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.