1. Quality management system process
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I. Contents of quality management system process
==================
This article is adapted from chapter two of the new Quality Press ASQ ISO 9000 Handbook
edited by Charles A. Cianfrani, Joseph J. Tsiakals and John E. "Jack" West. West is a member of
QP's regular panel of "Standards Outlook" columnists. The handbook provides insight on each
clause of ISO 9001:2000 by authors from around the world who were involved in the process of
writing the new standard. This article deals directly with the use of the process approach. Other
chapters in the handbook provide further insight into the use of the process approach in the
documentation of a quality management system and in continual improvement.
One of the most important aspects of the year 2000 revisions of ISO 9001 and ISO 9004 was the
adoption of the process approach to quality management systems (QMSs). A strong consensus
for adopting the process approach formed very early in the revision cycle.
This approach improves on that of the previous standard by providing a much more generic
structure readily applicable to all sectors of the economy and sizes of organization. At the same
time, it allows the requirements to be stated in language more familiar to line managers and less
encumbered by quality jargon.
ISO 9001:2000 focuses on improving the effectiveness of a QMS to enhance customer
satisfaction by meeting customer requirements, while ISO 9004:2000 focuses on improving the
effectiveness and efficiency of a QMS to enhance interested party satisfaction by meeting

2. interested party requirements. The common structure of the two standards is demonstrated
in Figure 1.
Understanding the approach
The process approach is one of the eight quality management principles upon which the entire
ISO 9000 series of standards is based. This principle says a desired result is achieved more
efficiently when activities and related resources are managed as a process.
The word "process" is defined in ISO 9000:2000 clause 3.4.1 as "a set of interrelated or
interacting activities that transforms inputs into outputs." Inputs to a process are generally
outputs of other processes. Processes in an organization are generally planned and carried out
under controlled conditions to add value.
From the principle and process definition you can see the process approach is a powerful way of
organizing and managing how work activities create value. While a more traditional structure
organizes and manages work activities vertically by function, with quality problems frequently
occurring at the boundaries of the functional departments, the process approach organizes and
manages work horizontally the way work activities create customer value.
The process approach directly links process inputs that come from suppliers to the
outputs of the process that go to customers. This horizontal linkage between
suppliers and customers is an excellent way to manage and continually improve both the
effectiveness (the amount of value created for the customers) and the efficiency of the process
(the amount of resources consumed). Figure 2 (p. 72) shows these relationships.
Methodology
Once the processes needed for the QMS and their sequences and interactions have been
identified (see Figure 1), it is necessary to establish management responsibilities and
accountabilities for the performance of these processes. Many methodologies are available for
managing and improving processes, but all share some simple basic elements. A simple process
management and improvement methodology organized in a series of steps is described in the
following:
Step one: Establish the responsibilities for managing the process. It is critical to have an
overall process manager or process owner with end to end responsibility and accountability for
all aspects of process performance. The process manager needs to understand the entire process
and have the authority to effect changes in any part of it.
The process manager is responsible for the following:

3.  Forming the process management team, which includes representatives from each major part
of the process.
 Ensuring the process operates in a controlled state of predictable performance.
 Establishing process performance measures that adequately characterize the efficiency and
effectiveness of the process in meeting the needs of all customers and other interested parties.
 Ensuring all aspects of process management and improvement are performed. This includes
creating documentation, tracking performance, and securing and allocating resources.
Step two: Define the process. The process manager and process management team need to
carefully define the process so everyone working within the process has a shared understanding
of how it operates. How much documentation is required depends on such attributes as the
stability and education of the workforce and the complexity and criticality of the process.
All process inputs and outputs are identified, along with the suppliers and customers, who may
be internal or external. The team also identifies process steps and flows. Many quality tools, such
as block diagrams and flowcharts, are available to support these activities.
Step three: Identify customer requirements. Carefully gather, analyze and document customer
needs, including how customers use the outputs of the process. Communicate frequently with
customers to understand needs from their viewpoint.
To the extent possible, define measurable customer needs and rank them in order of importance.
Directly validate needs and requirements with customers.
Step four: Establish measures of process performance. Translate customer needs and
requirements into measures of process performance. This is one of the most important and
difficult steps in process management.
Include customer satisfaction, in-process measures and measures of supplier performance in
process measures. Relate all important customer needs, such as on time performance, defect or
error rates, tolerance intervals, product reusability, and worker health and safety, to performance
measures.
The process approach is therefore one of the strongest approaches for integrating management
system standards because each process must be managed and improved simultaneously for all
process performance measures. Directly linking process performance measures with customer
needs is one of the most powerful aspects of process management.
Step five: Compare process performance with customer requirements. Use the process
performance measures to ensure your process is operating in a stable and predictable manner.

4. Compare the process performance measures with the needs and requirements of the customers.
Use a variety of statistical tools for analyzing process measurement data to help quantify process
performance. Identify critical process improvement opportunities through gaps in process
performance.
These first five steps provide a basic methodology for process management. But the
responsibilities of the process manager and process management team do not end there. A
significant benefit of process management is its natural fit with process improvement. Once
process performance has been compared with customer requirements, process improvement is
the natural next step.
Step six: Identify process improvement opportunities. Use gaps in process performance vs.
customer needs to determine critical process improvement opportunities. Analyze process
performance measures for improvement opportunities related to sources of such attributes as
errors and defects, process simplification opportunities, process bottlenecks and lack of adequate
process controls.
Both process effectiveness and efficiency can improve as a result of process improvement
activities. Many tools exist to identify process improvement opportunities.
Once process improvement opportunities are identified, any of the many quality improvement
methods can be used to improve process performance. These quality improvement methods fit
naturally into step seven of the process management and improvement methodology.
One quality improvement method that can be used at this step is the plan, do, check, act (PDCA)
cycle.
Step seven: Improve process performance. Select the process improvement opportunity to
pursue. This selection should take into account such attributes as the criticality of certain
improvement needs, difficulty of improvement opportunities, and resources and expertise
available.
Establish quality improvement teams to pursue specific improvement opportunities. These teams
are established by the process manager and process management team. The quality improvement
teams report to the process manager or the process management team and are typically disbanded
once their improvement project is completed.
The quality improvement teams complete the following activities:
 Clarify the improvement opportunity problem statement, schedule and budget.
 Determine the root causes of problems.

5.  Develop and implement countermeasures to reduce or eliminate the occurrence of root causes.
 Stabilize the process at the new level of performance.
 Return to step six or seven.
Support for the systemapproach
The process approach is an important part of the system approach to management. The process
approach assumes understanding and managing interrelated processes as a system can contribute
to an organization's effectiveness and efficiency in achieving objectives.
Using the process approach, a QMS is comprised of the following four categories of interrelated
processes (shown in Figure 1, p. 70):
 Management responsibility.
 Resource management.
 Product realization.
 Measurement, analysis and improvement.
Each process can be managed and improved using process management and improvement
methodology, but managing the interrelated processes as a system introduces additional
improvement opportunities.
First, processes can be analyzed and improved together as mega-processes, increasing the
opportunities for improvement. But you can also directly pursue improvement of the entire QMS
using audit and self-assessment (using 9004:2000 or quality award criteria) results and the
PDCA cycle.
The multiple levels at which continual improvement occurs make QMSs based on the process
approach a powerful way to manage organizations toward achieving performance excellence.
==================
III. Quality management tools
1. Check sheet

6. 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

7. 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

8. 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

9. 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

10. 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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