DELMIA Operations Intelligence for Composites enables users to extract risk patterns from production history that resulted in both high- and poor-quality composites.
In the composites industry, manufacturing engineers and process and quality experts are in charge of successful new product introductions, ramp-ups and continuous improvement of first-pass yield. A typical challenge they face is to determine which critical process and product attributes to monitor, and the right combinations to prevent variations.
Risk patterns are detected with a fact-based approach supported by actual data. From this analysis, rules are identified that will improve the composite’s quality and reduce scrap and rework. Real-time shop floor information is monitored, risk of quality defects is analyzed and operations are alerted of issues while there is still time to correct the situation. When a potential problem is identified, the level of risk is quantified based on best practices, a risk analysis is published and preventative or rectifying actions are proposed to the operators.
- Understanding patterns of production parameters that result in defects
- Gaining real-time visibility of the shop floor to monitor progress and
collaboratively solve production problems
- Communicating preventative or rectifying actions to operators quickly
- Improving production without having to re-engineer processes
Remove Unpredictability Analyze your shop floor data to discover hidden root causes of previously unexplained voids and delamination defects. Simplify execution and control of complex and highly engineered composite processes.
Formalize your Manufacturing Know How Capture best practices in natural language rules from past production data for clear recommendations to shop floor workers during real-time execution. Improve yields by capitalizing and industrializing best practices.
Scale up Production Volume Monitor shop floor data to quantify risk of defect and proactively prevent scrap and rework. Increase product quality through a closed
loop, continuous improvement process.
- Create risk probabilities of failure for ongoing processes at dedicated checkpoints
- Real-time adjustment of the production settings while staying within tolerances
- Leverage standard statistics indicators to filter variables
- Knowledge is formalized by the automated creation of rules
- Real-time traceability and reporting provides the insight needed to run critical operations
User Interface: View shows a rule of Risk Situation discovered in the data.
Visualization of Rules and Related Samples:
A graphical view enables users to understand how samples are distributed within and outside of a rule.