Six Sigma Design of Experiments Two and a Half-day Workshop

Continue building a strong foundation in Six Sigma design of experiments methodologies with our two and a half-day intermediate course

Course Description

Course Number SS507: Intermediate Design of Experiments (DOE): Methodologies in factorial studies with variable and categorical data

This two and a half days Intermediate Design of Experiments (DOE) workshop goes right to the heart of Six Sigma. Design of experiments is a microcosm of the complete Six Sigma DMAIC protocol in its quest for defining Y = f(x)). Students will learn Design of Experiments protocol that aligns perfectly with Lean principles by emphasizing value–added process steps, allowing the experimenter to make informed decisions about the relative benefits of including lesser value-adding steps in the design and execution of experiments.

This workshop extends the teachings from the Six Sigma — Introduction to Design of Experiments (DOE). After a thorough review of basic Design of Experiment principles, students will learn how to design and analyze statistically sound studies for: 3+ factors and 3+ levels, with full and fractional factorial response surface designs to model linear and non-linear cause and effect relationships. Participants will learn effective approaches to design optimum and robust processes, and how to do so in the most efficient manner possible.

Course Topics:

  • Design, run, analyze and interpret studies for five and more factors and develop process and product solutions requiring linear and non-linear cause and effect models.
  • Design and interpret efficient fractional designs with minimal risk of confounding important effects and thereby concluding incorrectly about improvement or design solutions for process or product.
  • Develop process and product guidelines for managing improved processes and products.
  • Apply Design of Experiments to your Six Sigma project.
  • Practice with simulations in the use of software to design, analyze, interpret and develop solutions with Design of Experiments software.
  • Participants receive course reference materials and free time-limited copies of Design Expert software for the design and analysis of designed experiments.

Day1 — Review of Concepts and Methods for the Design of Experiments, Introduction to Fractional Designs:

  • Review from Intro to Design of Experiments — Shewhart and Fisher concepts, Central Limit Theorem, Five Tenets for DOE, DOE Protocol, Manual analysis of effects, statistical significance, interaction plots and the Y = f(x) model development, Design Expert Software.
  • Design and analyze an experiment using simulations.
  • Introduction to fractional factorial designs to enable the economic design of experiments with 3+ factors.

Day 2 — Fractional and Response Surface Designs for Enabling Linear and Non-linear Modeling:

  • Assessing and managing the risks of confounded effects resulting from fractional designs.
  • Options for interpretation and follow&up for the results of fractional designs.
  • Process optimization based on the results of a Designed Experiment.
  • Sensitivity analysis and accounting for robustness in process and product optimization.
  • Design and analyze an experiment using simulations.
  • Introduction to Response Surface designs for 3+ level designs to enable non-linear modeling and true optimization.
  • Augmenting 2–level designs to create 3+−level designs.

Day 3 — Response Surface Designs (RSM), Modeling and Simulation; Application to DMAIC and DFSS projects:

  • Designing RSM studies from scratch – central composite designs, optimal designs, one-factor designs.
  • Design and analyze an experiment using simulations.
  • Application of Design of Experiments to your Six Sigma project.
  • Summary and Conclusions.

What career paths benefit the most from Intermediate Design of Experiments Workshop?

  • Process owners for any type process or anyone who is responsible for developing processes and process analysis, performance management and reporting.
  • People working with manufacturing or non-manufacturing process analysis, management and improvement.
  • Engineers, quality managers, engineers and technicians, manufacturing personnel, non-manufacturing personnel who will participate in the design and implementation of designed experiments for manufacturing and business process analysis and improvement.
  • Six Sigma Black Belt certification candidates managing DMAIC or DFSS projects
  • Product development engineers, especially those who regularly perform statistical analysis as part of Advanced Product Quality Planning (APQP) or equivalent product development protocols.
  • Leaders for organizations that aspire to world class operational excellence.

Additional Course notes:

Customized versions of this course are available on–site for organizations desiring to target specific groups or objectives desiring to target specific groups or objectives, e.g., overview for management including how to lead successful implementation of design of experiments; equipment operators with an emphasis on participation in the conduct and interpretation of results; quality and process engineers with emphasis on the design of experiments analysis and interpretation, sampling method design and follow–up strategies; marketing personnel and how to design studies to answer questions key to market interpretation. On–site customized courses typically include, at the discretion of the client, the design and execution of live experiments on the customers chosen processes or products.

Prerequisites: A basic understanding of statistics is preferable. This workshop on Intermediate Design of Experiments is a follow–up course from the Intro to Design of Experiments workshop (Six Sigma 505). However, as this workshop includes a thorough review of concepts and methods discussed in the Intro workshop, participants normally manage well even if they haven’t completed the intro workshop. On the other hand, for those who have completed the intro workshop, the review of concepts and methods serve as strong reinforcement of those principles and typically brings them to a significantly higher level of understanding and ability to apply them. Prior training in regression analysis and hypothesis testing isn’t required as we will teach the applicable principles as part of this course; however, they provide an excellent preparation.

Credit and Follow-up:

Participants who successfully complete this course will earn credit toward certification toward Six Sigma Black Belt certification. Participants completing the course will earn the right to return to audit the course free of charge whenever the course is offered and space is available.

Credits: 9 CEUs

Course Facilitator:

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