1. Approaches to quality management
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I. Contents of approaches to quality management
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It's wise to evaluate approaches of Total Quality Management (TQM) that best suit your type of
business, your personal management style, and your customers. Here we're looking at three of
the top favorite management processes: Empowering your team, Pareto charts, and ISO quality
procedures.
What is TQM?
As you consider your approaches of Total Quality Management (TQM), you have to evaluate
which methods best suit your company and your management style. The term came from the
teachings of the late statistician and industrial consultant, W. Edwards Deming, who promoted
five basic principles:
Reduce errors that occur during the manufacture or presentation of a product or service.
Render efficiency among the components (staff or company departments) necessary to produce
the product or service.
Utilize the most modern equipment or procedures available.
Maintain constant levels of employee training and education.
Assess levels of customer satisfaction.
Some of Deming’s most renowned work centered on adhering to qualify specifications, but
Deming believed in more than slide rule measurements and calibration techniques. His formula
for success focused on quality as the outcome of work efforts divided by the total costs. This

2. theory held that by concentrating on manufacturing a quality product, costs would naturally
decline over time. Conversely, Deming believed that when companies focused all their efforts on
reducing costs, then quality was jettisoned. There are multiple approaches of Total Quality
Management, and many managers like these three best:
Create the Ultimate TQM Environment
Employees and departments should not feel as if they are in competition with one another. If you
are managing TQM, then your primary goal is to ensure that you instill a sense of pride in your
workers that will build cross-functional teams of employees. Lessen your focus on merit
increases and statistical achievements, and increase attention toward the individual’s
contribution. Reward self-improvement and cooperative efforts among employees. When
product tests show repeatedly demonstrable improvements, celebrate the success with your staff.
Your approach with clients should be to offer a quality product, not the cheapest-possible
product or most-quickly-produced product. A company that follows this formula might
experience higher costs in the beginning, but as workers become accustomed to details of the
job, the processes will become streamlined—and thus less costly—as a natural byproduct.
Utilizing Pareto Charts
While Deming eschewed too much attention to statistics, it’s true that charting can clarify causes
versus their effects. The Pareto chart illustrates the principle put forth by Italian economist
Vilfredo Pareto that approximately 80 percent of your defects come from 20 percent of your
problems. Create a Pareto chart to display what you believe are current negative factors in a
given area; note where the line you have plotted along your x-axis meets the 80% mark on your
y-axis. Whatever you capture to the left of that line is important. Whatever is on the right might
be bothersome to you personally, but its overall effect on your product or service quality is
negligible.
ISO: Setting Standards for Consistency
The ISO has been around since 1947, and many companies are certified in one or another level
of ISO standards. It trains groups of employees to function consistently in performance of job
duties in order to ensure predictable outcomes. Whether or not your company achieves ISO
certification, the wise supervisor appreciates the importance behind a standardization process.
Why is it so important to practice consistency? Consider the last time you took a

3. cardiopulmonary resuscitation class. You learned that if you come upon an unconscious victim,
there is a series of steps through which you must proceed if you want to pass the course (and, of
course, revive the victim). You cannot bypass the seemingly simple steps; you’ve got to check
that the environment is safe, you must shake and shout to the victim, and next call 911. Only
then can you perform the seemingly more important steps such as checking for breathing, tilting
back the head, and giving your initial rescue breaths. But by learning each step in order by rote,
you are learning a mnemonic; if need to put your skills to use in a true emergency, you will
automatically perform all the correct steps.
The same applies to standardization of procedures within a company. It’s wise to review policies
and procedures across all departments and determine where cross-training will render your
employees able to act uniformly and efficiently, whether it applies to product development,
customer satisfaction, or any other area of procedure. Uniformity of process can result in vivid,
satisfying achievements.
Result: A Corporate Culture Based on Quality
Remember: You can combine various approaches of Total Quality Management to best suit your
company, your product or service, and your management style. As you steer your corporate
culture toward appreciation of each contributing employee as well as the customer, your quality
will climb and your costs will drop.
==================
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:

4.  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
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

5. 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.
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

6. 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
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

7. 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
 Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method

8. 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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