Towards an infrastructure for preparation and control of intelligent automation systems

Licentiate thesis, 2022

In an attempt to handle some of the challenges of modern production, intelligent automation systems offer solutions that are flexible, adaptive, and collaborative. Contrary to traditional solutions, intelligent automation systems emerged just recently and thus lack the supporting tools and infrastructure that traditional systems nowadays take for granted. To support efficient development, commissioning, and control of such systems, this thesis summarizes various lessons learned during years of implementation.

Based on what was learned, this thesis investigates key features of infrastructure for modern and flexible intelligent automation systems, as well as a number of important design solutions. For example, an important question is raised whether to decentralize the global state or to give complete access to the main controller.

Moreover, in order to develop such systems, a framework for virtual preparation and commissioning is presented, with the main goal to offer support for engineers. As traditional virtual commissioning solutions are not intended for preparing highly flexible, collaborative, and dynamic systems, this framework aims to provide some of the groundwork and point to a direction for fast and integrated preparation and virtual commissioning of such systems.

Finally, this thesis summarizes some of the investigations made on planning as satisfiability, in order to evaluate how different methods improve planning performance. Throughout the thesis, an industrial material kitting use case exemplifies presented perspectives, lessons learned, and frameworks.