1. Implementing quality management system
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I. Contents of implementing quality management system
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Step 1: Commitment from Top Management
The top management of an organisation should be determined and committed to implement
aquality management system. No quality initiative within an organisation can succeed without
commitment from top management. Top management can demonstrate to their clients that the
organisation is committed to quality through the certification and registration of the ISO
9000standard. Top management should thus come to the realization that overall business
efficiency would be improved by means of a quality management system.
Step 2: Establishing an Implementation Team
People are responsible for the implementation of ISO 9000. An implementation team, headed by
a Service Provider and a Management Representative (MR), is to be established. The Service
Provider and MR is the coordinator and is responsible for planning and overseeing the
implementation of the quality management system. He is thus the link between top management
and the ISO 9000 registrar. All departments within the organisation should be represented on the
implementation team.
Step 3: Conducting ISO 9000 Awareness Programs
Conducting ISO 9000 awareness programs will inform all employees about the aim of a quality
management system. These include the advantages offered to customers and employees, their
respective responsibilities and roles within the system, and how the quality management
system operates. The benefits that an organisation hopes to realize through a quality management
system implementation should be emphasized through ISO 9000 awareness programs.
Step 4: Providing Training
All personnel and all areas in an organisation are affected by a quality management system.
Training regarding the quality management system should thus be provided for all employees.

2. The quality management system implementation plan should make provision for this training.
All basic concepts of quality management systems and its impact on the organisation should be
covered.
Step 5: Conducting an Initial Status Survey
A quality management system conforming to the ISO 9000 standard should be created. However,
this does not preclude incorporating, adapting, or adding onto quality programs that already
exists. Thus, this step basically involves comparing an organization’s existing quality
management system (if there is one) with the requirements of ISO 9001:2008.
Step 6: Creating a Documented Implementation Plan
Once an organization’s quality management system has been compared with the ISO 9001:2008
standard, a documented implementation plan is used to address any non-conformances. The
documented implementation plan identifies and describes processes in order to make the
organization’s current quality management system in full compliance with the ISO 9000
standard.
Step 7: Developing a Quality Management System Documentation
Documentation is an area where non-conformance regarding quality management systemsare
very common. In order to avoid these non-conformities, documentation of a quality management
system should include the following:
 Documented statements of a quality policy and quality objectives;
 A quality manual;
 Documented procedures and records required by the standard of ISO 9001:2008; and
 Documents needed to ensure effective planning, operation and control of its processes.
Step 8: Control of Documents
In order to control quality management system documentation, a documented system should be
created. The creation, approval, distribution, revision, storage, and disposal of various types of
documentation are thus managed. Document control systems should be as easy and simple to
operate as possible. However, it should still be sufficient enough to meet the requirements of ISO
9001:2008.
Step 9: Implementation
In large organizations, it is best to implement the quality management system being documented
as the documentation is developed. This is in stark contrast to smaller organizations, where
the quality management system is implemented throughout the organisation all at once. During
phased implementation, however, an evaluation can take place regarding the effectiveness of the
system in different areas.
Through management review and an internal quality audit, the implementation progress is
monitored to ensure that the quality management system is effective and thus conforms to the
IS0 9000 standard
Step 10: Internal Quality Audit
The effectiveness of the installed system should be checked regularly by means of an internal
quality audit. Below are some reasons for conducting an internal quality audit into a quality
management system:

3.  To ensure that the quality management system conforms to the quality management
system requirements established by your organization, as well as to the requirements of
the ISO 9001:2008 standard; and
 To ensure that the quality management system is implemented and maintained in an
effective manner
Step 11: Reviewing by Management
A management review should be conducted three to six months after quality management
system implementation took place. The reasons for conducting management reviews are to
ensure continuous effectiveness, adequacy, and suitability of the quality management system.
Step 12: Pre-assessment Audit
Before applying for certification, a pre-assessment audit usually takes place. Certification bodies
provide a qualified but independent auditor to conduct this service. Some degree of confidence is
gained before application for certification if the pre-assessment audit goes well
Step 13: Certification and Registration
A formal application for certification is made at a certification body as soon as the quality
management system has been operating for a few months and has stabilized. An audit of the
documents (known as an adequacy audit) is first carried out, and if it conforms to the
requirements of the quality standard, it is followed by an on-site audit. A certificate is only
awarded to the organisation if the certification body is satisfied with the workings of the system.
However, the certificate is valid for a period of three years only, after which the certification
body will carry out periodic surveillance audits.
Step 14: Continual Improvement
Although an organisation gained certification, it is important to note that it has to try and
improve the suitability and effectiveness of the quality management system on a continuous
basis.
==================
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.

4. 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
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

5. 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
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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