Level: Beginner
Because practical experiments require significant expense, time, and effort, achieving tangible results is crucial. To achieve this, it is necessary to develop comprehensive capabilities that enable the understanding and execution of the following points through experience.
① Understand the importance of reducing error variability. To do this, it is necessary to understand how error variability affects the results.
② Identify several factors that are likely to be effective. To do this, utilize screening experiments.
③ Ensure that the model (function) has no missing terms. To achieve this, modeling experiments without LOF (loss of fit) are necessary.
④ The essence of design is nothing less than optimization using mathematical programming. For this purpose, user-friendly software with excellent functionality is indispensable.
⑤ Even with correct statistical processing, the solution often deviates from the target value due to the effects of variability. Therefore, regression correction is necessary afterward.
To acquire the above information quickly, safely, and satisfactorily, experiential education using virtual learning materials is essential.
This study proposes a comprehensive and practical educational curriculum for experimental design using a ball flight simulator. It provides a detailed overview of planning, experiment execution, data analysis, design (optimization), and regression correction.
After studying applied physics at university, I joined a major control equipment manufacturer and have been involved in all aspects of production, from basic to applied research and development of semiconductor devices for our products, to the development of elemental technologies for production, manufacturing line construction, customer quality assurance, and ISO certification. Subsequently, I researched optimization of management perspectives based on statistical quality control (SQC) in graduate school and obtained a PhD in business administration. Currently, I am more strongly aware of data management in line with the advancement of information and communication technology within my management perspective. Just as measurement technology evolved into IoT by merging with the internet, the era has arrived where engineers who promoted SQC can play an active role as data scientists. I started using JMP in my work in 2003 and quickly realized its high potential. I have presented on experimental design and optimization at JMPer's Meetings and have also given oral and presentations at Discovery Summit Japan since 2016.
*For those who wish to gain a more detailed understanding, a research paper is available. If you are interested, please contact the presenter, Mr. Ogawa , directly.
