The document discusses quality management system definition and related topics. It defines a quality management system as a system that aims to reduce inconsistencies in standards, customer expectations, and specifications in an efficient and cost-effective manner. It also provides examples of other management systems such as project management information systems and grants management systems. Finally, it discusses various quality management tools including check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, histograms, and others.

1. Quality management system definition
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I. Contents of quality management system definition
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The trends in the business have changed drastically when compared to the previous decades. The
management system plays up an essential role in making the company successful. There
management systems can be classified into many types based on the field. Some of the examples
of management systems are: project management information system, employee management
system, grants management system, quality management system etc. The quality management
system definition can be stated in many ways but in general a quality management system
definition sates that, it is a system through which a specific organization aims to lessen and
eliminate the inconsistencies in standards, customer expectations and specifications in a most
cheap as well as efficient manner. When it comes to quality, then it requires certain factors to be
considered which are as follows:
The expectations and requirements of the customers must be jotted down clearly in order to
make proper decisions.
The quality objectives and quality policies must be clearly defines as well as understood by the
people working in the organization.
The different methods and approaches to meet the goal need to be defined clearly and
implemented.
The various responsibilities and processes must be managed properly in order to achieve the
target.
In order to meet the requirements or goals, well infrastructure and resources are required.
The process of verification and product’s quality must be clearly defined.

2. The following are some of the management systems along with their explanations:
Project management information system: The acronym is PMIS and it helps the organizations to
plan, design, implement and execute the different phases properly. It makes sure that the steps
which are taken in each phase are correct or not. It is generally an electronic system which
contains techniques and tools to collect, disseminate and integrate the outputs of a particular
project. The organizations who do not use such systems can be very successful in finishing the
projects on time but if it uses a PMIS, then it will help the organization to know the scope, goals,
time period and cost of a particular project. The basic concept of this system is to manage all the
tasks in regard to the project. The information are collected, distributed and synthesized through
manual as well as electronic channels. The projects that are small need not require a PMIS but
for the large projects, it is very essential to make use of this system. Before you decide to buy a
PMIS, the following things have to be considered:
The existing hardware as well as software must be well integrated.
Make sure that the tool you buy must be cost effective and you get good returns after using it.
There must be a training session given to the people of the organization who will be involved in
using this tool.
Grants management system: For many years the educators were using different grants systems to
get better and organized information from the grant administrators, students, faculty and other
people who work in the university. But today there are enormous grants systems to choose from.
All you need to do is to select the right one based on the requirements. Using this system has
several advantages like:
It reduces the work of the employees and saves a lot of time. Management will be amazed to see
the rapid growth in the work carried out by their employees.
It helps to increase the productivity. The college’s productivity will increase to a great extent.
There will be a proper control in performing the various functions.
The records and data are secured in a proper way.
It helps in generating real time outputs or reports.
==================
III. Quality management tools
1. Check sheet

3. 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

4. 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

5. 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

6. 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

7. 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 system definition (pdf
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