September 05, 2023 | Steffen Clauß
The Challenges of End-to-End Production Planning: Integrating SAP PP/DS and REO
Optimizing production planning is crucial in manufacturing. Learn about the challenges of integrating SAP PP/DS and REO for seamless end-to-end planning.
May 10, 2023 | Dr. Holger Brandl
Optimizing Semiconductor Production with Scheduling, Dispatching, Digital Twin & AI
Learn how combining scheduling, dispatching, digital twin, and AI technologies can deliver significant benefits in semiconductor production.
October 20, 2022 | Jan Siebert
Decisions On-Demand to Power Semiconductor Manufacturing
Smart sampling with SYSTEMA RBA decreases production time, minimizes metrology steps, and leverages wafer-level data for other fab optimizations.
May 24, 2022 | Karim Sadek
Process Run-Time Predictions
Predictive capabilities for process run-times can be used for operator guidance, resource optimization, and engineering insights.
August 09, 2021 | Travis Stevens
A New Way to Optimize Semiconductor Yield: Make the Machines Hum Again
How to optimize yields in semiconductor fabs using a sophisticated approach to analyze lot and equipment data.
July 07, 2021 | Jim Connett
E10 Unmasked – Closing the Loop
Q & A regarding some nuances with the application of the SEMI E10 standard.
June 21, 2021 | Jim Connett
What Does the Chip Shortage Mean for the Semiconductor Industry?
Manufacturing automation will play a critical role in semiconductor manufacturers’ ability to meet increasing demand for integrated circuits.
January 18, 2021 | Helen Leps
2020: A year of challenges and digitization
With Covid19 digitalization is more needed than ever. The manufacturing industry took the chance to tackle automation and digitalization with high force.
January 12, 2021 | Dr. Holger Brandl
Predictive Analytics: Enabling robust planning & factory optimization
Insights on predictive analytics to enable factory forecasting to optimize planning and production capabilities.
August 18, 2020 | Jim Connett
The Details Are in the Data
Insights on manufacturing data collection: How should data be collected? When should data be collected? Where should the data be stored?