Web based quality management system

web based qualitymanagement system
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I. Contents of web based quality management system
==================
In highly regulated environments (such as pharmaceutical, medical device, biotech, blood/tissue,
and similar industries), Web-based quality management software systems (QMS) are essential to
the development of efficient processes and for helping companies stay ahead of the competition.
The Quality Conundrum Solved with Web-based Quality Management Software
Quality professionals have to manage multiple responsibilities while keeping their organizations
on track toward regulatory compliance and success in the marketplace. However, there are
countless challenges that arise on that quality path such as disconnected quality systems,
ineffective general purpose tools, lack of management support, and similar obstacles.
In the current market environment it is absolutely mandatory that quality teams are armed with
specialized, automated tools to achieve their organizational goals. What could be more valuable
to a company doing business in a regulatory environment than having the right tool for the right
job at the time you need it most? MasterControl's web-based QMS can help.
The MasterControl Web-based Quality Management Software System (QMS)
We all want to get the most "bang for our buck," and companies doing business in regulated
settings are no exception. An affordable and efficient web-based QMS and maximum ROI are
necessities in order for organizations to thrive in the current competitive market.
MasterControl, a leading global provider of quality management software systems, helps
companies affordably accelerate compliance. The MasterControl quality management solution
suite has been successfully implemented, validated, and inspected in regulatory environments

around the world for two decades. Organizations worldwide use MasterControl's web-based
quality management software systems to manage, control, and maintain accurate quality
processes and documentation in order to align their practices with standards established by
regulatory entities such as the FDA, ISO, and EMEA.
Benefits of MasterControl Web-based Quality Management Software Systems
An effective QMS software solution like MasterControl makes it possible for organizations to:
 Accelerate and automate essential quality processes such as CAPA, customer complaints,
deviations, change control, audits, non-conformance, and so forth
 Automate documentation processes like document change, distribution, notification, and
approval in order to reduce the time it takes for products to get to market
 Utilize a Web-based quality management software system that is ready right out of the
box but also customizable to suit your specific organizational needs
 Take advantage of a system that is specially designed to be quickly implemented and
validated
 Ensure the integrity of regulatory documentation and standard operating procedures
(SOPs)
 Route documents electronically along pre-defined workflows for more efficient
distribution, collaboration, and approvals
MasterControl's Web-based quality management software system also allows organizations to do
the following with relative ease:
 Maintain compliance with stringent regulatory requirements such as 21 CFR Part 11
 Establish a bleeding-edge web-based QMS architecture
 Accelerate compliance
 Support standard databases used in life sciences and similarly regulated environments
 Take advantage of form-to-form launching
 Track forms by status or history ("in process," "complete," etc.)
 Maintain active links so users can review a completed process to see what event caused
or merged with another event
 Integrate with existing document repositories and enterprise applications such as ERP,
LIMS, etc., without custom coding
 Integrate forms with training control (i.e., any change to a document or process that calls
for new training can be set to automatically trigger training tasks)
MasterControl also offers unparalleled education, product training, and technical support to
ensure that customers are able to maximize their investment in their quality management
software.
==================

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

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.

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

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

 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 web based quality management system (pdf
download)
quality management systems
quality management courses
quality management tools
iso 9001 quality management system
quality management process
quality management system example
quality system management
quality management techniques

quality management standards
quality management policy
quality management strategy
quality management books

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