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Nowadays end-users demand high variety and custom-engineered products. To be able to respond to these demands and stay competitive, a smart design and control of high-mix low-volume manufacturing systems is critical. This becomes possible by the rapidly increasing amount of real-time sensor and production data that can be shared among products and production resources, thus creating an Internet of Things. It facilitates the optimization of a factory as a whole: instead of sub-optimizing production units and processes separately, we can create flexible, intelligent and even autonomous manufacturing networks. The manufacturing research line aims at making this vision a reality.

We conduct research in topics such as:

• Data-driven models that combine prediction and optimization to improve operational KPIs
• Automated planning and scheduling mechanisms to interlink and control manufacturing operations, maintenance and material handling
• Optimized bio-manufacturing systems to enable cheaper and faster access to next-generation drugs

In these topics, research methodologies are used such as simulation, stochastic modeling and analysis, Markov decision processes, linear and nonlinear optimization techniques, data-mining, artificial intelligence and statistical techniques.