Knowledge-Based Automation for Smart Manufacturing Systems

Smart manufacturing is targeted as the next generation of manufacturing by many national and international strategic development. The increasingly rich production data, the integration and extensive application of information technology, and the intelligent data processing and system modeling methods have collectively enabled smart manufacturing. Building upon them, manufacturing system modeling, knowledge acquisition, design, and real-time control are the key components [item 1) in the Appendix], [item 2) in the Appendix]. It is still one of the really huge challenges to gather data, transform them into information, and derive knowledge out of this information, especially given the requirement of knowledge that can be trusted as manufacturing systems may harm humans and the environment if they come to the wrong conclusion. Despite the learning and derivation of knowledge, it could be modeled beforehand and taken, for example, as an environmental model for online decisions like in deliberative agent-based systems. Nevertheless, for decisions during operation, real-time requirements, dependability, and security issues are to be guaranteed. Finally, for acceptance and trust, humans need to “understand” the reasons behind automated decisions; therefore, explainability or at least a white box description is an issue of such knowledge-based systems.