Help enterprises quickly achieve digital transformation of quality management
1. Quality data cannot be effectively utilized
Difficulty in quality data collection, severe information silos, poor collaboration, unable to uncover the effective value of data
2. Quality indicators are not unified
Inconsistent quality inspection standards/basis, insufficient authenticity of inspection conclusions, difficulty in decision-making
3. Difficulty in quality cost statistics
Inconsistent business logic across multiple systems, difficulty in internal/external quality cost statistics
4. Lack of a fully functional quality system
Using quality modules of other application systems like ERP, MES, etc., with incomplete business functions and poor practicality
Cover all quality scenarios in the product lifecycle, achieve quality data interoperability, eliminate information silos
Based on quality gates and PDCA theory, achieve automatic data analysis and monitoring, quality improvement collaboration
Support multi-scenario model deployment on cloud, edge, and end, with one-click push of high-concurrency low-latency edge models from the cloud
Comprehensive quality management in enterprise production and manufacturing, continuous PDCA improvement, serving users at different levels