Semiconductor manufacturing is a complex process consisting of hundreds of manufacturing steps, and is one of the most demanding of businesses. As device sizes diminish, product quality becomes increasingly sensitive to variations at every single process step. In order to monitor and control the manufacturing process, manufacturers have traditionally invested in methods to analyze specific processes or equipment to create solutions that enhance productivity, yield and quality.
However, not many carry out a holistic analysis. This is due to lack of visibility (or access to data) across functions. For example, a manufacturing problem is easy to isolate. But integrating design and manufacturing, or tightly mapping process recipe with design, requires new approaches to data management and analytics. The holistic approach delivers better results than traditional management methods. Better performance, higher efficiencies and faster ramp up of yield can be expected.
The volume and variety of data such as MES data, equipment data, PLM/Design Data, ERP and Planning, Recipe data, metrology and defect data, and parametric and electrical data requires integration and a holistic approach to analysis. The good news is that manufacturers have realized this and are rising to the challenge. Investments in data management and analytics are growing, thereby helping companies to predict process behavior, identify and isolate defective tools and recipes, correlate parameters to help improve yield, and provide better visibility to management across the plant. The allure of analytics is in the precision with which it can sift through complex data and improve efficiency, yield, decision making and time-to-market. Using analytics can help fabs identify systemic factors like defective tools/recipes that degrade productivity and efficiency, correlate parameters in real time to ensure yield improvements and failure analysis.
I believe that analytical solutions with data mining and advanced modeling features will be central to the ability of the semiconductor industry to meet customer requirements in the future. Performance improvements will enable the industry to neutralize margin erosion, ensure faster go-to-market capabilities as product lifecycles shrink and adapt to new market conditions. The survival for many in the industry could be directly related to the ability to deploy analytics.
Innovations that include interactive reporting, enhanced GUIs, collaboration features and the ability to integrate multiple data sources will help foundries and IDMs within the semiconductor ecosystem achieve higher efficiency and reliability with optimized fab utilization.