Set a strong foundation in Six Sigma design of experiments methodologies with our one and a half days course
Course Number SS505: Introduction to Design of Experiments (DOE): Methodologies in Factorial Studies with Variable and Categorical Data
This Introduction to Design of Experiments one and a half-day workshop will prepare students to unlock the secrets of cause and effect of processes and products through the design of two-level full factorial studies with variable and categorical data. Students will learn how to design an experiment, how to make sure it reveals what needs to be known. Discovering the sweet spots for important process outputs, how to define process windows, and how to look for opportunities to create robustness are areas of focus for this course. Participants will learn the underlying concepts essential to assuring the design of effective experiments and how to ensure the most efficient use of resources for running a designed experiment. The course provides plenty of hands-on opportunities to practice new skills in simulated and live processes that assure students can walk away with new skills that can immediately be used in Six Sigma DMAIC or DFSS projects.
- How to design, run, analyze and interpret important studies to identify cause and effect and how to develop solutions to solve problems, improve processes and their outputs, or design new products and process for successful implementation — your ticket to operational excellence
- How to select study design options and strategies for accelerating the attainment of the study’s goals.
- How to exploit design of experiments methodology to assure the effectiveness of day to day operations, project and process management, and ensure your successful completion of Six Sigma DMAIC and DFSS projects
- How DOE meshes with successful SPC and SQC implementation.
- Participants receive course reference materials and free time-limited copies of Design Expert software for the design and analysis of designed experiments
Day 1 — What is a Design of Experiments, How to design and analyze an experiment, and intro to Design Expert Software
- Simulated process demonstration to illustrate the necessary considerations for designing a meaningful and productive experiment to identify and quantify cause and effect – the five tenets of an effectively designed experiment
- The step by step design and execution protocol for design of experiments
- Workshop to manually create and analyze a designed experiment for simulated processes to drive home the concepts — design, performance, calculation of effects, determination of statistical significance, the creation of the model and interaction, and effects plots
- Introduction to Design Expert software and workshop to demonstrate and practice the use of the software to both design and analyze a designed experiment
- Workshop to design and execute a 3-factor full factorial simulated designed experiment using the Design Expert software
Day 2 — Optimizing Processes with design of experiments
- Design and analysis of a live process
- Workshop to design and analyze a process and practice, including the analysis and interpretation of the results
- How to apply design of experiments in a Six Sigma DMAIC or DFSS project, as part of an SPC and SQC implementation, or in a routine part of process management and continuous improvement
Upon completion of this one and a half day workshop, participants will understand the foundational principles of the Six Sigma design experiments methodology and leave with a greater ability to manage effective processes.
What career paths benefit the most from Introduction to 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 staff who will participate in the design and implementation of designed experiments for manufacturing and business process analysis and improvement
- Six Sigma Green Belt certification candidates and 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 and on-site versions of this course are available for organizations desiring to target specific groups or objectives. Examples include: 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 a focus 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 understanding.
Prerequisites: A basic understanding of statistics is preferable. Concepts such as histograms, distributions, mean and standard deviation, area under the normal curve, and the central limit theorem are helpful and are reviewed in the course. 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 complete this course successfully will earn credit toward Six Sigma Green Belt and Six Sigma Black Belt certification. Participants completing the course will earn the right to return to audit free of charge when the course and classroom space is available.
Credits: 1.5 CEUs
On‐site training & coaching
In addition to our courses, we provide on‐site training and coaching to individuals and teams