The explosive growth of the new energy vehicle industry, driven by electrification, intelligence, and connectivity, is reshaping the global semiconductor landscape. As the "nerve center" of automotive electronics, the quality of automotive-grade chips directly impacts driving safety and user experience. Establishing a robust quality management system has become a core competitive advantage for semiconductor companies to break through automotive certification barriers and capture market opportunities.

Automotive Transformation Drives "Extreme Challenges" for Domestic Automotive Chip Quality

From a functional perspective, automotive chips are mainly divided into four categories:

-       Computing and control chips (MCU/SoC)

-       Power chips (IGBT) for energy conversion

-       Sensor chips (CIS) for environmental perception

-       Memory chips for data storage

Automotive chips are widely used in critical areas such as powertrains, smart cabins, and autonomous driving, supporting the core functions of new energy vehicles.

With the increasing penetration of L3+ autonomous driving, the number of chips per vehicle is growing exponentially, posing unprecedented challenges to the computational performance and real-time response capabilities of automotive-grade chips.

Data from a third-party testing agency indicates that automotive-grade chips must pass over 2,000 reliability tests throughout their lifecycle, far exceeding the stringent requirements of consumer electronics. While industrial-grade chips typically maintain a defect rate of one per million, automotive-grade chips must achieve a "zero-defect" standard of one per billion. In terms of supply cycles, automotive-grade chips must support continuous supply for over 15 years to match the 20-year lifespan of vehicles.

The high-quality requirements of automotive-grade chips have compelled the semiconductor industry to form a precisely coordinated ecosystem. In the automaker’s supplier system, semiconductor companies typically operate at the Tier 3 level, requiring deep collaboration with chip design, wafer manufacturing, and packaging and testing. This synergy is reflected not only in technical alignment but also in the standardization of quality management systems.

Currently, the international automotive industry has established multiple authoritative standards, setting entry barriers for automotive-grade chips across dimensions such as reliability testing, end-to-end quality management, and failure prevention and management throughout the lifecycle from concept design to disposal.

GETECH QMS: Ensuring Automotive Chip Quality and Winning the "High-End Game"

Facing the "extreme" quality challenges of automotive-grade chips, GETECH’s QMS (Quality Management System) provides an integrated quality solution for the semiconductor industry. With the core philosophy of "Quality in One System," it covers end-to-end business scenarios from R&D, procurement, production, to post-sales, enabling precise quality control through data interoperability and process synergy.

1. End-to-End Business Scenario Coverage

GETECH QMS builds a comprehensive quality business management system covering R&D, supply, production, and service scenarios:

R&D Quality Control: Introduces APQP (Advanced Product Quality Planning) at the design stage, using DFMEA (Design Failure Mode and Effects Analysis) to identify potential risks and ensure designs meet automotive standards. An IC design company achieved a 40% improvement in potential risk identification during the design phase using GETECH QMS’s FMEA module.

Supply Chain Quality Management: Establishes a full lifecycle supplier management system, from qualification audits and performance evaluations to continuous improvement. For example, during IQC inspections, supplier-related information (including status, approved material lists, performance, and improvement actions) is automatically linked, enabling source control of quality issues.

Production Process Control: In wafer manufacturing and packaging/testing, QMS uses SPC (Statistical Process Control) to monitor key process parameters in real-time. For instance, alerts are automatically triggered when CPK values fall below 1.67, ensuring process stability. A packaging and testing company improved first-pass yield in critical processes by 3.2 percentage points after implementation.

Post-Sales Quality Traceability: Establishes a complete product traceability system, supporting end-to-end traceability from finished products to raw materials. During customer complaints, the system can locate key information such as material sources and process parameters for problematic batches within 15 minutes, significantly reducing analysis cycles.

2. Deep Integration with Automotive Standards: Six Tools to Enhance Yield

As one of the authoritative automotive standards, IATF 16949 builds on ISO 9001 by adding automotive-specific requirements, including core tools such as APQP and FMEA, guiding companies from inspection-based to preventive quality management. GETECH QMS deeply embeds automotive standards into its system functionality and provides specialized solutions for the six quality tools required by IATF 16949.

3. End-to-End Traceability: Accelerating Automaker Audits

To address automaker audits based on VDA 6.3 standards, GETECH QMS provides comprehensive audit support:

Audit Preparation: Automatically generates VDA 6.3 audit checklists, enabling companies to conduct self-assessments and corrections in advance, improving issue identification by 60%.

On-Site Audits: Offers real-time data querying, allowing auditors to quickly access key documents such as design files, process records, and inspection reports, improving audit efficiency by 40%.

Rectification Tracking: Automatically generates corrective tasks for identified issues, linking responsible departments and deadlines, improving rectification efficiency by 60%.

4. AI-Powered Quality Response Efficiency

GETECH QMS incorporates AI technology to create an intelligent quality response system, upgrading quality management paradigms:

Automated 8D Report Generation: Generates 8D report frameworks based on historical case libraries and issue characteristics, improving key information filling efficiency by 70%.

Quality Trend Prediction: Uses machine learning algorithms to analyze historical data and predict potential quality risks. One manufacturing company achieved a 92% accuracy rate in process anomaly warnings.

Intelligent Knowledge Assistant: Builds a quality knowledge base supporting natural language queries, providing real-time quality knowledge support to frontline employees and reducing training costs by 30%.

Conclusion

As the penetration of new energy vehicles continues to rise, the market for automotive-grade chips will expand further. To win the "breakthrough" battle, semiconductor companies must deeply integrate quality management into the product lifecycle, leverage QMS to streamline quality data chains, strengthen comprehensive quality control, and achieve product quality leaps. GETECH QMS, rooted in automotive standards, ensures stringent quality control through end-to-end business coverage and traceability, while AI-driven innovations propel automotive chip quality management into a new digital-intelligent era, solidifying the foundation for domestic substitution of automotive-grade chips.