This use case aims to harmonize and digitalize equipment control and maintenance operations across semiconductor factory sites, especially within the Dresden and Villach fab cluster. It focuses on standardizing equipment checks, maintenance sequences, reporting, real-time monitoring, deviation alarms, and cross-site comparison in support of Infineon’s “One Virtual Fab” concept. A key objective is to develop an Equipment Health Factor that predicts future equipment deviations and helps optimize control plans and maintenance intervals. The expected impact is reduced routine workload for engineers, shorter waiting times, improved equipment availability, higher throughput, better cycle time, and more material-, headcount-, and energy-efficient fab operations.
| # |
Technology Name |
Description |
| 1 |
Test Wafer Harmonization |
A novel unified UI is developed to achieve test wafer harmonization across the 300 mm fab sites of IFD and IFAT. The goal is to reduce the total number of required test wafers, minimize costs, and maintain quality standards by supporting harmonized concepts, shared data access, cross-site comparison, and more efficient test wafer management. |
| KPI # |
Related Technology |
KPI Target |
| 1 |
Test Wafer Harmonization |
Fully harmonize 7 out of 19 work centers, reaching an average harmonization level of 45%. |
| 2 |
Test Wafer Harmonization |
Connect relevant databases and complete data extraction, with Y2 calculations showing approximately 700 kEUR savings. |
| 3 |
Test Wafer Harmonization |
Save approximately 4 production days when bringing production back to full flow. |
| KPI # |
Baseline |
| 1 |
The Villach and Dresden front-end manufacturing sites each have their own test wafer concepts. |
| 2 |
There is no harmonization between the sites. |
| 3 |
High material costs occur due to missing harmonization. |
| 4 |
High engineering costs occur due to missing harmonization of different databases, MES, and software. |
| 5 |
No ML methods are used within the test wafer strategies at both sites. |
| KPI # |
Validation Method |
| 1 |
Identify additional requirements to further improve existing software features and establish a beta version of the harmonization UI. Trial and verify the beta ANKO harmonization UI with harmonization teams from IFAT and IFD, following the One Virtual Fab approach. |
| 2 |
Specify the target state by each team and demonstrate acceptance of the defined target states through first test runs. Collect interim lessons learned, align challenges and risks, and prepare sustainment activities. |
| 3 |
Develop algorithms to track material usage, material process efficiency, recycling, and costs. Establish new database architectures for the two factories. |
| 4 |
Validate harmonization impact through reduction of ANKOs, such as phase-out and merging, reduction of wafers per ANKO, reduction of ANKO frequency, material optimization through reuse and recycling, logistics adjustments, and spin-off activities such as Rolling ANKO, Circular ANKO, and ANKO Reporting. |
- Industrial process phases made more effective and precise through integrated and tailored AI algorithms, methods, and tools.
- Reduced manufacturing costs in the long term.
- Improved overall productivity of the manufacturing factory by approximately 20%.
- Self-adjusted/adapted manufacturing processes above 15%.
- Providing documented methods for dynamic application of tools to improve sustainability.
- Improved performance and faster time-to-market.
The use case contributes to more effective and precise semiconductor manufacturing by harmonizing test wafer concepts, data access, reporting, and control procedures across the Dresden and Villach sites. The ANKO harmonization UI and related database connections support a more unified and transparent approach to test wafer management within the One Virtual Fab concept. The reduction of ANKOs, wafers per ANKO, ANKO frequency, and improved material reuse or recycling directly supports lower material costs and more sustainable fab operation. The achieved database connection and reporting capabilities also support faster deviation response, with approximately 4 production days saved when bringing production back to full flow. Overall, the use case improves productivity, reduces engineering and material effort, and supports cross-site harmonization of equipment-control-related processes.
| AI Toolbox Tool |
Use within the Use Case |
| Tabular Prediction Tool |
Used to analyse structured test-wafer, work-center, database, cost, and production-flow data across the Dresden and Villach sites. It supported harmonization analysis, cost estimation, and data-driven evaluation of test wafer strategies. |
| Device-Level Quality Detection Tool |
Used to connect test-wafer-related measurements and process data with device-level quality risks. It supported the harmonized control of test wafer strategies while maintaining quality standards across sites. |
| Time-Series Anomaly Detection Tool |
Used to detect deviations and abnormal temporal patterns in equipment-control, test-wafer, and production-flow data. It supported faster response to deviations and helped reduce the time needed to bring production back to full flow. |
| Explainability Tool |
Used to make harmonization, deviation, and equipment-health-related analyses more transparent for engineers. It supported interpretation of which data sources, work centers, or process indicators contributed to deviations, material usage, or harmonization decisions. |
| Document Parsing Tool |
Used to process and structure information from site-specific procedures, reports, harmonization documents, and engineering documentation. It supported the consolidation of heterogeneous information needed for cross-site test wafer harmonization. |