Knowledge-based Technologies for Future Factory Engineering and Control

Global and lean supply chains subject manufacturers to sudden disruptions of different severity that affect shops floors and performance. Due to a variety of factors, disruptions do not only occur internally but also externally. Hence, if manufacturers want to ensure competitive performance in a highly dynamic environment, they have to be capable of quickly detecting disruptions and adapting their production adequately. The frequent appearance of supply and production glitches, however, highlights the inflexibility of existing supply and production systems. For detecting disturbances and initiating compensation mechanisms, knowledge e.g. about the production system, the good to be produced and the supply chain play a crucial role. Knowledge-based technologies which rely on a formal model encapsulating knowledge about a domain of discourse, can be an enabler for increasing reactivity and robustness of future factory automation systems. In this contribution, applications and developments of knowledge-based technology in the domain of future factory automation are presented. In order to detect supply chain disturbances earlier and realize robust, predictive diagnostics, the utilization of logic-based models are investigated. To reason about compensation options in case of disturbances, an knowledge-based production order optimization realized in a Manufacturing Execution System (MES) is presented. These knowledge-based operation techniques utilize a huge amount of knowledge which have to be available. To bridge the gap between engineering and operation, an integrated, knowledge-based approach to develop flexible field-level automation software, gather required information from Plant Lifecycle Management Systems and transfer this engineering knowledge into operation will be presented.