Course descriptions : Manufacturing

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Minitab Statistical Software
Introduction to Minitab
Decrease the time required for statistical
analysis by quickly learning to navigate
Minitab’s user-friendly and customizable
environment. Learn how to import/export data
and output between Minitab and various
software and database systems. Enhance your
ability to create, manipulate, and restructure
data. Develop sound statistical approaches to
data analysis by learning how to create and
interpret a wide variety of graphs and
numerical measures useful for quality
improvement initiatives. This course focuses
on the utilization of these tools as they
pertain to applications commonly found in
manufacturing, engineering, and business
processes.
Topics covered in the training material
include: Charts, Histograms, Boxplots,
Dotplots, Scatterplots, Tables, Measures of
Location and Variation, ODBC
Prerequisite: None. This course is a
prerequisite for all other general Minitab
courses.
Basic Statistics
Augment your graphical analysis skills using
Minitab’s powerful statistical tools. Develop
the foundation for important statistical
concepts such as hypothesis testing and
confidence intervals. By analyzing a variety of
real world data sets, learn how to match the
appropriate statistical tool to your own
applications and how to correctly interpret
statistical output to quickly reveal problems
with a process or to show evidence of an
improvement. Learn how to explore critical
features in your processes through statistical
modeling tools that help to uncover and
describe relationships between variables. A
strong emphasis is placed on making good
business decisions based upon the practical
application of statistical techniques commonly
found in manufacturing, engineering, and
research and development endeavors.
Topics covered in the training material
include: t-Tests, Proportion Tests, Tests for
Equal Variance, Power and Sample Size,
Correlation, Simple Linear and Multiple
Regression, ANOVA and GLM
Prerequisite: Introduction to Minitab
Optional Topic for On-Site Training:
Nonparametric Tests
Statistical Quality Analysis
Develop the necessary skills to successfully
evaluate and certify manufacturing and
engineering measurement systems. Learn the
basic fundamentals of statistical process
control and how these important quality tools
can provide the necessary evidence to improve
and control manufacturing processes. Develop
the skills to know when and where to use the
various types of control charts available in
Minitab for your own processes. Learn how to
utilize important capability analysis tools to
evaluate your processes relative to internal
and customer specifications. The course
emphasis is placed on teaching quality tools
as they relate to manufacturing processes.
Topics covered in the training material
include: Gage R&R, Destructive Testing, Gage
Linearity and Bias, Attribute Agreement,
Variables and Attribute Control Charts,
Capability Analysis for Normal, Non-normal
and Attribute data
Prerequisites: Introduction to Minitab and
Basic Statistics
Optional Topic for On-Site Training:
Acceptance Sampling for Attribute and/or
Variables Data
Factorial Designs
Learn to generate a variety of full and
fractional factorial designs using Minitab’s
intuitive DOE interface. Real-world
applications demonstrate how the concepts of
randomization, replication, and blocking form
the basis for sound experimentation practices.
Develop the skills necessary to correctly
analyze resulting data to effectively and
efficiently reach experimental objectives. Use
Minitab’s customizable and powerful graphical
displays to interpret and communicate
experimental results to improve products and
processes, find critical factors that impact
important response variables, reduce process
variation, and expedite research and
development projects.
Topics covered in the training material
include: Design of Factorial Experiments;
Normal Effects Plot and Pareto of Effects;
Power and Sample Size; Main Effect,
Interaction, and Cube Plots; Center Points;
Overlaid Contour Plots; Multiple Response
Optimization
Prerequisites: Introduction to Minitab and
Basic Statistics
Advanced Regression and ANOVA
Continue to build on the fundamental
statistical analysis concepts taught in the
Basic Statistics course by learning additional
statistical modeling tools that help to uncover
and describe relationships between variables.
Hands-on examples illuminate how modeling
tools help reveal key inputs and sources of
variation in your processes. Learn how to use
statistical models to investigate how
processes may behave under varying
conditions. This course provides techniques to
help you better understand your processes and
to focus and verify your improvement efforts.
Topics covered in the training material
include: Multiple and Stepwise Regression;
GLM with Covariates, Nesting and Random
Factors; MANOVA; Binary and Nominal Logistic
Regression
Prerequisites: Introduction to Minitab and
Basic Statistics
Response Surface
Expand your knowledge of basic 2 level full
and fractional factorial designs to those that
are ideal for process optimization. Learn how
to use Minitab’s DOE interface to create
response surface designs, analyze
experimental results, and find optimal factor
settings. Learn how to experiment in the real
world by using techniques such as sequential
experimentation that balance the discovery of
critical process information while being
sensitive to the resources required to obtain
that information. Learn how to find factor
settings that simultaneously optimize multiple
responses.
Topics covered in the training material
include: Central Composite and Box-Behnken
Designs, Calculations for Steepest Ascent,
Overlaid Contour Plots, Multiple Response
Optimization
Prerequisites: Introduction to Minitab, Basic
Statistics, and Factorial Designs
Formulation and Mixture Designs
Learn the principles of designing experiments
and analyzing the resulting data for processes
that are comprised of the mixing and blending
of ingredients such as those commonly found
in the chemical, food, and beverage industries.
By utilizing Minitab’s easy to understand
interface, create experiments designed to
study and uncover important process
information related to mixture processes with
the minimal amount of experimental
resources. Learn how to interpret graphical
and statistical output to understand a
mixture’s blending properties and to choose
the appropriate mixture of ingredients needed
to optimize one or more critical process
characteristics.
Topics covered in the training material
include: Simplex Lattice and Centroid Designs,
Upper and Lower Constraints, Extreme
Vertices Designs, Pseudocomponents,
Response Trace Plots, Mixtures with Process
Variables, Mixture Amounts
Prerequisites: Introduction to Minitab, Basic
Statistics, and Factorial Designs
DOE in Practice
Learn how to handle common DOE scenarios
where classic factorial or response surface
design and analysis techniques are neither
appropriate nor possible due to the nature of
the response variable or the data collection
process. Develop techniques for experimental
situations often encountered in practice such
as missing data and hard-to-change factors.
Understand how to account for variables
(covariates) that may affect the response but
cannot be controlled in the experiment.
Explore the opportunities to minimize costs or
variability while simultaneously optimizing an
important product or process characteristic.
Learn how to find and quantify the effect that
factors have on the probability of a critical
event, such as a defect, occurring.
Topics covered in the training material
include: ANCOVA, Unbalanced Designs, Split-
Plot Designs, Multiple Response Optimization,
Binary Logistic Regression
Prerequisites: Introduction to Minitab, Basic
Statistics, and Factorial Designs
Optional Topic for On-Site Training: Taguchi
Designs
Introduction to Reliability
Determine lifetime characteristics of a product
using both graphical and quantitative analysis
methods. Examine case studies containing
censored and uncensored data to learn how to
correctly handle a wide variety of data
structures commonly found in reliability.
Explore the common distributions used to
model failure rates and develop necessary
skills in choosing these models.






Topics covered in the training material
include: Parametric and Nonparametric
Distribution Analysis, Estimation and
Demonstration Test Plans, Growth Curves,
Multiple Failure Modes, Warranty Predictions,
and Weibayes Analysis.
Prerequisites: Introduction to Minitab and
Basic Statistics
Advanced Reliability
Study and describe the impact that
explanatory variables have on product
lifetime. Determine the effect of factors and
covariates on product failure and the risk of
failure to a population of products. Learn how
to obtain reliability estimates on highly
reliable products in a reasonable amount of
time and assess when those components are
expected to fail. Establish appropriate sample
sizes and allocation of units to stress levels
for an accelerated life test, and determine the
effect of a stress variable on the probability of
failure. A strong emphasis is placed on using
appropriate probability models to predict
important lifetime characteristics of your
products once in the field.
Topics covered in the training material
include: Probit Analysis, Regression with Life
Data, Accelerated Life Testing and Test Plans.
Prerequisites: Introduction to Minitab, Basic
Statistics, and Introduction to Reliability
Statistics for Pharmaceuticals and Medical
Devices
In this 4-day course you will learn to apply
Minitab tools to the different stages of the
FDA 2011 Process Validation Guideline.
Understand how to select the right tool for a
given stage and to correctly interpret the
results of the analysis. All examples and
exercises are from the pharmaceutical and
medical device industries.
Statistical topics include t-Tests for testing
targets, Gage R&R for measurement system
verification, Capability Analysis for Normal
and Attribute Data, Variables and Attribute
Control Charts, Acceptance Sampling for
incoming/outgoing inspections, Regression for
modeling observational data, ANOVA, DOE for
process improvement, Stability Analysis for
establishing expiration dates, and Reliability.
Also covers importing data, formatting data,
creating/editing graphs, and general tips.
Prerequisite: None. This course can be used as
a pre-requisite to Response Surface Designs
and DOE in Practice.
Macros
Automate your Minitab analysis and save time
with macros. Learn how to use Minitab’s
command syntax to write macros that
instantaneously import data from a database,
manipulate poorly structured Excel files, and
perform statistical analysis with minimal user
input. By the end of this hands-on course, you
will be able to write and execute your own
custom macros.
Prerequisites: Introduction to Minitab
Quality Companion
Quality Companion Essentials
In this 2-day course you will quickly learn how
to navigate Quality Companion’s user-friendly
and customizable environment. Learn how to
identify a potential project and quantify its
risks. Define and scope a project to more
easily gain buy-in from key stakeholders. Learn
to use Quality Companion’s built-in Roadmaps
and Coaches to determine which tools and
statistical analyses are appropriate at any
phase of the project. Define a process and
manage its activities to gain insight into the
value stream. Modify Quality Companion’s
built-in tools to reflect your preferred quality
improvement methodology. Create custom
data fields and categories as well as custom
project and tool templates that can be stored
as permanent software options and shared
with other users.
Topics covered in the training material
include: Quality Companion environment,
Project Manager, Roadmap, Coaches,
Templates, Custom Data Fields, Project Data
Sharing and Modifying Forms.
Tools covered in the training material include:
Process mapping, Brainstorming / Fishbone
diagram, Y metrics, Ballots, Presentations,
Analysis Capture tools, Value Stream mapping,
as well as various form tools such as Project
Charter, C&E Matrix, FMEA, and more.
Prerequisite: View Quality Companion
recorded webcasts prior to attending this
course.