1. Quality management degree
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I. Contents of quality management degree
==================
Read on for more information about degree and certificate programs in quality management.
Learn about each program's course requirements and prerequisites, and discover career
opportunities in the field.
or quality assurance, is a management style designed to assure quality in all organizational
processes. Programs in quality management are offered at the undergraduate certificate,
associate's degree, bachelor's degree, graduate certificate and master's degree levels. Each of
these programs teaches students the basics of the field and can prepare them for positions
where they will improve the quality of products or services through modifications in response
to customer feedback.
Undergraduate Quality Management Certificate
Community colleges, technical schools and continuing education departments of 4-year
institutions offer undergraduate certificates in quality management. This entry-level program
develops students' management abilities in quality-oriented settings through several focused
courses. Students are trained to be involved with employees through team building and conflict
resolution practices. Handling and managing change within an organization are also
emphasized. Other than the standard prerequisites for entrance to the school, students should
have a solid mathematics background.

2. Program Coursework
Courses emphasize positive change and improved efficiency within an organization. Problem
solving is a recurring theme in many quality management certificate programs, and students
can expect to explore the following additional topics:
 Corrective actions
 Problem identification
 Quality systems
 Improvement plans
Popular Career Options
Though an undergraduate certificate alone won't qualify individuals for high-level management
positions, it may serve as a credential for obtaining entry-level supervisory positions in retail or
manufacturing. Possible jobs are as follows:
 Shift supervisor
 Team leader
 Quality technician
Associate Degree Programs in Quality Management
Degree options at this level for quality management students include the Associate of Applied
Science (AAS) in Quality Assurance, AAS in Industrial Quality Management, AAS in Water
Quality Management and more. Students pursuing this level of training in quality management
will be introduced to the basic principles and terminology of statistical quality management and
total quality management. Students also learn math, statistics and other general courses.
Graduates with quality management training at the associate degree level can find positions
developing and managing policies and procedures that guarantee quality for a company's brand
image and products or services.
Educational Prerequisites
Associate degree programs that offer quality management training are primarily offered
through community colleges. Students are typically required to have a high school diploma or
equivalent. Specific enrollment and course prerequisites can vary by school.
Program Coursework
The curriculum of quality management and assurance programs at this level include
applications, principles, basic elements and other areas. The following are examples of
common course topics:
 Value engineering
 Computer applications
 Manufacturing
 Industry transformation

3. Popular Career Options
Associate degree training in quality management prepares graduates for entry-level quality
control and assurance positions. Students will develop the experience needed for quality
management careers through such positions as the following:
 Product weight assistant
 Manufacturing inspector
 Production test technician
Bachelor's Degree Programs in Quality Management
The Bachelor of Science (BS) with a quality management concentration and Bachelor of
Manufacturing Management (BMM) in Quality Management are two examples of
undergraduate programs that provide a 4-year quality management. Students enrolled in these
types of quality management programs typically take courses in statistical quality management
and total quality management. Manufacturing processes and the authenticity, normalization and
certification of quality products or services are also covered. Quality management students can
also complete an internship where they will work closely with technicians in factory settings to
enforce quality product and process conformity.
Educational Prerequisites
Bachelor's degree and certificate programs that offer quality management training typically
require students to have undergraduate coursework in statistics, physics, mathematics, science,
engineering or business.
Program Coursework
The quality management curriculum in a bachelor's degree program assists students in
developing the technical knowledge used in the field. The following are examples of the core
and elective course material:
 Statistics
 Compliance methods
 Marketing
 Strategic management
 Advanced quality control
Graduate Certificate in Quality Management
Those who have a bachelor's degree in a number of areas might be interested in a graduate-
level quality management certificate. Many people who enroll in such programs are already
working as quality management professionals in the engineering, science and manufacturing
fields, among others. These programs teach students the quality management methods used in
governmental and industrial settings.
Educational Prerequisites
Interested individuals need a bachelor's degree and documentable proficiency in statistical
methods. Students should also be competent with word processors and spreadsheets.

4. Program Coursework
Students will explore the fundamental concepts of quality management and will also take some
elective courses. Possible elective topics may include these:
 Engineering statistics
 Project planning
 Project policy
 Applied quality management
Master's Degree Programs in Quality Management
Master's programs in quality management, such as the Master of Science (M.S.) in Quality
Management and Master of Business Administration (MBA) in Quality Management, focus
more on the theoretical aspects and issues of quality control. Students earning quality
management master's degrees will cover such topics as quality functions within organizations,
quality standards, and quality control in industrial, statistical and quality engineering.
Graduates with quality management master's degrees can find careers within a variety of
different organizations, where they design, implement and monitor quality control programs
throughout the production process or customer experience.
Educational Prerequisites
Applicants to the M.S. and MBA programs in quality management programs should have a
bachelor's degree; however, the degree doesn't have to be in a specific field. Many master's
degree programs require coursework in science, business, mathematics and engineering. The
Graduate Management Admissions Test (GMAT) or Graduate Record Examination (GRE) is
also used as an admission requirement for some quality management degree programs at this
level.
Program Coursework
A capstone project and thesis research are often done during a quality management master's
degree program. The graduate-level quality management training is also achieved through
courses in areas such as process improvement, statistical and quality techniques, organization,
as well as classes covering:
 Project engineering
 Human factors in quality control
 Quality auditing
 Supply chain management
 Quality planning
Employment Outlook and Salary Information
Graduates with a bachelor's or master's degree in quality management can find careers as
quality control managers. These professionals' responsibilities include the adherence to quality
programs based on the policies and procedures they develop and maintain. The U.S. Bureau of
Labor Statistics (BLS) projects that the number of jobs for quality control inspectors will grow
by eight percent from 2010 to 2020. Similarly, the number of employed industrial production

5. managers is expected to increase nine percent during that time. Industrial production managers
earned a median salary of $89,190 in 2012, reported the BLS.
==================
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

6. 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

7. 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

8. 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.

9. 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

10. 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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