design of experiments

better decisions through better analysis

see what our graduates have to say:

Don’t waste your time shopping around, partner with Air Academy.  We wasted three months vetting other companies.

Jeff M., Kopp Glass

The instructor was able to provide feedback/applications for ‘real world’ examples of the subject matter to our processes.

Chris J., Kopp Glass

Instructor explained the fundamentals as well as the application of DOE very well. He also helped the students understand how to apply DOE or MSA to their own systems.

Beth H., Sorb Technologies

This is a great introduction to Design of Experiments and the statistics involved therein.  Don’t feel like you will get lost, the course is done in a very tactful manner that teaches as you go.

Ross J., DST

The DOE Pro and SPC XL software is amazing!  Used Minitab and JMP previously, and the user interface for this new software makes it far easier to use.

Kai M., Zurn

I would highly recommend this Greenbelt training.  The course and tools are designed to bring success to the students & businesses.  The skills learned will bring value throughout your career.

Cecilia B., Sauer Brands

Highly recommended! The content was explained in an easy-to-understand way, and was practically applied so that you could see it in action.

Justine G., Kopp Glass

The course it is well presented and detailed and well worth it to establish a base understand of the DoE principles and applicable to just about any project that requires optimization.

Richard M., DST

Where I benefited the most from this course was working through the many examples that were provided during the course.  The content was very well explained which made working through the examples, while the instructor presented them, easy to follow and very helpful.

Rob M., Zurn

Instructor clearly has a wealth of knowledge and experience and he was able to convey to us some very complicated ideas and concepts through these examples, as well as his excellent presentation skills.

Brad T., DST

The course is well thought out and organized.  It provides a systematic approach to test prep, test design, and results analysis of both means and variation.

Rainer E., Zurn

Highly recommend especially if your work is directly related to designing experiments with longer run times. This course will assist in pointing out the important factors and how to go on about being most efficient while maintaining a high confidence level.

Karam G., Zurn

Design of Experiments Course

Quality is a paramount concern in any manufacturing or service organization. In today’s business climate, the need to improve quality and productivity while reducing costs has never been greater. One powerful technique for achieving these objectives is the Design of Experiments or DOE. DOE is the best way to collect data to understand your product, process, and customer.

Air Academy Associates is pleased to offer a comprehensive course on this important quality improvement tool. Taught by expert instructors, the course provides participants with the knowledge and skills necessary to conduct successful experiments.

The course begins with a review of experimental design basics and statistical concepts. It then progresses to more advanced topics such as factorial designs, response surface methodology, and Design For Six Sigma. Throughout the course, participants will work on hands-on projects to gain practical experience with the techniques covered.

Upon completing the Design of Experiments course, participants can select and implement the appropriate DOE method for their application. They will also be better equipped to troubleshoot quality problems and effectively communicate the results of their designed experiments to management.

Who Should Participate in This Online Experimental Design Course?

As part of the Air Academy Associates’ Lean Six Sigma Black Belt training program, this course can be utilized to prepare for the Air Academy’s LSBB certification. It is also an excellent stand-alone course for enhancing your competence and increasing your skill set in any industry where product and process development or technology deployment is responsible.

This course will help you make sound decisions concerning the design and management of your products and processes, instead of constructing mathematical arguments or solving complex matrix problems.

Basic Objectives

  • Use the design of experiments methods to accommodate both stochastic and deterministic computer models.
  • Effectively plan, develop, and carry out experiments. Then, analyze the collected data to draw accurate, unbiased conclusions.
  • Learn to use software experimental design tools to create original process designs when standard methods are not readily applicable.
  • Use response surface approaches to optimize the system following a successful screening.

Overview of The Course

Highlights of Design of Experiments Training

The following are the features of this design of experiments online course:

  • The Design of Experiments video lectures, exercises, practical examples, manuals, and tests are included.
  • Could you set up the conditions for a DOE and the procedures that must be followed?
  • Recognize the variations between the full factorial and fractional factorial methods, as well as the advantages and disadvantages of each.
  • You can learn how to create these studies, when to use a Plackett-Burman and Taguchi DOE, and many other designs and when not to.
  • Learn how to run a DOE study with Air Academy Associates’ widely used statistical analysis software.
  • Learn how to leverage DOE data to help design and problem-solving teams make wise decisions.
  • I’d like you to please learn the essential components for conducting a successful DOE study.
  • Learn crucial abilities for your work in product and process development, technology implementation, or as a Lean Six Sigma team member.

Enroll With Us Today

Are you looking for a course on the design of experiments? Look no further than Air Academy Associates! Our course offers a comprehensive introduction to the principles and techniques of designing experiments. You will learn how to plan and conduct effective experiments, interpret data, and use statistical methods to improve the quality of your results. The course is taught by experienced instructors who are experts in well-designed experiments. Enroll today and get started on your journey to successful process optimization!

Click to register for our online Operational Design of Experiments Course.

FAQS

To use a subset of the experimental runs from a , experimental layouts are called fractional factorial designs. The subset is chosen to take advantage of the sparsity-of-effects concept to offer information on the problem’s most important parts in a fraction of the time and resources required for a full factorial design. To put it another way, it uses the fact that many full factorial design tests are redundant and yield little new .

To use a subset of the experimental runs from a full factorial design, experimental layouts are called fractional factorial designs. The subset uses the sparsity-of-effects concept to offer information on the problem’s most important parts in a fraction of the time and resources required for a full factorial design. In other words, it uses the fact that many full factorial design tests are redundant and yield little new information about the system.

Here are the most important differences between the two main kinds of DOEs:

  • Factorial/RSM factor levels have nothing to do with each other. Temperature, speed, and the type of material are all things that can change.
  • Substances are used instead of factors in the formulation and mix of DOEs. The Mixture DOE levels will be the same as the Factorial DOE levels in terms of the proportions of the different parts and factor levels because the total proportions of the ingredients will always be the same; if the proportion of one ingredient changes, the proportions of at least one other ingredient must change to make up for it. This means that unlike in Factorial/RSM, the proportions of the ingredients in Mixture are interdependent.

Among the software packages in the market, the DOE PRO is a robust Design of Experiments instrument that can evaluate and optimize various chemical reactions. This easy-to-use Excel snap-in statistical software allows you to generate designs, analyze designs using multiple regression, display results, optimize, and predict.

Integrating DOE Pro XL with Excel will accelerate the data analysis process. Instead of copying and pasting your data into another application, DOE Pro XL enables you to store, analyze, and display your results directly within Excel. Check out our wide array of software tools for you to use with a free trial period you can take advantage of.

This course will teach you the fundamental steps to carrying out a successful design of experiments. Here are the fundamental steps:

A designed experiment generally proceeds as follows:

  • Define the goal (s)
  • Learn more about the procedure
  • Could you create a list and decide which variables to use?
  • Could you put levels on the variables?
  • Perform experiments
  • Analyses of the data and conclusions

The reality is that it is easier than you think. When completing the Design of Experiments online course, you can start with a basic “trial-and-error” or one-factor-at-a-time (OFAT) approach, then move on to more complex methods when ready.

Anyone interested in learning more about their environment makes use of DOEs. They are not constrained to a specific industry. DOEs are applicable in every industry and across all sectors. Field tests and even simulating real-world scenarios can be done using DOEs. A DOE could be used, for instance, to research how various packaging materials affect the shelf life of food products.

Furthermore, using experimental designs to enhance already-existing products is incredibly helpful. They can be used to lower expenses and boost efficiency.

In most experiments, several variables must be considered. These variables affect the outcome of your experiment. They are classified into several categories:

  • Experimental factors. You can specify and set your experimental parameters. For example, the highest temperature to which a solution can be heated.
  • Classification factors. Although classification factors cannot be defined or fixed, they can be recognized, and your samples selected accordingly—for example, a person’s gender or age.
  • Combinatorial or Treatment factors. You will want to manipulate the treatment factors important to you in your experiment to test your hypothesis.
  • Noise or Nuisance Factors. Although you are not interested in nuisance factors for the experiment, they may still impact your results.

Furthermore, you’ll need to employ two basic types of combinatorial/treatment factors:

  • Quantitative factors, such as pH levels, can be set to any precise level required.
  • Qualitative factors. Different plant species and a person’s gender are just two categories that comprise qualitative factors.

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