System Overview
Designed and developed based on ISO/TS quality management system requirements, the system supports comprehensive management of standards, regulations, and quality activities. It not only digitizes quality management processes but also provides data analytics and information mining capabilities, offering detailed trend analysis to help users identify issues, improve production processes, and enhance product quality.
Challenges of Traditional Quality Management
- Large volumes of forms require manual completion, and significant manpower is needed for data consolidation.
- Process events within quality activities cannot be effectively linked, resulting in insufficient quality traceability.
- Management cannot access workshop product quality status anytime and anywhere.
- Customers face difficulty quickly querying historical product quality records.
Key Features
Following the PDCA principles, the system establishes a comprehensive internal quality management framework and achieves quality objectives based on accurate real-time data collection and statistical analysis.
- Custom Quality Inspection Standards: Define control limits (supporting national standards and user-defined standards).
- Quality Inspection Data Collection: Automated or manual data acquisition, supporting multiple devices such as tablets, PCs, and PDAs.
- Quality Inspection Activity Tracking: Rapid output and traceability of inspection results and inspection reports.
- Quality Performance Analysis: Rich trend analysis tools, SPC control charts, and other statistical tools to provide scientific evidence for process improvement.
- Predefined process quality parameters and inspection specifications, with real-time alerts for abnormalities.
Core Value
Optimize Quality Management Operations and Improve Overall Efficiency
- Paperless workflows enhance information transfer efficiency while saving time and space.
- Streamlined and standardized quality management makes quality operations simpler.
- Multiple convenient methods for data collection.
- Automatic aggregation and statistical processing of core quality data, improving the speed and accuracy of data analysis.
Achieve Quality Monitoring Throughout the Production Process
- Enhanced process prevention and diagnostic capabilities.
- Scientific machine and process adjustments based on real, accurate data.
- Real-time characteristic monitoring with abnormality alerts linked to responsible personnel, improving issue-handling efficiency.
- Intuitive and efficient visual management.
Product Quality Traceability
- Comprehensive sharing of quality information.
- Forward and backward quality traceability.
