Online Six Sigma Black Belt Certification

Fee: $3250
SME Members: $2925

Program Dates

This is a cohort program and new classes will be offered.

  • Dec. 17, 2009 - June 18, 2010
Program Sections:

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Overview

Arizona State University, through the Department of Industrial Engineering and the Interdisciplinary Committee on Statistics, has developed a new educational initiative in six sigma methodology. This program allows professionals to pursue an educational focus in six sigma techniques and implementation as part of a noncredit professional certification. The program is delivered conveniently over the Internet through video streamed lectures available 24 hours a day 7 days a week. This convenient format provides the flexible format necessary for busy professionals.

The Industrial Engineering program at ASU is among the top 20 programs in the nation, as ranked by U.S. News & World Report. We have the finest faculty of industrial statistics in the world. ASU faculty and industry leaders, who have successfully deployed six sigma transformations for many years, teach the Black Belt program bringing both methods, leadership and deployment strategies into the curriculum.

Students will not receive academic credit for the noncredit option. However, if a student has interest in pursuing the Graduate Certificate in Statistics-Six Sigma Black Belt "academic option", please visit; http://www.asu.edu/graduate/statistics/Certificate.html

Noncredit Professional Certification Requirements

There are specific requirements for this program. It is incumbent on you, the student, to have the background necessary to successfully complete the program. Please review the following fully and carefully so you can plan appropriately for the timing of the class, the content and workload. If you still have questions on your qualifications, please contact us prior to registration.

  • One previous course in engineering statistics within the last five years or a concurrent working knowledge of statistical methods
  • Proficient in computing and interpreting the sample mean and standard deviation; previous exposure to the normal distribution; familiarity with concepts of testing hypotheses (the t-test, for example)
  • Constructing and interpreting a confidence interval, model-fitting using the method of least squares, and some familiarity with matrix algebra is required
  • Students must complete the courses, exercises, and exams within 6 months of the program start date
  • An overall score of 70% or higher must be attained on the exams to receive certification
  • A Black Belt project from the workplace is required and must be completed within 8 months of the cohort start date to receive certification
  • Certification is administered by ASU Fulton School of Engineering, an ABET Accredited Engineering School
  • The program is organized in a cohort (group) format with a defined start and completion date for the training portion of the program
  • A course moderator is provided to support and facilitate the program with coaching and advising for each student

Faculty

Dr. Douglas C. Montgomery

Doug Montgomery, Ph.D., is a Regent's Professor of Industrial Engineering and Statistics, and ASU Foundation Professor of Engineering at Arizona State University. Additional accolades include;

  • John M. Fluke Distinguished Professor of Engineering, Director of Industrial Engineering and Professor of Mechanical Engineering at the University of Washington in Seattle
  • Professor of Industrial and Systems Engineering at Georgia Tech
  • BSIE, MS and Ph.D. degrees from Virginia Tech
  • Recipient of the Shewhart Medal, William G. Hunter Award, Brumbaugh Award, and the Shewell Award (twice) from the American Society for Quality Control
  • Interests focus on industrial statistics, including design of experiments, quality and reliability engineering, applications of linear models, and time series analysis and forecasting
  • Industrial experience includes engineering assignments with Union Carbide Corporation and Eli Lilly and Company, and extensive consulting experience
  • Visiting Professor of Engineering at the Monterey Institute of Technology in Monterey, Mexico, and a University Distinguished Visitor at the University of Manitoba
  • The Office of Naval Research, the National Science Foundation, the United States Army, and private industry have sponsored Dr. Montgomery's research

Dr. George Runger

George C. Runger, Ph.D., is a Professor in the department of Industrial Engineering at Arizona State University. He has co-authored research papers on real-time monitoring and control, data mining, and other data-analysis methods with a focus on large, multivariate data streams. He teaches these and related subjects in graduate courses at ASU. His work is funded by grants from the National Science Foundation.

Dr. Runger was previously a faculty member at the University of Maryland and at Renssaeler Polytechnic Institute. He has industrial experience with IBM as a senior engineer.

Dr. Runger's areas of expertise are statistical process control, multivariate statistics, experimental design and data mining. He holds the BSIE from Cornell University and the Ph.D. in Statistics from the University of Minnesota.

Dr. George Runger is a two time recipient of the Martin A. Brumbaugh Award, annually given out by the American Society for Quality for the most important journal paper in the field.

Course Topics

  • IEE 572 Design of Experiments
    • This is a basic course in designing experiments and analyzing the resulting data intended for engineers, physical/chemical scientists and scientists from other fields such as biotechnology and biology
    • Topics include strategy of experimentation, factorials, blocking and confounding, fractional factorials, response surfaces, nested and split-plot designs
    • Prerequisites are - a basic working knowledge of statistical methods; proficient in computing and interpreting the sample mean and standard deviation; previous exposure to the normal distribution; familiarity with concepts of testing hypotheses (the t-test, for example), constructing and interpreting a confidence interval, and model-fitting using the method of least squares; Most of these ideas will be reviewed as needed
    • The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions
  • IEE 570 Advanced Quality Control
    • This course covers topics in quality control that have been widely used in many industries (including service industries), specifically, process monitoring with control charts (Shewhart, cusum, EWMA), feedback adjustment and engineering process control, process capability, autocorrelation, including selected topics from current literature
    • Prerequisites are - one previous course in engineering statistics; introductory knowledge of hypothesis testing, confidence intervals, probability; and some familiarity with matrix algebra is required
    • Minitab is required, however other statistical packages may be used for your homework but you will be expected to interpret Minitab output for exams
  • IEE 578 Regression Analysis
    • This is a basic course in regression analysis and model-building for engineers and physical/chemical scientists
    • Focus is on building empirical models for relating an observed response to one or more predictor or regressor variables
    • Prerequisites are - one previous course in engineering statistics; introductory knowledge of hypothesis testing, confidence intervals; and familiarity with matrix algebra is required
    • Minitab is required, however other statistical packages may be used for your homework but you will be expected to interpret Minitab output for exams
  • IEE 598 Six Sigma Methodology
    • The six sigma process improvement strategy of define, measure, analyze, improve, and control (DMAIC) is the central focus of this course
    • Students are shown how statistical methods and other six sigma problem solving tools are integrated and deployed via the DMAIC framework
    • Other topics include project selections and management, team facilitation/leadership, and an introduction to design for six sigma and lean principles
    • The course objective is to prepare participants to use the six sigma approach to process improvement in business and industry, and for participants to learn how a variety of six sigma tools and methods are integrated through DMAIC to successfully complete six sigma projects
  • Six Sigma Applied Project

    • Students are required to complete the self-study program and exam within six months of the start date, and will have an additional 60 days to complete and submit the black belt project

Required Textbooks & Software: (not included in program fee)

  • IEE 572 Design of Experiments
    • Design and Analysis of Experiments, 6th Edition, by Douglas C. Montgomery, 2005, John Wiley & Sons (ISBN: 047148735X)
    • Design and Analysis of Experiments, Student Solutions Manual, 6th Edition, by Douglas C. Montgomery, 2005, John Wiley & Sons (ISBN: 0471733040)
    • Design-Expert Software, Educational Version 6.0, September 2000, Stat-Ease, Inc. (ISBN: 0471394114)
  • IEE 570 Advanced Quality Control
    • Introduction to Statistical Quality Control, 5th Edition, by Douglas C. Montgomery, 2005, John Wiley & Sons, Inc. (ISBN: 0471656313)
    • Introduction to Statistical Quality Control, Student Resource Manual, 5th Edition, by Douglas C. Montgomery, 2005, John Wiley & Sons, Inc. (ISBN: 0471678104)
  • IEE 578 Regression Analysis
    • Introduction to Linear Regression Analysis, 3rd Edition, by D.C. Montgomery, E.A. Peck, and G.G. Vining, 2001, John Wiley & Sons (ISBN: 0471315656)
  • IEE 598 Six Sigma Methodology
    • Lean Six Sigma: Combining Six Sigma Quality with Lean Speed by Michael L. George, 2002, McGraw-Hill (ISBN: 0071385215)
    • Leading Six Sigma: A Step-by-Step Guide Based on Experience with GE and Other Six Sigma Companies by R.D. Snee and R.W. Hoerl, 2003, Financial times Prentice Hall
      • (ISBN: 0130084573)
  • Optional Textbook for Applied Regression Analysis and Advanced Quality Control:
    • Applied Statistics and Probability for Engineers, 3rd edition, by Douglas C. Montgomery and George C. Runger, 2006, John Wiley & Sons (ISBN: 0471735566)


Textbooks are available at most bookstores or online. Below are links to some online vendors:
www.amazon.com
www.campusbooks.com
www.ecampus.com
www.bigwords.com
www.walmart.com

Required Software

Minitab Version 15 (student version is acceptable). This software is required to complete this course. You may purchase Minitab from any vendor or online (not included in the cost of the program).

Program Deliverables

The following defines due dates and expectations for project and exam deliverables:

  • 30 Days after cohort start date; A short project summary must be submitted
  • 60 Days after cohort start date; Project Update - This is a progress report
  • 90 Days after cohort start date; Second Project Update - more detailed
  • All topic exams must be completed by the course end date
  • Final Project due 60 days after end date of cohort

Technical Requirements

In order to view the online course, the following is the basic recommended setup to successfully view our educational material;

  • Pentium or equivalent processor
  • 128 MB RAM
  • CD-ROM drive (preferred)
  • Sound card and speakers
  • Color monitor (17" or better preferred) set to display at 800x600
  • High-speed Internet access
  • Windows 98 SE, NT 4.x or newer operating system
  • Internet Explorer 5.5 or later
  • Windows Media Player 9 or newer
  • Acrobat Reader and Flash browser plugins

Registration

Program Fee

$3250 (includes training, exam, and project coaching) Students are required to purchase the textbooks and software. Group discounts and program customization is available.

Refunds and Cancellations

As a working student we know that life gets hectic and unforeseen circumstances occur. Here are some things to keep in mind:

  • While this program is self-paced there is a deadline to complete the program. You have six (6) months from the start of this program to complete the course and the exams. You will have an additional two (2) months after the program ends to complete the project.
  • There are no refunds or cancellations once the program begins. Students may only cancel this course prior to the program start date.
  • Cohort transfers: you will have a period of 30 days from the start date if you find you need to take the option to transfer to another cohort. There is a fee of $200 to do so.
  • After 30 days from the start date there is no option to transfer to another cohort program.
  • To cancel or transfer this course, please send request via email to jose.quiroga@asu.edu or fax (480) 965-8653, Attention: Jose Quiroga

For more information contact:

Octavio Heredia
Associate Director, Extended Education
asu.cpd@asu.edu