1. Strategic quality management
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I. Contents of strategic quality management
==================
Course Overview:
The course will create graduates that understand the theory and practical application of quality
management tools and techniques, with particular emphasis on the areas of Lean and Six Sigma
as they would apply to their own organisation. It will educate and train participants in specific
quality management skills in both the lean and six sigma domains and in strategic and
transferable business skills. A graduate of the programme will be considered a Master Black Belt
in Lean and Six Sigma.
Duration:
Course Progression is flexible and students can complete the programme in 2 to 3 years at a pace
that suits their work and family commitments. Participants can take 1 to 3 taught modules each
semester, until they complete the programme.
For Whom:
The MSc is designed for those with a responsibility for/or actively engaged in organisational
improvement and development through the use or intended use of quality management, lean or
six sigma methodologies. The programme is suited to a variety of industry sectors both in
manufacturing and services, including the public sector.

2. Entry requirements:
Applicants require a 2.1 degree (NFQ level 8) in any discipline or equivalent and at least three
years relevant work experience.
Applicants who have completed the Specialist Diploma in Lean Systems and/or Six Sigma are
eligible for exemptions from those modules on this programme.
Features:
•Master Content to Master Black Belt standard
•On-line interactive and non-interactive content
•Flexible course progression
•Moderated e-discussion boards
•On-line & email-tutor support
•Supplement face-to face tutorial sessions
•Peer supported study groups (on-line and off-line)
•Work based project- industrial mentor and academic supervisor
•Professionally designed learning material
Programme Structure:
Choose 2 or 3 modules from each semester block until the programme is complete. This can be
done in a minimum of 4 semesters but 6 semesters is the suggested duration.
Semester 01 Module Block Semester 02 Module Block
1. Lean Thinking/Lean Tools 1 1. Lean Thinking/Lean Tools 2
2. Lean Sigma, Project Management and
Finance
2. Leadership Change and Innovation
Management
3. Quality Science 1 3. Quality Science 2
4. Organisation Behaviour &
Development
4. Problem Solving Tools & Techniques
5. Strategic Business and Operations
Management
5. Information Systems and Software
Management

3. 6. Thesis 1 6. Thesis 2
Thesis is a work based project, applying the tools and techniques of Lean/Six Sigma with the
aim of generating a verified saving of significant benefit for the company, in the region of
€100,000.
Module Descriptions are available here
In Company Project - Thesis:
Programme completion requires a substantial industry based project, reported in the form of a
thesis. The expectation that the project would realise savings of €100,000for the participant
organisation. The project will require the application of the concepts covered in the course. The
output of the project should involve a significant benefit to the company. The Student,
Supervisor and Company will agree the success metric for the project as part of the topic
selection process.
Examples of success metrics could include:
•the improvement of a specified performance indicator by an agreed amount.
•the quantifiable addition of value to process or service which was the focus of the project.
•a cost saving of the order of €100,000 which must be verified by the company, or in the case of
a Small to Medium Enterprises, (SMEs, <250 employees), project savings must amount to 0.3%
of annual turnover.
An example could be a plant relay out that could result in cost savings through inventory
reduction to the value of €100,000, or an increase in machine efficiency by 5%, or a reduction
process cycle time by 10%.
The University of Limerick and several leading Irish companies designed this course to meet the
standards of a Master black belt. While there is no single authority that issues belts in Lean or
Six Sigma the industry group and university carried out extensive research in designing the
course to ensure that the course met the general standards that are expected of a black belt
holder. Master Black Belt projects are expected to save in the region of €100,000 for their
organisation. A Master Black Belt holder is expected to be competent in the tools and techniques
to organise and implement a project at this level, and to be capable of managing a number of
such projects simultaneously for their organisation in a strategic capacity.

4. Successful participants will receive a letter from the University of Limerick stating that their
course is at Master Black Belt level.
Delivery:
Delivery is a hybrid of traditional distance education and online learning together with a number
of on-campus tutorials (approx. 3 Saturdays per semester). In addition, there are online
discussions moderated by a subject matter expert on elements of each module to reinforce the
learning and maximise the benefit of the programme for participants.
Programme Fees:
As the number of modules taken each semester can vary, participants are charged €1,175 for
each module as they take them. The Research Thesis is €3,500 so the total cost of the programme
(10 taught modules plus thesis) is €15,250. Students will receive a list of recommended course
readings and text books for purchase.
==================
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)

5.  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.

6. 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

7. 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

8. 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

9. 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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