In the domain of machine learning, automated decision making and big data analytics, there have been a number of advances achieved recently. For example, the availability of more computational resources made it possible to learn more complex machine learning models. Complementary, new algorithmic approaches for predictive analytics have been researched. These proposed methods will be evaluated for the application scenario of semiconductor manufacturing.

Any new technology has to be economically and socially viable. Indeed, the ultimate test for a technology to be adopted by companies and markets is its capacity to answer to consumers’ and communities’ needs, as well as companies’ aspirations and designs to performance improvement. Accordingly, the technical-technological and socio-economic impact of the research project will be examined.