MCEE 205 Statistics and Design of Experiments
ROCHESTER INSTITUTE OF TECHNOLOGY
Microelectronic Engineering
MCEE 205 Statistics and Design of Experiments
Students required to take this course: (by program and year, as appropriate)
Course is required for Microelectronic Engineering students in 2nd year.
Students who might elect to take the course:
Students interested in use of statistics and experimental design for research or
manufacturing operations.
Statistics and Design of Experiments
Statistics and Design of Experiments will study descriptive statistics, measurement
techniques, SPC, Process Capability Analysis, experimental design, analysis of variance,
regression and response surface methodology, and design robustness. The application of
the normal distribution and the central limit theorem will be applied to confidence
intervals and statistical inference as well as control charts used in SPC. Students will
utilize statistical software to implement experimental design concepts, analyze case
studies and design efficient experiments.
Prerequisite(s): None
Co-requisite(s): None
Class 3, Lab 3, Credit 3 (Semester)
Textbook:
T.B. Barker, Quality by Experimental Design, 3rd Edition, CRC Press, 2005
ISBN 0-8247-2309-0
Schaum's Outline of Statistics for Engineers By Larry Stephens Date April 7, 2011
Format Paperback, 304 pages Other Formats Electronic book text
ISBN 0071736468 / 9780071736466
Goals of the course:
1.To understand the nature of variability.
2.To understanding of the principles of statistical inference.
3.To apply statistical inference and control charts to applications.
4.To understand assumptions and limitations of DOE.
5.To conceive and conduct a designed experiment to characterize a process.
Topics:
1. Tools for Improving Manufacturing
MCEE 205 Statistics and Design of Experiments
2. Characteristics of a good response
3. Fundamental concepts of probability
4. Variability and how to describe it--Sampling and degrees of freedom
5. Measurement techniques and Random variation
6. The normal curve and the distributions of averages
7. Application of the Central limit theorem to Control Charts
8. Statistical Process Control and Process Capability
9. Means and standard deviations of sums and differences
10. Statistical inference about variances
11. Interval estimates for the mean
12. Test of Hypothesis of the mean
13. Testing means and variances
14. Full Factorial Design
15. ANOVA and Regression Analysis
16. Model Equations
17. Fractional Factorials and Confounding Effects
18. 3 Level Designs
19. Taguchi Methodology
Laboratory
1.
2.
3.
4.
5.
6.
7.
8.
9.
JMPin
Matlab creating Plots
Understanding variability
SPC and Process Capability
One-way ANOVA
ANOVA on Full Factorial Design
Regression and Zero Point information in Factorial Designs
ANOVA on Fractional Factorial Design
Response Surface Methodology DOE Project
Evaluation Methods:
Homework / Labs
Exams (2)
Report / Presentation on DOE project
Final Exam
35%
30%
20%
15%
Intended course learning outcomes and associated assessment methods of those
outcomes
Course Learning Outcome
Exams & Homework Labs Projects
Quizzes
Student will understand the basic concepts
X
X
X
of variability. [1]
Student will demonstrate ability to make
X
engineering decisions based on statistical
MCEE 205 Statistics and Design of Experiments
analysis. [4,8]
Student will conceive of and construct
control charts for a process. [4,5,7,8]
Student will demonstrate ability to make
engineering decisions about design,
implementation, and analysis of an
experiment. [4,9]
Student will conceive and conduct a
designed experiment to characterize a
process. [4,8]
Student will exhibit their ability to write and
present detailed information about the
Design of Experiment project to others.
[5,8]
X
X
X
X
X
X
X
X
X
X
Program outcomes and/or goals supported by this course
Program Outcomes
Note: These nine program outcomes are mapped to ABET criteria a-k at the end of this
section.
1.0 Understand the fundamental scientific principles governing solid state devices and their integration into modern
integrated circuits.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
[1] Students will demonstrate ability to make engineering decisions based on statistical analysis.
[1] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[1] Students will conceive and conduct a designed experiment to characterize a process.
2.0 Design and conduct a sequence of processing steps to fabricate a solid-state device to meet a set of geometric,
electrical, and/or processing parameters.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[3] Students will understand the basic concepts of variability.
[3] Students will demonstrate ability to make engineering decisions based on statistical analysis.
[3] Students will conceive of and construct control charts for a process.
[3] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[3] Students will conceive and conduct a designed experiment to characterize a process.
[2] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
3.0 Acquire and analyze experimental electrical data from a solid-state device to extract performance parameters for
comparison to modeling parameters used in the device design.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
MCEE 205 Statistics and Design of Experiments
[1] Students will demonstrate ability to make engineering decisions based on statistical analysis.
[1] Students will conceive of and construct control charts for a process.
[1] Students will conceive and conduct a designed experiment to characterize a process.
[1] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
4.0 Conceive and conduct a designed experiment to characterize and/or improve a process utilized in IC fabrication.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
[1] Students will demonstrate ability to make engineering decisions based on statistical analysis.
[2] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[3] Students will conceive and conduct a designed experiment to characterize a process.
5.0 Communicate the results of an in-depth engineering research experience using techniques appropriate for oral,
poster, and paper presentations at technical conferences.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[3] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
6.0 Enter the job market or graduate school with a minimum of 4 quarters of engineering co-op experience.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
[1] Students will demonstrate ability to make engineering decisions based on statistical analysis.
[1] Students will conceive of and construct control charts for a process.
[1] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[1] Students will conceive and conduct a designed experiment to characterize a process.
[1] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
7.0 Discuss the relevance of a process or device, either proposed or existing, to current manufacturing practices.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
[1] Students will demonstrate ability to make engineering decisions based on statistical analysis.
[1] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[1] Students will conceive and conduct a designed experiment to characterize a process.
[1] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
8.0 Understand, characterize, and modify current lithographic materials, processes, and systems to meet imaging
and/or device patterning requirements.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
[1] Students will demonstrate ability to make engineering decisions based on statistical analysis.
MCEE 205 Statistics and Design of Experiments
[1] Students will conceive of and construct control charts for a process.
[1] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[1] Students will conceive and conduct a designed experiment to characterize a process.
[1] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
9.0 Appreciate the multidisciplinary nature of the field and the inherent trade-off between breadth and depth of
knowledge.
Course Learning Objectives:
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
[1] Students will understand the basic concepts of variability.
[1] Students will demonstrate ability to make engineering decisions about design, implementation, and
analysis of an experiment.
[1] Students will exhibit their ability to write and present detailed information about the Design of
Experiment project to others.
Course and Program Outcomes overall correlation strength summary
3-high correlation, 2-medium, 31-low
Course number and name
MCEE-205
Statistics & Design of Experiments
MicroE Program Outcomes
1 2 3 4 5 6 7
2
1 3 2
2
8
3
9
1
Listing of ABET criteria a-k
a. “Engineering Foundations”. An ability to apply knowledge of mathematics,
science, and engineering
b. “Experimentation”. An ability to design and conduct experiments, as well as to
analyze and interpret data
c. “Design”. An ability to design a system, component, or process to meet desired
needs within realistic constraints such as economic, environmental, social, political,
ethical, health and safety, manufacturability, and sustainability
d. “Multidisciplinary Teamwork”. An ability to function on multidisciplinary teams
e. “Problem Solving”. An ability to identify, formulate, and solve engineering
problems
f. “Professional Responsibility”. An understanding of professional and ethical
responsibility
g. “Communication”. An ability to communicate effectively
h. “Broad Education”. The broad education necessary to understand the impact of
engineering solutions in a global, economic, environmental, and societal context
i. “Life-Long Learning”. A recognition of the need for, and an ability to engage in
life-long learning
j. “Contemporary Issues”. A knowledge of contemporary issues
k. “Modern Tools”. An ability to use the techniques, skills, and modern engineering
tools necessary for engineering practice
Microelectronic Program Outcomes & ABET Criterion
(3 is strongly supported, 2 is moderate, 1 is weakly supported, blank is not applicable)
MCEE 205 Statistics and Design of Experiments
Microelectronic Engineering Program
Outcomes
ABET Criteria
a
Understand the fundamental scientific principles
governing solid state devices and their integration
into modern integrated circuits.
Design and conduct a sequence of processing
steps to fabricate a solid state device to meet a set
of geometric, electrical, and/or processing
parameters.
Acquire and analyze experimental electrical data
from a solid-state device to extract performance
parameters for comparison to modeling
parameters used in the device design.
Conceive and conduct a designed experiment to
characterize and/or improve a process utilized in
IC fabrication.
Communicate the results of an in-depth
engineering research experience using techniques
appropriate for oral, poster, and paper
presentations at technical conferences.
Enter the job market or graduate school with the
required engineering co-op experience.
Understand the relevance of a process or device,
either proposed, past or existing, to current and
future manufacturing practices.
Understand, characterize, and modify current
lithographic materials, processes, and systems to
meet imaging and/or device patterning
requirements.
Appreciate the multidisciplinary nature of the
field and the inherent trade-off between breadth
and depth of knowledge.
b
c
d
e
f
g
h
i
3
k
2
2
3
3
2
3
3
2
2
2
2
3
2
3
3
2
3
3
j
3
3
2
3
2
3
1
3
3
2
3
3
1
3
3
1
2
3
2
MCEE 205 Statistics and Design of Experiments
General Education Learning Outcome Supported by the
Course
Assessment
Method
Communication
X
X
X
X
Express themselves effectively in common college-level
written forms using standard American English
Revise and improve written and visual content
Express themselves effectively in presentations, either in
spoken standard American English or sign language (American
Sign Language or English-based Signing)
Comprehend information accessed through reading and
discussion
Lab Reports
Lab Reports
Lab Reports and
presentations
Exams, HW, Lab
Intellectual Inquiry
X
X
X
Review, assess, and draw conclusions about hypotheses and
theories
Analyze arguments, in relation to their premises, assumptions,
contexts, and conclusions
Construct logical and reasonable arguments that include
anticipation of counterarguments
Use relevant evidence gathered through accepted scholarly
methods and properly acknowledge sources of information
Statistical
Conclusions, HW,
Lab
DOE Lab
Exams, HW, Lab
Ethical, Social and Global Awareness
Analyze similarities and differences in human experiences and
consequent perspectives
Examine connections among the world’s populations
Identify contemporary ethical questions and relevant
stakeholder positions
Scientific, Mathematical and Technological Literacy
X
X
X
X
X
Explain basic principles and concepts of one of the natural
sciences
Apply methods of scientific inquiry and problem solving to
contemporary issues
Comprehend and evaluate mathematical and statistical
information
Perform college-level mathematical operations on quantitative
data
Describe the potential and the limitations of technology
Use appropriate technology to achieve desired outcomes
Exams, HW, Labs
Exams, Hw, Labs
Exams, Hw, Labs
Exams, Hw, Labs
Labs
Creativity, Innovation and Artistic Literacy
Demonstrate creative/innovative approaches to course-based
assignments or projects
Interpret and evaluate artistic expression considering the
cultural context in which it was created
Other relevant information (such as special classroom, studio, or lab needs,
special scheduling, media requirements, etc.)
Laboratory requirements:
MCEE 205 Statistics and Design of Experiments
This course reinforces general statistical knowledge through the collection of actual lab
data. The specific data collected can change since the concepts are general. Similarly the
course allows students to use a laboratory to execute a variety of different designed
experiments as generally taught in lecture. The nature of the experiment is not the focus
but rather the general application of DOE concept. The lab makes use of the very unique
Semiconductor & Microsystems Fabrication Laboratory within the KGCOE, i.e. “the
cleanroom”.
Course Policy on Academic Honesty
KGCOE HONOR PRINCIPLES: RIT Engineering faculty, staff and students are truthful and honorable,
and do not tolerate lying, cheating, stealing, or plagiarism.
All members of our community are expected to abide by these principles and to embrace the spirit they
represent. We each have a responsibility to address any unethical behavior we observe; either
through direct discussion with the offending party, or by discussion with an appropriate faculty or staff
member. Allowing unethical behavior to continue unchallenged is not acceptable.
Rochester Institute of Technology does not condone any form of academic dishonesty. Academic
Dishonesty falls into three basic areas: cheating, duplicate submission and plagiarism (refer to
http://www.rit.edu/kgcoe/advising/handbook.pdf pages 19-20 for more information).
Throughout this course the following specific conditions exist in regards to academic honesty:
Course Element
Specific Conditions
Homework: Graded and
Student collaboration is encouraged. However, the final product
Ungraded
that is turned in must be your own work. All homework sets must
be completely documented in regards to references used (books
other than the course textbook, web sites, etc.) and assistance
obtained from individuals other than the course instructor. Proper
documentation would include source, date, and extent of
information gained through that source.
Exams
Individual exercise; collaboration of any kind is disallowed
Laboratory Assignments
All team members expected to participate fully; one submission
required from each student
Any act of Academic Dishonesty will incur the following consequences. After notifying and presenting
the student with evidence of such misconduct, the instructor has the full prerogative to assign a lower
grade, including an “F” for the offense itself or for the entire course. If after careful review of the
evidence, the instructor decides that the student’s actions are indeed misconduct and warrant a
penalty, the instructor will add a letter to the student’s file in his or her home department (copy to the
student, Department Head and the Dean) documenting the offense. Depending on the seriousness of
the offense, the student may also be brought before the Academic Conduct Committee of the College
in which the offense occurred, and may face academic suspension or dismissal from the Institute. The
student has the right to appeal any disciplinary action as described in section D17.0 “Academic
Conduct and Appeals Procedures” and D18.0 “RIT Student Conduct Process” of the Institute Policies
and Procedures Manual.
Prepared by: Dale Ewbank
Date: 08/05/2013
MCEE 205 Statistics and Design of Experiments
Microelectronic Engineering Program – ABET course outcomes student survey
MCEE 205 Statistics and Design of Experiments
Outcomes: Please rate (1-5) your understanding of, and ability to apply, the knowledge
and skills listed in the outcomes for this course.
Learning Objective
Rating
Weak
Proficient
1 – Student will understand the basic concepts of
1
2
3
4
5
variability.
2 – Student will demonstrate ability to make
1
2
3
4
5
engineering decisions based on statistical analysis.
3 – Student will conceive of and construct control
1
2
3
4
5
charts for a process.
4 – Student will demonstrate ability to make
1
2
3
4
5
engineering decisions about design,
implementation, and analysis of an experiment.
5 – Student will conceive and conduct a designed
1
2
3
4
5
experiment to characterize a process.
6 – Student will exhibit their ability to write and
1
2
3
4
5
present detailed information about the Design of
Experiment project to others.
Course Evaluation: Please rate the various components of this course in helping you
develop and apply the knowledge and skills listed in the course outcomes.
1 - Student will understand the
basic concepts of variability.
Lectures
Not helpful
1
2
3
Very helpful
4
5
2 - Student will demonstrate ability
to make engineering decisions
based on statistical analysis.
Not helpful
Very helpful
1
2
3
4
5
Homework
1
2
3
4
5
1
2
3
4
5
Exams
1
2
3
4
5
1
2
3
4
5
Project/labs
1
2
3
4
5
1
2
3
4
5
MCEE 205 Statistics and Design of Experiments
3 - Student will conceive of and
construct control charts for a
process.
Lectures
Not helpful
1
2
3
Very helpful
4
5
4 - Student will demonstrate ability
to make engineering decisions
about design, implementation, and
analysis of an experiment.
Not helpful
Very helpful
1
2
3
4
5
Homework
1
2
3
4
5
1
2
3
4
5
Exams
1
2
3
4
5
1
2
3
4
5
Project/labs
1
2
3
4
5
1
2
3
4
5
5 - Student will conceive and
conduct a designed experiment to
characterize a process.
Lectures
Not helpful
1
2
3
Very helpful
4
5
6 - Student will exhibit their ability
to write and present detailed
information about the Design of
Experiment project to others.
Not helpful
Very helpful
1
2
3
4
5
Homework
1
2
3
4
5
1
2
3
4
5
Exams
1
2
3
4
5
1
2
3
4
5
Project/labs
1
2
3
4
5
1
2
3
4
5
ADDITIONAL COMMENTS: Please provide additional comments on this course
below or overleaf. Detailed comments are particularly important if you feel that some
goals were not met.