JapanChemicals and materials2018 – ongoingJX Advanced Metals
DataRobot analysis of manufacturing defects at Isohara
JX Advanced Metals staff reported completing analysis within 1 week of a defect occurring
Problem
Manufacturing teams relied heavily on experience to explain defects. Existing statistical tools were difficult for employees without specialist knowledge.
Approach
JX Advanced Metals began adopting DataRobot in 2018 with support from NTT DATA. Isohara staff used models to investigate warping and cracking in metal products, then tested manufacturing changes. Initial results took more than a year, arriving in 2019.
Results
Takeaway
The faster analysis followed a lengthy learning period. Staff interpreted model results and tested changes in the manufacturing process.
Categories
- Size
- Large enterprise
- Industry
- Chemicals and materials
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
NTT DATA described DataRobot's adoption and practical support at Isohara. Customer staff reported completing defect analysis within 1 week after spending more than a year developing their initial capability.
Full details are in the original sources.
