1. quality management policy statement
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I. Contents of quality management policy statement
==================
When tendering for a contract, you will have to show the buyer that you can be relied upon to
deliver the project to the required standard, on time. But how? This is where a quality statement
comes in – a document that explains the skills, experience and expertise that you can bring to the
job. Here's how to write one.
When a buyer puts a project out to tender, the buyer looks at a whole range of different factors to
help choose the right supplier. Key factors might include:
Cost – the initial costs (ie the price paid to the supplier) and the lifetime costs. For example,
initially more expensive but energy-efficient equipment might work out cheaper in the long
run.
Technical performance – for example, the materials used, how suitable the finished product is
for its purpose, durability.
Project management – including delivering the completed project on time and minimising any
risks.
Sustainability – the broader impact of the project on the environment, local community, and so
on.
When you submit your bid, some of these elements can be included in a direct way: for example,
you can quote a price and provide a specification of what you plan to deliver. But others are less
straightforward: how do you show that you will finish the project on time, to the required
standard?
2. What is a quality statement?
The quality statement deals with this problem. You may already have a quality statement for
general use in your business or you can create one as part of your response to a tender. It should
help to convince the buyer that you are the right supplier for their needs.
A quality statement lays out your firm's working practices and commitment to providing a good
service. It should explain how effective and efficient your methods of carrying out the project
will be.
Quality statements and tenders
When creating your quality statement, bear in mind that you will need to customise it extensively
for every tender. The Office of Government Commerce advises businesses: "There are no hard
and fast rules about what type of quality statement might be asked for, as it very much depends
on the type of procurement, the requirements, whether or not quality standards are an important
issue, and part of the evaluation criteria. These are matters which departments need to consider
on a case-by-case basis, taking account of value for money and EU regulations."
What does a quality statement include?
Typically, a quality statement covers issues such as:
How you would approach and manage the project
Your quality management system, and whether you are accredited to any standards (eg ISO
9001 or any specific standards for your type of product)
Compliance with legal requirements, and your policies in areas such as health and safety,
equality and sustainability
The qualifications and experience of key personnel
Previous experience of similar projects, including references
Often, the buyer will tell you what information you need to include in your quality statement –
for example, asking you to include a copy of your health and safety policy – and explain how
your quality statement will be assessed.
Bear in mind that quality management systems are not the same as quality statements. A quality
management system is a way of measuring your firm's internal processes, often with external
accreditation from organisations such as the International Organization for Standardization
(ISO). If you have systems or standards like this in place, you should include details as part of
your quality statement, but you must also provide the other information you are asked for.
Supplying complete information is essential: if you do not, your bid will probably be ruled out,
no matter how good it is in other areas.
==================
3. 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
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
4. 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
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.
5. 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
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
6. 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.
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
7. Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method
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 quality management policy statement (pdf
download)
quality management systems
quality management courses
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iso 9001 quality management system
quality management process
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quality system management
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