For modern manufacturing businesses, high-speed, high-yield, energy-efficient and highly customizable manufacturing facilities are vital. Manufacturing of complex devices often demands processing or even the development of new types of materials, such as nano- and bio-materials. Those materials tend to have nonstandard properties and complex structure themselves.

Smart factories with advanced automation are the natural next step in manufacturing technologies. These systems can be improved by the introduction of methods of self-optimization, self-diagnosis, and intelligent support of human workers in performing their increasingly complex tasks.

Machine learning is thus becoming decisive in analyzing the ever increasing quantity of complex data coming from industrial process monitoring sensors. Speed and accuracy of analysis are crucial to allow for in-process analysis and real-time control of manufacturing systems.

The goal of this workshop is to bring together researchers and practitioners from machine learning, advanced manufacturing, and materials science, in order to give them the opportunity to present and discuss their work, to exchange information, and to discuss important open problems at the intersection of these fields.

In addition to talks by renowned experts, the workshop will feature an open problems discussion, where participants could share open research problems or application cases that are relevant to the theme of the workshop.

Advanced manufacturing businesses (from food to electronics manufacturers) are looking forward to applying machine learning in their businesses, but they have no platform to connect to machine learning community in general. The same applies to materials science researchers.

Meanwhile, most of the machine learning researchers are working on different types of problems and are not aware of the new problematic, challenges and opportunities that can be found in advanced manufacturing or materials science.

This workshop will be a step forward to creating collaborations between these three communities, and will send a positive signal to many of those businesses that are currently struggling to find a proper application of machine learning for their products.