Level: Intermediate
Recently, in order to improve chronic problems such as defect occurrence and low equipment operating rate in the manufacturing and equipment industries, many efforts are being made to improve the large amount of data generated in the field through data science.
Therefore, for Citizen Data Scientists who want to improve on-site problems, we would like to introduce a case study that re-established a problem-solving methodology in a big data environment through analysis-modeling-optimization using JMP.
* Problem-solving methodology to be introduced: DATA Roadmap (Detect - Analyze - Transform - Apply)
1. Detect: Data Setup and NA and Outlier Processing
2. Analyze: Exploration and Validity Screening
3. Transform: Train/Test Data Set Separation and Modeling Analysis
4. Apply: Select optimal modeling and derive optimal factor conditions
