An assembly process planning pipeline for industrial electronic equipment based on knowledge graph with bidirectional extracted knowledge from historical process documents DOI

Youzi Xiao,

Shuai Zheng, Jiewu Leng

et al.

Journal of Intelligent Manufacturing, Journal Year: 2024, Volume and Issue: unknown

Published: June 5, 2024

Language: Английский

Knowledge graph-based manufacturing process planning: A state-of-the-art review DOI

Youzi Xiao,

Shuai Zheng, Jiancheng Shi

et al.

Journal of Manufacturing Systems, Journal Year: 2023, Volume and Issue: 70, P. 417 - 435

Published: Aug. 24, 2023

Language: Английский

Citations

62

CausalKGPT: Industrial structure causal knowledge-enhanced large language model for cause analysis of quality problems in aerospace product manufacturing DOI
Bin Zhou, Xinyu Li, Tianyuan Liu

et al.

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 59, P. 102333 - 102333

Published: Jan. 1, 2024

Language: Английский

Citations

41

Evolving to multi-modal knowledge graphs for engineering design: state-of-the-art and future challenges DOI
Xinyu Pan, Xinyu Li,

Qi Li

et al.

Journal of Engineering Design, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 40

Published: Jan. 6, 2024

With the support of advanced information and communication technologies open innovative design platforms, emerging blooming paradigm mass personalization drives process engineering to include knowledge with higher heterogeneity more complex modalities. To this end, Multi-Modal Knowledge Graphs (MMKG), evolved from semantic networks graphs, provide a powerful technology system for effectively organizing utilizing knowledge. understand state-of-the-art key aspects that enables MMKG, recognize potential challenges forefront applications in design, literature review MMKG-related publications is conducted. selected 131 representative papers together other 32 supplementary studies (up 11/11/2023), article summarizes technical practical efforts multi-modal extraction, fusion technology, specific process. Meantime, MMKG faces its foreseeable development potentials are discussed, which hoped basis futuristic explorations implementations MMKG-enhanced availability productivity design.

Language: Английский

Citations

15

Making knowledge graphs work for smart manufacturing: Research topics, applications and prospects DOI Creative Commons
Y Wan,

Ying Liu,

Zhenyuan Chen

et al.

Journal of Manufacturing Systems, Journal Year: 2024, Volume and Issue: 76, P. 103 - 132

Published: July 29, 2024

Smart manufacturing (SM) confronts several challenges inherently suited to knowledge graphs (KGs) capabilities. The first key challenge lies in the synthesis of complex and varied data surrounding context, which demands advanced semantic analysis inference second main limitation is contextualization systems exploitation domain knowledge, requires a dynamic holistic representation knowledge. last major obstacle arises from facilitation intricate decision-making processes towards correlated ecosystems, benefit interconnected structures that KGs excel at organizing. However, existing survey studies concentrated on distinct facets SM offered isolated insights into KG applications while overlooking interconnections between various technologies their application across multiple domains. What specific role should play aforementioned challenges, how effectively harness for these essential topics methodologies required make functional remain underexplored. To explore potential SM, this study adopts systematic approach investigate, evaluate, analyse current research KGs, identifying core advancements implications future practices. Firstly, cutting-edge developments challenge-driven roles techniques are identified, extraction mining construction updates, further extending embedding, fusion, reasoning—central driving ecosystems. Specifically, depicted holistically, emphasizing interplay diverse with comprehensive framework. Subsequently, foundation outlines discusses scenarios engineering design predictive maintenance, covering representative stages life cycle. Lastly, explores practical advantages systems, pointing emerging avenues.

Language: Английский

Citations

15

A knowledge graph-based intelligent planning method for remanufacturing processes of used parts DOI
Shuo Zhu, L C Gao, Zhigang Jiang

et al.

Journal of Engineering Design, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 28

Published: Jan. 12, 2025

Intelligent remanufacturing process planning is crucial for the efficient and high-quality of used parts with complex failure characteristics. However, due to varied characteristics parts, diversity processes, non-linear relationships among elements, relying solely on mathematical programming or manual empirical difficult effectively model optimise planning. To this end, a knowledge graph-based intelligent method processes proposed enhance efficiency quality by combining reuse. Firstly, as decision nodes, full-element ontology constructed, linking characteristics, corresponding plans. The BERT-BiLSTM-CRF extracts entities, graph (RPKG) constructed. Secondly, an decision-making based multi-node path retrieval proposed. Aim minimise carbon emissions, time, cost, feature similarity calculations nearest neighbour search (NNS) efficiently retrieve optimal plan each characteristic. Then, plans are merged constraints create complete plan. Finally, concrete case given verify effectiveness advantages method.

Language: Английский

Citations

1

Large language model assisted fine-grained knowledge graph construction for robotic fault diagnosis DOI

Xingming Liao,

Chong Chen, Zhuowei Wang

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103134 - 103134

Published: Jan. 23, 2025

Language: Английский

Citations

1

A large language model-enabled machining process knowledge graph construction method for intelligent process planning DOI
Qingfeng Xu,

Fei Qiu,

Guanghui Zhou

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103244 - 103244

Published: March 8, 2025

Language: Английский

Citations

1

Systematic knowledge modeling and extraction methods for manufacturing process planning based on knowledge graph DOI
Peihan Wen, Yan Ma,

Ruiquan Wang

et al.

Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 58, P. 102172 - 102172

Published: Sept. 22, 2023

Language: Английский

Citations

20

Exploiting a knowledge hypergraph for modeling multi-nary relations in fault diagnosis reports DOI
Xinyu Li, Fei Zhang,

Qi Li

et al.

Advanced Engineering Informatics, Journal Year: 2023, Volume and Issue: 57, P. 102084 - 102084

Published: July 4, 2023

Language: Английский

Citations

18

A knowledge graph-based bio-inspired design approach for knowledge retrieval and reasoning DOI Creative Commons
Liuqing Chen, Zebin Cai, Zhaojun Jiang

et al.

Journal of Engineering Design, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 31

Published: Jan. 31, 2024

Bio-inspired Design (BID) is a method that draws principles from biological systems to solve complex real-world problems. While diverse knowledge-based tools have served BID, the retrieval and reasoning capabilities of knowledge graphs not been explored in BID. This study introduces novel graph-based BID approach, exploiting power support In comprehensive ontology defined then applied construct BID-specific graph, enabling efficient representation rich knowledge. The graph supports by facilitating reasoning. Retrieval accomplished finding potential links between relevant design applications. Reasoning supported link prediction model follows process mapping Two case studies are conducted demonstrate effectiveness approach. first shows our approach outperforms other benchmarks retrieving related knowledge, second presents how aids generating inspirational ideas.

Language: Английский

Citations

9