Quality management slogans

1. quality management slogans

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I. Contents of quality management slogans

==================
As we move to the next millennium, the ISO 9000 family of quality management system
standards is being updated to reflect a modern understanding of quality.
This article is based on the second committee drafts (CD 2) of the three basic standards in the
family. The reader should remember that these documents are subject to change as the standards
development process continues. They should not be used as a basis for changing existing
management systems.
The three basic standards in the ISO 9000:2000 family are:
 ISO 9000:2000, Quality Management Systems--Fundamentals and Vocabulary.
 ISO 9001:2000, Quality Management Systems--Requirements.
 ISO 9004:2000, Quality Management Systems--Guidelines for Performance
Improvement.
Each of these three documents has its own role in the family. ISO 9001 will remain the most
used of the three, but the other two are useful companions that should not be ignored.
Context for the update

2. Over the years, the world's view of how quality is created and assured has been evolving. This
natural progression did not directly create the need to revise the ISO 9000 family, but it may be
useful to view the proposed revisions in the context of the evolution of quality thinking.
The original ISO 9000 family was based on the understandings of an earlier era in which quality
was thought to be primarily a technical discipline--the purview of the quality professional. In the
1980s we discovered that this view was incomplete. We heard the slogan "Quality is a human
resources problem, not a technical problem." So programs were developed to get workers
involved in quality improvement.
Today most organizations understand that all work is accomplished through processes, which are
most effective when they are actively managed. As the 1990s advanced it became clear that
quality has both a technical and a human side.
There has also been an increasing interest by organizations other than traditional manufacturing
(such as the services sector, education, governmental agencies) in using ISO 9001 as a basis for
quality management. This has proven to be somewhat awkward because ISO 9001:1994 uses
language that is focused on manufacturing.
It is not surprising to find this maturing of quality thinking and application in the mid-1990s
reflected in revisions to quality system standards.
ISO Technical Committee (TC) 176, the group responsible for the ISO 9000 family, long
recognized that the standards needed an overhaul. In the early 1990s the committee put plans in
place to make the updates. These plans included the development of specifications for the
changes to ensure that the needs of users around the world would be met.
The specifications outlined how the ISO 9000:2000 revisions would resolve perceived
shortcomings with the current documents. These specifications created the criteria for a
significant advancement of the ISO 9000 family and reflect contemporary concepts of quality
management. The goals of the specifications are summarized in the sidebar "Goals for the New
Revisions."
Basic changes
Two types of changes are apparent with the latest committee drafts. There are:
 Changes in presentation, terminology and format.
 Changes in the actual requirements.

3. This article presents an overview of the changes in presentation, terminology and format. Future
articles will highlight changes in requirements in ISO 9001.
Quality management principles
As an initial step along the road to the ISO 9000:2000 revisions, TC 176 developed a consensus
on a set of quality management principles (QMPs). The principles were developed after research
of the quality concepts in use around the world. Many input sources were considered.
Eight principles resulted from this work and they have been used as a foundation for the
revisions (see sidebar "The Eight Quality Management Principles"). These principles appear in
both ISO 9000 and ISO 9004.
While the principles were a basis for developing ISO 9001, they do not formally appear in that
document. Each principle has a place within the ISO 9001 requirements, but the extent of
application to ISO 9001 is quite limited compared to its application in the new ISO 9004. ISO
9004 uses each principle fully to help organizations drive for excellence.
Format and presentation
The format of ISO 9001 and ISO 9004 has been changed to link the quality management system
with the processes followed by most organizations. The requirements of ISO 9001 are now given
as four primary processes.
The interrelationship of these four processes in the quality management system is
shown graphically in the quality management process model in Figure 1, which is
reproduced with the permission of the International Standards Organization (ISO).
The model may change as the standards progress through the draft stages. Each
process is described below:
 Management responsibility--Management sets direction and objectives of the system.
 Resource management--Resources are determined, provided and managed.
 Product and/or service realization management (called processmanagement in Committee
Draft 1)--Processes are established for creating and delivering the organization's products and
services and are verified and managed. Product realization processes take inputs from
customers in the form of requirements, needs and/or wants and convert them into the products
and services that satisfy customer requirements.
 Measurement, analysis and improvement--Products, processes and customer satisfaction or
dissatisfaction are measured. Audits are conducted of the quality management system. Data

4. are analyzed and results provided as input to the management review process. The data and
analysis are used to improve the system continually.
Terminology
There has been a major effort to use everyday English terms that are easily understood. This is
more difficult than it would seem. For example, the first committee draft attempted to avoid
jargon by using common words.
Unfortunately, a careful reading of the draft revealed that many of these common words have
several meanings. In many cases, when words were used multiple times in the draft, the various
uses had different intended meanings. Much of this has been corrected with the CD 2, but simple
language remains a challenge.
A good example of a shift to common language is the word used to describe an organization that
implements ISO 9001. In the 1994 edition, the term "supplier" is used. This is derived from the
initial focus of ISO 9001 as a tool to be used in a contractual relationship between a customer
and a supplier. The ISO 9001:2000 drafts have used the term "organization" to describe the
entity that implements the standard, and the term "supplier" has its normal English meaning.
Changes in actual requirements
This article has discussed reasons for a change in focus for the ISO 9000:2000 standards and has
introduced the quality management principles. It has also reviewed changes in format,
presentation and terminology. Subsequent articles in this series will discuss the QMPs in more
detail, particularly the changes in requirements that are included in the second committee draft of
ISO 9001:2000.

==================

III. Quality management tools


1. Check sheet

5. 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
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

6. 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.

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

7. 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
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

8. 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
 Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates


6. Histogram method

9. 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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