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Publications (13)
Since high data volume and complex data formats delivered in modern high-end production environments go beyond the scope of classical process control systems, more advanced tools involving machine learning are required to reliably recognize failure patterns. However, currently, such systems lack a general setup and are only available as application...
Semiconductor manufacturing is a highly innovative branch of industry, where a high degree of automation has already been achieved. For example, devices tested to be outside of their specifications in electrical wafer test are automatically scrapped. In this work, we go one step further and analyse test data of devices still within the limits of th...
In semiconductor industry it is of paramount importance to check whether a manufactured device fulfills all quality specifications and is therefore suitable for being sold to the customer. The occurrence of specific spatial patterns within the so-called wafer test data, i.e. analog electric measurements, might point out on production issues. Howeve...
Semiconductor devices must fulfill highest quality standards since they are used in safety relevant applications. Bad devices, namely devices which are not fully functional after the production are scrapped immediately and not delivered to the customer. Unfortunately, among the remaining ones there are still devices with increased risk, prone to in...
Reliable semiconductor devices are of paramount importance as they are used in safety relevant applications. To guarantee the functionality of the devices, various electrical measurements are analyzed and devices outside pre-defined specification limits are scrapped. Despite numerous verification tests, risk devices (Mavericks) remain undetected. T...
The problem of contemporary semiconductor reliability testing is twofold: on one hand demands on the device lifetime increase steadily implying longer testing times and on the other hand resources are limited (devices, testing time, ...). Therefore it seems unavoidable to apply advanced statistical methods to gain a reliable lifetime model. To incr...
Performing experiments is necessary to find influences of different factors on the measured output. In semiconductor industry experiments are mainly performed following predefined specifications and guidelines, given by experts for the device under test (DUT). The statistical method design of experiments (DoE) provides an objective solution to the...