Helps enterprises to rapidly achieve digitalization of quality management
1. Ineffective Use of Quality Data
Difficulty in collecting quality data, info. silos, poor coordination, data value under explored
2.Quality Metrics Not Unified
Inconsistent standard/criteria for quality inspection, insufficient authenticity of test conclusions, difficulty in decision-making
3.Difficulty in Calculating Quality Costs
Incongruent logics between different systems, difficulty in calculating internal/external quality costs
4.A Lack of Versatile Quality Systems
Quality modules using such application systems as ERP and MES are incomplete in their functions and lack practicality
Full lifecycle coverage of product quality scenarios, quality data interconnections, info. silo eliminated
Automatic data analysis and monitoring, quality improvement collaboration based on quality gate and PDCA theory,
Cloud-end-edge multi-scenario model deployments, high concurrency and low latency end-edge one-click model pushing from the cloud
Total quality management of production and manufacturing, continuous PDCA improvement, can serve users of different levels