mKGMPP: A multi-layer knowledge graph integration framework and its inference method for manufacturing process planning

Abstract

Manufacturing process planning is the process of organizing the production steps based on product design. It aimed at determining the process routes and formulating resource allocation strategies in response to digital model. In the process of connecting product design and manufacturing, designers and manufacturing technicians focus on different aspects of the digital model. This leads to a distortion when manufacturing technicians transform the digital model information into process information. As a result, this results in a deviation in the mapping between design intent and process intent. Such deviations can lead to disconnections in the association of process knowledge, undermine the consistency and traceability between process documents and digital models. Therefore, this study proposes a multi-layer knowledge graph for manufacturing process planning(mKGMPP) and an interactive manufacturing process planning system (IMPP system) driven by digital model and the proposed knowledge framework. The historical process schemes are analyzed using a dual-dimensional approach based on text and digital model. An extraction strategy based on structured data parsing and intelligent agent processing is employed for textual knowledge extraction. For geometric feature knowledge, the OpenCV library is employed, along with Gaussian blur, morphological operations, and the Canny detection algorithm. The intra knowledge of process schemes is integrated using the 4M1E elements, and multi-dimensional relationships between process schemes are established based on TQCSE. The geometric similarity inference module, process scheme inference module, and processing content modification module have been developed, and an interactive interface has been built based on Gradio. A manufacturing process planning of a slender shaft in the aerospace domain validates the rationality of the proposed knowledge organization framework and knowledge inference method.