Experimental design is a methodology that enables scientists and engineers to efficiently assess the effect of multiple inputs (factors), on measures of performance (responses). Compared to one-factor-at-a-time, trial-and-error approaches, a well-designed experiment can provide clear results while dramatically reducing the required amount of testing.

In this series we’ll learn how to effectively implement (or expand) the use of design of experiments at your organization. We’ll learn a little more about the history of design of experiments (DOE), its benefits and the numerous ways it can help expand your understanding and positively impact your organization.

During the series, we’ll learn:

  • The origins of DOE, how it has evolved, and new innovations on the horizon.
  • The benefits of using statistically designed experiments.
  • How to design efficient experiments despite real-world constraints like process or budget limitations.
  • How to implement “Easy DOE” and how it can help you understand cause and effect better (and faster).
  • Tips, tricks, and best practices for effectively using designed experiments in your organization.

Each session lasts 30 minutes, followed by 15 minutes of live Q&A with our experts.

Session 1: DOE: Past, Present, and Future

Presenter: Bradley Jones

Design of experiments is one of the most strategic contributions to enable us to learn faster from data and understand cause and effect.

In this session, JMP’s Distinguished Research Fellow, Dr. Bradley Jones will discuss the origins of design of experiments, how it evolved and its immeasurable contributions to statistics and data discovery.

During this session we will learn:

  • About the pioneers of the design of experiments methodology (past, present, and future).
  • The evolution of experimental design, including inflection points and advancements that have helped shape the methodology.
  • How fast (or slow) DOE has been adopted across various industries and application areas.
  • Tools that make DOE easier to implement.
  • How DOE has changed the world and how exciting new innovations can make it even better.

Following Brad’s talk, we’ll hear from Dr. Ryan Lekivetz. Now that Brad has retired, Ryan has assumed leadership of the DOE and reliability R&D groups at JMP. He’ll discuss the future of DOE at JMP, share more about his continued collaboration with Brad and other innovators, and answer questions. Anything DOE-related is fair game, so come prepared.

Session 2: Design of Experiments Made Easy

Presenter: Peter Polito

Sometimes the hardest part of conducting a designed experiment is getting started. Few of us – particularly when we’re under a deadline – have the time or energy to learn the new concepts and jargon needed to be effective with DOE. What we really need is an “easy button” for shortening the learning curve.

Good news! Whether you’re brand new to DOE or been using it for years, JMP now has a guided platform that makes designing, running and analyzing experiments consistently… yes, essentially an “Easy Button” for DOE.

During this session we’ll learn:

  • The basics of DOE.
  • The importance of conducting consistent experiments.
  • How the new Easy DOE platform in JMP 17 provides a guided workflow that allows you to conceptualize, design, run, analyze, and report out the results in no time flat.

Session 3: Unlocking the Power of Designed Experiments

Presenter: Mike Anderson

When it comes to efficiently collecting experimental information, there is no better method than designed experiments. Still, they have limitations. Due to their incredible efficiency, and relatively small data sets, it can be difficult to create a robust predictive model from a designed experiment without compromising the data set.

A recent development has identified a novel way to create robust models from these data sets by stringing together cutting-edge modeling techniques and best practices to create an enhanced solution.

In this session we’ll learn:

  • The importance of cross validation and why it’s hard to do with designed experiments.
  • An exciting new capability you can apply to your designed experiments… and even your historical data.
  • How to leverage historical data along with new techniques to create a holistic experimental design process.

Register now for this free webinar

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