1. Risk and quality management
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I. Contents of risk and quality management
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In the world of quality management systems (QMS), the nature of the relationship between risk
management and preventive actions is often confused and misunderstood. Indeed, some believe
that a thorough risk assessment process replaces the need for preventive action.
In fact, risk management and preventive action are sequential, complementary elements that are
essential to the QMS. The effectiveness of any preventive action depends on the extent to which
the action addresses the root causes identified by the risk assessment. Therefore, the success of
the risk assessment process depends on the extent to which it identifies root cause issues. When
all root cause issues have been identified, it is possible to examine the proposed preventive
actions to determine if all elements of risk have been satisfactorily addressed.
Risk assessment of changes to a QMS
All of the elements described in an ISO 9001-compliant QMS can benefit from a risk assessment
evaluation. Let’s examine some of these elements from the risk management perspective.
• Documentation. A risk assessment of process documentation should be tangible since, by
definition, process-related documents very specifically describe a process. The amount of detail
required here depends on a risk assessment of the available training and the competence of the
users. Even more critical in a risk assessment of documentation is an assessment of the potential
risk associated with an incorrect interpretation of the documentation itself.

2. • Management Review. Documentation of the management review process should include a
commentary on changes to the QMS. Although there is often a minimal amount of such
commentary found in management review records, it can help to identify specific actions taken
by business units or departments. However, when evaluating action items by department, the risk
assessment of changes affecting anything from personnel to tools to work environment is often
incomplete. Actions undertaken in support of continuous improvement efforts must incorporate a
risk assessment to understand their potential effect on related processes.
• Competency and training. Continuous employee involvement is essential in any QMS
initiative. As quality processes and actions are implemented, the absence of employee
involvement can lead to non-conforming actions that can directly and negatively affect product
quality, an aspect of implementation that is frequently overlooked. Therefore, risk assessment
evaluations should include the potential consequence of non-involvement by employees.
• Planning, customer-related processes, design, purchasing and production. Any organization
considering the implementation of a QMS is focused on two key processes. First, the
organization must identify the needs of the customer (i.e., the end-user), and second,
management must self-assess the organization’s ability to satisfy those requirements. In the first
key process, potential risks include miscommunications, such as unmet expectations based on
unspoken assumptions. Therefore, the assessment of all input requirements for a proposed
product must include input from all involved parties. The second key process requires an
objective assessment of the organization’s capabilities in product design, manufacturing, and
other activities. Here too, a risk assessment can identify areas where capabilities may fall short of
customer expectations.
• Measurement, analysis, and improvement. These areas are the most important risk assessment
elements of a QMS. Again, preventive action as applied within the QMS is often misinterpreted
as the risk assessment process. Preventive actions are actually the result of an effective risk
assessment, and the subsequent analysis of its actual effect provides the ultimate assessment of
the effectiveness of the actions taken. Therefore, any proposed actions for improvement should
include an assessment of possible risks associated with their implementation.
Grading identified risks
The assessment of risk related to a QMS process can be graded according to a number of metrics,
such as its effect on a related process or the effect on a customer. However, viewing a risk
assessment solely as a preventive action within a QMS limits its usefulness. A documented risk
assessment must include information on inputs, process controls, and outputs, and can be useful
in grading risks over time. Effective record keeping can support efforts to grade the effect of a
correction action once it has been implemented.
Effectiveness of actions resulting from a risk assessment

3. Every effective QMS includes some form of risk assessment, whether it has been expressly
identified as such or not. However, evaluating actions stemming from a risk assessment is not
always clear. When a specific risk has been identified, it usually leads to a clear statement of
what will happen if certain actions are not taken. When preventive actions based on possible but
not proven risks are implemented, however, the results are often difficult to verify. That’s
because of the absence of objective evidence that the actions taken are directly responsible for
preventing the risk from occurring.
In other cases, an action taken to reduce or eliminate a possible risk can inadvertently affect a
related process. Often, this potential effect is neither identified nor investigated. When the
potential risk does not occur, the effect of the related process is not considered as a possible
cause.
==================
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)

4.  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
individuals), however the type of chart used to do
this requires consideration.
3. Pareto chart

5. 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

6. 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.

7. 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]
III. Other topics related to Risk and quality management (pdf download)
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