An Interaction Engine and Question Refactor Method in Question Answering for Knowledge-Driven Process Planning

Abstract: Process planning is the intermediate stage between product design and product production. In the ever-evolving landscape of manufacturing, the optimization of process planning plays a key role in ensuring efficiency, cost-effectiveness and overall productivity. Traditional process planning methods often rely on predefined rules and expert knowledge, along with process engineers’ experiences, which are tacit and unstructured, existing in their minds. Weak optimal results and resource inefficiencies come in accordance with inefficient knowledge reuse. Existing research work has developed systematic knowledge modeling for process planning and constructed a process knowledge graph (PKG), based on which fundamental question answering (QA) has been performed. But there is the single round strategy in the process of QA over knowledge graph (QAKG). Process planners’ questions may be not parsed and they don’t have chance to implement or even don’t know what to implement. We propose an interactive QAKG framework containing the question refactor method for process planning. The interaction engine will be triggered when the input question can’t be parsed to query statement for target entities. Candidate intermediate entities are searched and listed for specifying. The initial question will be refactored after integrated with the entities selected by users. The methodology is implemented by taking the process data of CPU cooler from a manufacturing enterprise. Results show the method could promote the intelligence of knowledge-driven process planning as well as the level of knowledge acquiring and sharing.

Keywords: Process planning, Knowledge Graph, Question Answering, Intelligent Interaction

DOI: 10.54941/ahfe1004863

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