Solutions
IoT Solutions for Machining Lines
Case.01Improving quality while reducing costs with machining diagnosis utilizing AI
- Machining improvement
- Individual equipment
Issues
Need to detect machining abnormalities and analyze defect trend utilizing IoT data.
Need to bring down cycle time and tool costs by reducing the number of tool replacements.
Sampling inspection by human cannot completely prevent outflow of defective products.
Need to bring down cycle time and tool costs by reducing the number of tool replacements.
Sampling inspection by human cannot completely prevent outflow of defective products.
Solution
- Predict the quality during machining with AI by creating a predictive model based on the relation between machining data and workpiece dimensions
- Automatically diagnose and output the optimal timing to change tools by capturing the deterioration trend of the cutting tools and detecting wear and breakage
- *1Dedicated software (sold separately) for easy analysis even for production engineers with no experience in data analysis.
- *2The value varies depending on the learning data.
Benefits
- Prevent defects by detecting the factor with the machining automatic diagnosis
- Reduce cycle time, tool costs, and management costs with less tool replacement
- Enable quality control equivalent to 100 % inspection with the AI prediction of machining quality
Providing
solutions that serve the needs
of our customers
Case.02Utilizing the collected data to visualize the operation statuses and production results
- Machining improvement
- Monitoring
- Individual equipment
- Overall line
Solution
- Add the e-F@ctory Starter Package to the iQ Monozukuri Tool Wear Diagnosis for Machine Tools Package to monitor machine tools
- The e-F@ctory Starter Package displays collected operation statuses and production results data on the GT SoftGOT2000
Benefits
- Reduce system build costs by linking the data of the Tool Wear Diagnosis for Machine Tools and e-F@ctory Starter Package
- Real time monitoring of overall equipment effectiveness (OEE) and production results enables users to make more accurate decisions
