Industrial Dimensional Quality Data Management and Analysis System: Intelligent Enhancement of Manufacturing Quality

July 2017

Abstract

With the advancement of Industry 4.0 and smart manufacturing, the requirements for quality control are becoming increasingly high. Facing the diverse demands of complex manufacturing industries such as automotive manufacturing, aerospace, consumer electronics, heavy industry, and medical devices, the Dimensional Quality Management System provides comprehensive solutions. By empowering with artificial intelligence, the system achieves efficient predictive analysis, delivering excellent quality management and data analysis experiences for manufacturing enterprises.

Multi-Source Data Integration and Real-Time Analysis: Eliminating Information Silos

In the automotive manufacturing industry, the quality of component and body dimension data is crucial. Traditionally, many OEMs rely on Excel for manual recording and analysis, which is not only time-consuming but also prone to errors. The Dimensional Quality Management System integrates data from various measurement devices, such as Zeiss CMM, Nikon Laser Radar, ATOS measuring instruments, and portable scanners. The system automatically converts data formats and uploads them to a unified database, enabling cross-factory and supplier data management.

Intelligent Data Parsing and Visualized Reporting

The system features powerful data recognition and parsing capabilities, quickly unifying complex data from various devices into a single platform for analysis. Its 3D model interactive function is more advantageous than traditional PDF reports, allowing users to directly view real-time measurement results on the 3D model, quickly navigate, and examine key quality data. This enables more interactive data feedback and timely identification of anomalies. Designers and manufacturers can communicate based on the same real-time data, forming an effective feedback loop and avoiding rework and cost losses due to delayed information.

AI-Driven Predictive Analysis: Precise Quality Control

Based on AI-driven statistical analysis, the system can monitor key quality indicators (KPIs) in real-time. When data exceeds control limits or tolerance ranges, the system immediately issues alerts. This functionality significantly shortens the response time to issues, allowing users to focus on the anomalies that require attention. With Statistical Process Control (SPC) tools, the system can calculate Cp, Cpk, Pp, Ppk metrics, providing precise evaluations of the production process, identifying potential issues, and offering actionable adjustment recommendations.

Supporting Various Analytical Needs: Comprehensive Quality Management from Design to Production

In the aerospace industry, the precision of component dimensions is particularly stringent. The system not only supports standard tolerance analysis but also performs Measurement System Analysis (MSA) to ensure data reliability. Additionally, the system’s flexible configuration options can meet personalized enterprise needs. Users can customize report modules based on specific requirements and easily generate customer-required report formats, fully digitizing manual input and review processes, effectively improving quality management efficiency.

Integrated Business Intelligence Analysis: Achieving Efficient Supply Chain Collaboration

The system performs in-depth data analysis on a business intelligence platform, ensuring timely resolution of quality issues. By managing supplier data on a unified platform, users can validate and analyze the quality data from suppliers, improving part acceptance rates and enhancing supply chain integration and coordination. The system also offers the ability to share analysis panels online, enabling enterprises to embed real-time analysis results into MES or ERP systems, synchronizing production information and further enhancing intelligent data management.

Cost-Effective SaaS Model: Flexibly Meeting Enterprise Needs

Compared to expensive traditional quality management software on the market, the Dimensional Quality Management System adopts a SaaS service model, providing a more flexible and cost-effective solution. Users can choose between public cloud deployment or localized private cloud deployment to suit their personalized needs. The system also offers some free features, and users can add new devices and modules as needed, quickly seeing improvements in quality management.

Highly Compatible Industrial Software Ecosystem

The system can seamlessly integrate into an enterprise’s existing IT environment, whether it is a small or medium-sized enterprise or a large Original Equipment Manufacturer (OEM). Through this system, enterprises can enjoy comprehensive data management and analysis services.