Design of Experiments (DOE) for Engineers     

Webinar On-site
Delivery
Certificate
Program

I.D.# WB0932Printable Description
Duration: 12 Hours
Show Session Dates
January 26-February 6, 2015 (6 Sessions ) - Live Online
 
Show Session Dates
August 17-28, 2015 (6 Sessions ) - Live Online
 

Design of Experiments (DOE) is a methodology that can be effective for general problem-solving, as well as for improving or optimizing product design and manufacturing processes. Specific applications of DOE include, but are not limited to, identifying root causes to quality or production problems, identifying optimized design and process settings, achieving robust designs, and generating predictive math models that describe physical system behavior. This competency-based web seminar utilizes a blend of reading, discussion and hands-on to help you learn the requirements and pre-work necessary prior to DOE execution, how to select the appropriate designed experiment to run, DOE execution, and analysis of DOE results. You will experience setting up, running, and analyzing simple-to-intermediate complexity Full Factorial and Partial Factorial experiments both by hand and using computer software. You will also set-up and analyze Robust/Taguchi and Response Surface experiments utilizing computer software.

Each participant will receive a 30 day MinitabTM product trial copy for use in the web seminar. Due to the nature of the online format, each participant will be expected to dedicate approximately one hour to complete "homework" and/or short reading assignments in preparation for each session.

Note: A similar course is available as a classroom seminar.

Learning Objectives
By participating in this web seminar, you will be able to:

  • Determine when DOE is the correct tool to solve a given problem or issue
  • Select the appropriate DOE experiment type (DOE Goal) for a given application
  • Set up simple Full Factorial DOEs by hand, using cube plots
  • Set up and analyze any Full Factorial DOE using Minitab
  • Identify appropriate partial factorial design(s) based on one's application
  • Set-up and analyze Partial Factorial DOEs, simple Robust Design (Taguchi) DOEs, and simple Response Surface DOEs using Minitab
  • Recognize the structured process steps recommended when executing a DOE project

Who Should Attend
This web seminar will benefit engineers involved in product design and/or optimization; process design and/or optimization; quality improvement efforts such as defect elimination, warranty avoidance or similar initiatives; and technicians, analysts and managers who support engineers in these efforts. This course has no specific course prerequisites. However, participants are expected to have some math background, that includes elementary statistics. Since the course includes demonstration and hands-on use of Minitab, participants should have some familiarity with Windows-based personal computer applications.

Topical Outline
Session 1

  • Introduction
  • What is DOE (with Initial Data Collection Exercise)
  • Full Factorial Experiments using Cube Plots
    • Identifying main effect and interaction terms
    • Determining effects for all terms
  • Estimating How Much Experiment Data is Enough
  • Assignment for Session 2: Review of Web-Based Demo of Minitab - Full Factorial DOE Set-up and Analysis; and Reading, Overview of DOE Statistics

Session 2
  • Set up and Analysis of a Full Factorial Experiment using Minitab
  • Minitab's DOE Results (High Level Overview of Minitab Outputs)
  • Review of Methods for Determining 'Significance'
  • ANOVA and Regression Overview
  • Assignment for Session 3: Hands-on Exercise in the use of Minitab using Simulator to Generate Data, and Reading on the Structured DOE Process

Session 3
  • Review of Exercise Assigned at the End of the Session 2
  • Review and Additional Information on DOE Statistics and Interpretation of DOE Output
  • Best Practice: The Problem Solving Process
  • Best Practice: The Structured DOE Process
  • Assignment for Session 4: Reading on Overview of Confounding and Partial Experiments

Session 4
  • The Confounding Principle and Partial Factorial Experiments
  • How Confounded Occurs in a DOE, including Identity Usage and Resolution
  • Setting up Partial Factorial Experiments using Minitab
  • Assignment for Session 5: Partial Factorial Exercise using Minitab and a Simulator to Generate Data for the DOE; Reading on Robust/Taguchi DOE

Session 5
  • Review of Exercise Assigned at the End of the Session 4
  • When Robust/Taguchi DOE is Appropriate
  • How Robust/Taguchi DOE is Different
    • Two-Step Optimization Concept
    • Control vs. Noise
    • Importance of Control-by-Noise Interactions
    • Signal-to-Noise (S/N) and Loss Statistics
  • Some Taguchi DOE Success Stories (incl. Set-up and Analysis in Minitab)
  • Demonstration of Minitab for Setting Up a Taguchi DOE
  • Assignment for Session 6: Robust/DOE Exercise using Minitab and a Simulator to Generate Data for the DOE, Reading on Overview of Response Surface Methodology

Session 6
  • Review of Exercise Assigned at the End of the Session 5
  • When Response Surface DOE is Appropriate
  • How Response Surface DOE is Different
    • Box-Behnken Concepts (with Demonstration of Minitab Set-up)
    • Central-Composite Concepts (with Demonstration of Minitab Set-up)
  • Class Exercise: Response Surface Set-up and Analysis
  • High-level Overview of Other Designs/Application: Plackett-Burman and Mixture
  • FAQ Review
  • Summary

Instructor(s): Kevin Zielinski
Kevin ZielinskiKevin Zielinski currently owns and operates Red Cedar Media LLC, a training and corporate communications consulting, design, development and delivery company based in Michigan. Previously, Kevin was Senior Applications Specialist for EDS (including General Motors/EDS and Hewlett Packard/EDS) specializing in technical training delivery, training consulting, courseware design and development, and e-Learning. He has designed, developed and delivered over 40 lecture- and web-based courses attended by General Motors and EDS employees worldwide. Mr. Zielinski has also served as Adjunct Professor for the Wayne State University College of Engineering and WSU/Focus:Hope for many years. His areas of expertise include: e-Learning design and development, Quality Tools and Methods (Design of Six Sigma, Robust Engineering, Design of Experiments (DOE), Statistical Tolerancing and GD&T); Design for Manufacturing and Assembly (DFMA); Engineering Economics; and Plant Floor Throughput Improvement. Mr. Zielinski has been an instructor for SAE Professional Development since 1990, and is a recipient of SAE's Forest R. McFarland Award (April 2005). He holds a bachelor's and master's degree in engineering from Wayne State University.

Registration Information
Registration for this live web seminar is available on a per-person basis, similar to purchasing a seat in a classroom. Participants attend an online session from work or home; anywhere with a PC with internet access (at least 56K) and a telephone. The fee includes one connection to the conference calls (toll free telephone number provided for U.S. and select countries*) and assigned personal ID number; one connection to SAE's online training center (via WebEx); and access to a secure course in the SAE Learning Center that contains the presentations, class session recordings, supplemental materials, and assignments.

Registrations will be accepted until 5:00 p.m. the day before the start of the web seminar, but early registration is encouraged to allow for pre-course set-up and instructions.

*Global toll-free telephone numbers are provided for many countries outside the U.S., but are limited to those on the WebEx call-in toll-free number list. Check here to see if your country has a global call-in toll free telephone number for this web seminar. If your country is not listed, you may still connect using the US/Canada Call-in toll number or Voice over Internet Protocol (VoIP).

Although WebEx Training Manager will automatically launch when you join the web seminar, you or your system administrator are encouraged to download the plug-in in advance to help ensure successful setup. Click here, then follow the onscreen instructions.

NOTE: The course presentation will be recorded and made available for 30 days to those who register by the deadline.

Multiple Seat Discount - Does your company have a group of employees who need this course? Register one individual at the appropriate member or list price, then register additional employees at half off the list price. Registration by phone with SAE Customer Service is required to take advantage of this discount. Register all individuals at the same time or mention the confirmation number for the first registrant. The offer is good for only the same web seminar offering. All registrants will receive a personal account and opportunity for CEUs.

Cancellations
Can't attend on the date/time above? The presentation will be recorded and made available for 30 days to those who are registered, regardless of availability for the live session. If you still need to cancel, transfer to a future offering, or designate a substitute, a full refund is issued if you notify SAE at least 14 days prior to the web seminar start date. If less than 14 days prior, please contact SAE Customer Service to discuss options*. NOTE: SAE reserves the right to cancel web seminar and cannot be held responsible for related costs incurred by registrants other than the registration fee.

*Cancellation penalties may apply.

Fees: $810.00 ; SAE Members: $648.00 - $729.00

1.2 CEUs
You must complete all course contact hours and successfully pass the learning assessment to obtain CEUs.

Testimonial
"The best hands-on DOE seminar. I will be using these tools in my job starting next week."
Alexis Perez
Lighting Application Engineer
Federal Mogul Corporation

"Content was professionally delivered and our objectives were easily met!"
Andrew Rogers
Process Engineer
FineLine Prototyping

To register, click Register button at the top of this page and submit the online form, or contact SAE Customer Service at 1-877-606-7323 (724/776-4970 outside the U.S. and Canada) or at CustomerService@sae.org.