AddManBERT: A combinatorial triples extraction and classification task for establishing a knowledge graph to facilitate design for additive manufacturing
Haruna A. Noman K. Li Y. Wang X. Hasan M.J. Alhassan A.B.
September 2025Elsevier Ltd
Advanced Engineering Informatics
2025#67
In recent years, triple extraction and classification have received attention in the context of Additive Manufacturing (AM). However, the lack of a formalized process to extract and classify triple from textual data poses challenges for the effective embedding learning techniques in utilizing AMs product innovation and manufacturing capabilities. Hence, the AM fields manual cognitive process hinders the broader adoption of Design for AM (DFAM) in manufacturing. Aiming to solve these challenging problems, this research proposes a Natural Language Processing (NLP) and Knowledge Graph (KG) methodology for triple extraction and classification from textual data to provide an embedding learning approach. Initially, multi-source textual data for triple extraction and classification is developed. Then, AM Bidirectional Encoder Representation from the Transformers (AddManBERT) is used for triple extraction and classification. The AddManBERT utilizes dependency parsing to determine the semantic relations between the entities for triple extraction and classification. Consequently, the AddManBERT transformed each extracted piece of knowledge from the textual data into a 768-dimensional vector structure by analyzing the projected probability of the output within the center word based on the token embedding surrounding the input. The triples extracted and classified are then saved in the Neo4j database and displayed as graph nodes. An experiment and an application case study verify the proposed methods efficacy. The experiment results indicate that the proposed method outperforms the traditional centralized approaches in responsiveness, classification accuracy, and prediction efficiency.
Additive manufacturing , BERT model , Knowledge graph , Textual Data , Triples extraction and classification
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School of Aeronautics, Northwestern Polytechnical University, Shaanxi Province, Xian, China
School of Civil Aviation, Northwestern Polytechnical University, Shaanxi Province, Xian, China
Aircraft Strength Research Institute of China, Shaanxi Province, Xian, 710065, China
Dataxense, Scotland, Aberdeen, United Kingdom
Dept. of Robotics and Mechatronics, Nazarbayev University, Astana, Kazakhstan
School of Aeronautics
School of Civil Aviation
Aircraft Strength Research Institute of China
Dataxense
Dept. of Robotics and Mechatronics
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026