The document provides guidelines for quality management system documentation. It discusses that ISO 9001 requires certain documentation like a quality manual, procedures, and records. It recommends structuring documentation in a hierarchy with a quality manual at the top level providing an overview of the quality management system, followed by more detailed procedures and work instructions. The document also describes six common quality management tools: check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, and histograms. These tools can be used to collect and analyze quality data.

1. Guidelines for quality management system documentation
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I. Contents of guidelines for quality management system documentation
==================
Usually, when people think of quality management system documentation, they envision loads of
documents, and unnecessary and bureaucratic procedures. This is because companies often go
overboard when documenting their quality management systems. However, this doesn’t need to
be the case.
It is true that the international standard for quality management systems (ISO 9001) requires
certain documentation (see this article: List of Mandatory Documents for ISO 9001). The
purpose and the benefits of the QMS documentation are manifold: it provides a clear framework
of the operations in an organization, it allows consistency of processes and better understanding
of the QMS, and it provides evidence for achievement of objectives and goals. When designing
QMS documentation, you should focus on efficiency and create processes and documents that
are applicable in your organization.
QMS documentation hierarchy
The QMS documentation can consist of different types of documents. Usually, it includes
documents such as quality policy, quality manual, procedures, work instructions, quality plans,
and records. The QMS documentation can be represented as a hierarchy as shown in the diagram
below:

2. ISO 9001 requires different types of information to be documented; however, not all information
needs to be documented as separate documents. It is flexible so that the organization to decide on
the size of the documentation and the level of details documented. For example, small companies
can have documented procedures that will be included in the QMS manual.
How to structure your QMS documentation
The international standard ISO 10013:2001 Guidelines for quality management system
documentation gives directions for effective dimensioning of the QMS documentation, as well as
an overview of recommended contents and structure of the different QMS document types. The
following recommendations take into consideration the ISO 10013 guidelines.
1) Quality manual. The manual should fit your organization. The structure and the content of
the manual can vary depending on the size of the organization, the complexity of operations, and
the competence of the personnel. Small organizations can document the entire QMS in one
manual. On the other side, large international organizations may have several different quality
manuals. Generally, the manual includes the QMS scope, exclusions from the standard,
references to relevant documents, and the business process model. The quality policy and the
objectives can be part of the manual as well.
The quality manual should include most of following elements: title and table of contents; scope
of the QMS; exclusions from ISO 9001, versioning information and approval; quality policy and
objectives; QMS description, the business process model of the organization; definition of
responsibilities for all personnel; references to relevant documents and relevant appendices.

3. More information on how to document an effective quality manual can be found in this
article: Writing a short Quality Manual.
2) Quality policy. A policy represents a declarative statement by an organization. A Quality
policy should state the commitment of the organization to quality and continual improvement.
Usually, this policy is used for promotional purposes and should be displayed in the
organization’s premises and posted on websites, so a clear and short quality policy is convenient
and is the general practice.
The Quality policy defines the quality objectives to which the organization strives. The quality
goals of organizations are defined by quantifying the quality objectives.
3) Quality procedures. Quality procedures can have different formats and structures. They can
be narrative, i.e., described through text; they can be more structured by using tables; they can be
more illustrative, i.e., flow charts; or they can be any combination of the above.
Quality procedures should include the following elements:
 Title – for identification of the procedure;
 Purpose – describing the rationale behind the procedure;
 Scope – to explain what aspects will be covered in the procedure, and which aspects will not
be covered;
 Responsibilities and authorities of all people/functions included in any part the procedure;
 Records that result from the activities described in the procedure should be defined and listed;
 Document control – identification of changes, date of review, approval and version of the
document should be included in accordance with the established practice for document
control;
 Description of activities – this is the main section of the procedure; it relates all the other
elements of the procedure and describes what should be done, by whom and how, when and
where. In some cases, “why” should be clarified as well. Additionally, the inputs and the
outputs of the activities should be explained, including the needed resources.
 Appendices may be included, if needed.
4) Work instructions. Work instructions can be part of a procedure, or they can be referenced in
a procedure. Generally, work instructions have a similar structure to the procedures and cover the
same elements; however, the work instructions include details of activities that need to be
realized, focusing on the sequencing of the steps, tools, and methods to be used and required
accuracy.

4. Training of personnel and use of competent personnel can decrease the need for highly detailed
work instructions. More detail on this topic can be found in Using Competence, Training and
Awareness to Replace Documentation in your QMS.
Good QMS documentation is essential for an effective quality management system
Dimensioning the QMS documentation based on your organizational needs is essential for a
functional QMS. Moreover, properly structured documentation will make your operations much
easier, while incorrect documentation will bring you nothing but trouble.
==================
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

5. 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
individuals), however the type of chart used to do
this requires consideration.
3. Pareto chart

6. 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
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

7. 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
exactly.

8. 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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