Level: Beginner
Practical experiments require a lot of money, time, and effort, so it is important to ensure that the results are reliable. To achieve this, it is necessary to acquire comprehensive response capabilities that allow you to understand and carry out the following through experience:
1) Understand the importance of reducing error variability. To do this, you need to understand the impact of error variability.
② Identify several factors that may definitely be effective. To do this, use screening experiments.
3) Ensure that the model (function) does not have any missing terms. This requires modeling experiments that are free of LOF (lack of fit).
④The essence of design is nothing other than optimization using mathematical programming. For this, easy-to-use software with excellent functions is essential.
⑤Even if the statistical processing is correct, the solution often deviates from the target value due to the influence of variability. This requires post-hoc regression correction.
In order to learn the above content safely and satisfactorily in a short time, experiential education using virtual teaching materials is essential.
This study proposes a comprehensive educational curriculum for practical experimental design using a flying ball simulator. It concretely introduces planning, experimental execution, data analysis, design (optimization), regression correction, etc.
I studied applied physics at university, and after joining a major control equipment manufacturer, I was in charge of everything from the basics to applications of production, including research and development of semiconductor devices for the company's products, development of elemental production technologies, construction of production lines, customer quality assurance, and ISO certification. After that, I studied optimization from a management perspective based on statistical quality control (SQC) at graduate school and obtained a doctorate in business administration. Now, I am more aware of data management due to the advancement of information and communication technology in the management perspective. Just as measurement technology has merged with the Internet and evolved into IoT, the engineers who promoted SQC are now active as data scientists. I started using JMP in my work in 2003 and immediately realized its high potential. I have presented on experimental design and optimization at the JMPer's Meeting, and have been giving oral presentations at Discovery Summit Japan since 2016.
*For those who wish to understand in more detail, a paper is available. If you are interested, please contact Mr. Ogawa , the presenter, directly.
