| Summary: | Manufacturing intelligence is the ability to gather and analyse data for decision-making in production systems towards reaching an objective. This project involves introducing intelligence in production systems for achieving self-configuration. This is done by conceptualising and developing the intelligent components that act as building blocks of the self-configuring production systems and their application in the system. The approach taken for the project is iterative and built from the bottom-up. A classification tool is developed to study the capability of self-configuration in the current industrial production system, followed by insight gathered through surveys. The theoretical aspects involving self-configuration are discussed, and a general adaptation strategy is developed that integrates self-configuration capabilities in the intelligent components. These components are then manipulated and controlled through the use of technologies. Tools and techniques involving asset administration shell, state charts/state machines, multi-agent system, information model and machine learning approaches were studied. These technologies were implemented to achieve self-configuration, leveraging data gathered during operation. This research is applied to use cases of an industrial leak test equipment MALT and on a force testing station of the PRIME assembly system. The dissemination of work is highlighted, and future possibilities are expanded.
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