality control.[3] Typically control charts are
used for time-series data, though they can be used
for data that have logical comparability (i.e. you
want to compare samples that were taken all at
the same time, or the performance of different
individuals), however the type of chart used to do
this requires consideration.
3. Pareto chart
A Pareto chart, named after Vilfredo Pareto, is a type
of chart that contains both bars and a line graph, where
individual values are represented in descending order
by bars, and the cumulative total is represented by the
line.
The left vertical axis is the frequency of occurrence,
but it can alternatively represent cost or another
important unit of measure. The right vertical axis is
the cumulative percentage of the total number of
occurrences, total cost, or total of the particular unit of
measure. Because the reasons are in decreasing order,
the cumulative function is a concave function. To take
the example above, in order to lower the amount of
late arrivals by 78%, it is sufficient to solve the first
three issues.
5. The purpose of the Pareto chart is to highlight the
most important among a (typically large) set of
factors. In quality control, it often represents the most
common sources of defects, the highest occurring type
of defect, or the most frequent reasons for customer
complaints, and so on. Wilkinson (2006) devised an
algorithm for producing statistically based acceptance
limits (similar to confidence intervals) for each bar in
the Pareto chart.
4. Scatter plot Method
A scatter plot, scatterplot, or scattergraph is a type of
mathematical diagram using Cartesian coordinates to
display values for two variables for a set of data.
The data is displayed as a collection of points, each
having the value of one variable determining the position
on the horizontal axis and the value of the other variable
determining the position on the vertical axis.[2] This kind
of plot is also called a scatter chart, scattergram, scatter
diagram,[3] or scatter graph.
A scatter plot is used when a variable exists that is under
the control of the experimenter. If a parameter exists that
is systematically incremented and/or decremented by the
other, it is called the control parameter or independent
variable and is customarily plotted along the horizontal
axis. The measured or dependent variable is customarily
plotted along the vertical axis. If no dependent variable
exists, either type of variable can be plotted on either axis
and a scatter plot will illustrate only the degree of
correlation (not causation) between two variables.
A scatter plot can suggest various kinds of correlations
between variables with a certain confidence interval. For
example, weight and height, weight would be on x axis
and height would be on the y axis. Correlations may be
positive (rising), negative (falling), or null (uncorrelated).
If the pattern of dots slopes from lower left to upper right,
it suggests a positive correlation between the variables
6. being studied. If the pattern of dots slopes from upper left
to lower right, it suggests a negative correlation. A line of
best fit (alternatively called 'trendline') can be drawn in
order to study the correlation between the variables. An
equation for the correlation between the variables can be
determined by established best-fit procedures. For a linear
correlation, the best-fit procedure is known as linear
regression and is guaranteed to generate a correct solution
in a finite time. No universal best-fit procedure is
guaranteed to generate a correct solution for arbitrary
relationships. A scatter plot is also very useful when we
wish to see how two comparable data sets agree with each
other. In this case, an identity line, i.e., a y=x line, or an
1:1 line, is often drawn as a reference. The more the two
data sets agree, the more the scatters tend to concentrate in
the vicinity of the identity line; if the two data sets are
numerically identical, the scatters fall on the identity line
exactly.
5.Ishikawa diagram
Ishikawa diagrams (also called fishbone diagrams,
herringbone diagrams, cause-and-effect diagrams, or
Fishikawa) are causal diagrams created by Kaoru
Ishikawa (1968) that show the causes of a specific
event.[1][2] Common uses of the Ishikawa diagram are
product design and quality defect prevention, to identify
potential factors causing an overall effect. Each cause or
reason for imperfection is a source of variation. Causes
are usually grouped into major categories to identify these
sources of variation. The categories typically include
People: Anyone involved with the process
Methods: How the process is performed and the
specific requirements for doing it, such as policies,
procedures, rules, regulations and laws
Machines: Any equipment, computers, tools, etc.
required to accomplish the job
Materials: Raw materials, parts, pens, paper, etc.
used to produce the final product
Measurements: Data generated from the process
that are used to evaluate its quality
7. Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method
A histogram is a graphical representation of the
distribution of data. It is an estimate of the probability
distribution of a continuous variable (quantitative
variable) and was first introduced by Karl Pearson.[1] To
construct a histogram, the first step is to "bin" the range of
values -- that is, divide the entire range of values into a
series of small intervals -- and then count how many
values fall into each interval. A rectangle is drawn with
height proportional to the count and width equal to the bin
size, so that rectangles abut each other. A histogram may
also be normalized displaying relative frequencies. It then
shows the proportion of cases that fall into each of several
categories, with the sum of the heights equaling 1. The
bins are usually specified as consecutive, non-overlapping
intervals of a variable. The bins (intervals) must be
adjacent, and usually equal size.[2] The rectangles of a
histogram are drawn so that they touch each other to
indicate that the original variable is continuous.[3]
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