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This five day course (being run over 4 long days for March 2018), extends on the advanced modern techniques for test design and analysis taught to systems engineers and project managers initially in foundational design of experiments (DOE) or design for six sigma (DFSS) either through the University of NSW’s masters subject (ZEIT 8034) or Air Academy Associates’ (AAA) Operational DOE course. Students who have been applying the basic test design and test analysis techniques to screen, model or validate system performance with packages like DOE PRO XL, SPC XL and rdExpert, will be introduced to more advanced functionality offered by Quantum XL and DFSS techniques to improve their test designing and analysis in the following areas:
- Methods to build quality in from conceptual design through to service (house of quality)
- How to optimise designs more fully, including operational models.
- How to extract and use probabilistic transfer functions more fully
- Expected value analysis (EVA) using Monte Carlo routines to estimate more precise confidence intervals of outputs
- Using EVA to set more robust design inputs and allocate cost-effective tolerances for design or operations
- Logistics regression techniques to better evaluate and predict from testing when outputs are binary like pass/fail, defeat/no defeat, decoy/no decoy, penetrate/no penetrate as used in electronic warfare, operational analysis and cybersecurity testing
- Historical (big) data analysis techniques.
- Case studies and practical workshops on the above.
Students who complete this course will be eligible in the following year to submit to a short examination and review of three case studies of their work by AAA in order to be Green Belt Industry accredited in DFSS techniques. This accreditation is well regarded in international industry.
What you will receive
What you will receive
Who should attend
Who should attend
Reviews
“Excellent instructor for very tough subject, good interaction with class, great training materials, books, visuals, etc.”
“Overall, one of the very best training courses I have ever had. Top notch instructor, presentation, and knowledge skills.”
“I really enjoyed the team interactions and the excellent instructor. I have been to a number of courses and this has been my favorite in 10 years!”
“First course I have ever taken where exercises truly added to the understanding. The most clear and meaningful presentation on process improvement I have seen to date.”
Presenter
DR MARK KIEMELE
Mark J. Kiemele, President and Co-founder of Air Academy Associates, has more than 30 years of teaching, consulting, and coaching experience. Having trained, consulted, or mentored more than 30,000 leaders, scientists, engineers, managers, trainers, practitioners, and college students from more than 20 countries, he is world-renowned for his Knowledge Based KISS (Keep It Simple Statistically) approach to engaging practitioners in applying performance improvement methods. His support has been requested by an impressive list of global clients, including Xerox, Sony, Microsoft, GE, GlaxoSmithKline, Raytheon, Lockheed-Martin, Northrop-Grumman, Woodward, Samsung, PerkinElmer, Danaher, Corning, EMC, Kaiser Aluminum, Apogee, Schlumberger, Bose, Heritage Valley Health System, John Deere, Valeant, Sandia Laboratories, General Dynamics Land Systems, Aptuit, Pittsburgh Glass Works, Energizer, and Army Materiel Command.
Mark earned a B.S. and M.S. in Mathematics from North Dakota State University and a Ph.D. in Computer Science from Texas A&M University. Dr. Kiemele has been involved in the origin and evolution of Six Sigma, as he trained the first Six Sigma Black Belts at the Six Sigma Research Institute at Motorola and has helped deploy and implement Six Sigma at more than 80 companies worldwide. During his time in the U.S. Air Force, Mark supported the design, development and testing of various weapon systems, including the Maverick and Cruise Missile systems, and was a professor at the U.S. Air Force Academy. He currently serves on the National Defense Industrial Association’s Test and Evaluation Executive Committee.
In addition to many published papers and articles, he has co-authored the books Basic Statistics: Tools for Continuous Improvement ; Knowledge Based Management ; Applied Modeling and Simulation: an Integrated Approach to Development and Operation ; Network Modeling, Simulation, and Analysis ; Lean Six Sigma: A Tools Guide; and Design for Six Sigma: The Tool Guide for Practitioners. He is also the editor of the text Understanding Industrial Designed Experiments.
Course Information
Introduction to Design for Six Sigma (DFSS)
- The Identify, Design, Optimize, Validate (IDOV) Methodology
- DFSS Goals and Benefits
- Key Ingredients for success
- Quantifying Savings and Benefits
The DFSS Scorecard
- Keeping Score using the DFSS Scorecard
- Scorecard Elements and Construction
- Parts
- Process
- Performance
- Software
- Methods for Computing DPU
- Hands-on practice completing a DFSS Scorecard using DFSS Software
Identify: The DFSS Project and Team
- DFSS projects and studies
- Key elements of the business case
- Initiating and Scoping the project
- Project charters
- The DFSS team
- Stakeholder analysis
Identify: The Voice of the Customer (VOC)
- The Identify phase of IDOV
- Kano’s Model
- Determining Customer Wants and Needs
- Sampling Methods
- Identifying Critical to Customer Requirements
- Prioritizing Customer Requirements
- Introduction to Quality Function Deployment (QFD) and the House of Quality
- Hands-on Practice Completing House of Quality #1 to identify Measurable CTCs (critical to customer measures)
Design: Concept Generation and Selection, Product Design, and Requirements Flowdown
- The Design phase of IDOV
- Assigning Specs and Formulating Design Concepts
- FAST diagrams
- Overview of Triz and Axiomatic Design
- Comparing Alternate Design Concepts using Pugh Concept Selection
- Risk Analysis and Management
- Building House of Quality #2
Design: Transfer Functions
- Importance of Transfer Functions for IDOV
- Methods for Obtaining Transfer Functions
- Design of Experiments (DOE)
- Simulation
- Historical Data Analysis
- Using Multiple Transfer Functions to optimize performance
- Multiple Response Optimization experiment using the Statapult ®
- Logistic Regression Analysis
- Historical (Big) Data Analysis and Predictive Analytics
Optimize: Expected Value Analysis
- Meaning of expected value
- Expected Value Analysis (EVA) for Quantifying the Distribution of the Output
- Comparing Methods and Strategies for EVA
- Root Sum Square (RSS)
- Monte Carlo Simulation
- Using DFSS software for EVA Analysis
- Determining distribution of inputs
- Working with Normal and Non-Normal Input and Output Distributions
Optimize: Robust Design
- Understanding how input means affect output performance
- Noise factors and P-diagrams
- Robust Design: Finding Optimal Mean Settings for the Inputs to Minimize Variation in an Output
- Methods for Robust Design
- Hands-on Robust Design experiment using the Statapult ®
- Computer Based Robust Design (Parameter Design) using DFSS software
- Robust design examples and exercises
Optimize: Tolerance Allocation
- Quantifying the Sensitivity of the Output DPM to Changes in the Input Variable’s Standard Deviation
- Tolerance Allocation Examples and Exercises
- Setting Tolerances
- Methods to Reduce the Standard Deviation of Inputs
Design for X-ability and Scorecard Updates
- DFX Concepts – beyond just designing for performance
- DFX principles and examples
- Introduction to Design for Reliability (DFR)
- Designing with Reliability in Mind
- Common life data distributions and analysis
- Mistake Proofing and Error Proofing
- Capability prediction
- Design scorecard updating and analysis
Validate: The Achievement of Breakthrough Performance
- Sensitivity Analysis
- Quantifying the impact of mean and standard deviation shifts in design inputs
- Developing prototypes, test cases and pilots
- Introduction to high throughput testing for validating performance
- Performing gap analysis if results don’t confirm
DFSS Case Studies and Examples
Design Exercise: Applying the IDOV Methodology
- Hands-on practice with the IDOV process
- Teams Design a Product to Meet the Customer Needs, using the IDOV process; Teams optimize their design using the IDOV tools and ultimately build and test their designs to validate performance
Courses will be held subject to sufficient registrations. UNSW Canberra reserves the right to cancel a course up to five working days prior to commencement of the course. If a course is cancelled, you will have the opportunity to transfer your registration or be issued a full refund. If registrant cancels within 10 days of course commencement, a 50% registration fee will apply. UNSW Canberra is a registered ACT provider under ESOS Act 2000-CRICOS provider Code 00098G.