Core domain ontology for joining processes to consolidate welding standards

Saha, Sattam; Usman, Zahid; Li, Weidong; Jones, Steve; Shah, Nazaraf

doi:10.1016/j.rcim.2019.05.010

Cited by 21 publications

(8 citation statements)

References 34 publications

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“…Applying ontologies for the purpose of reuse, sharing and improving interoperability of knowledge sources is not new within mechanical domains. Saha et al [1] introduced a core domain ontology for joining processes focusing on welding standards. The ontology is intended to overcome the terminological inconsistencies within and across those standards and therefore mainly on the categorization of welding processes.…”

Section: Related Workmentioning

confidence: 99%

Provision of cross-domain knowledge in mechanical joining using ontologies

Zirngibl

Kügler

Popp

et al. 2022

Prod. Eng. Res. Devel.

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Since the application of mechanical joining methods, such as clinching or riveting, offers a robust solution for the generation of advanced multi-material connections, the use in the field of lightweight designs (e.g. automotive industry) is steadily increasing. Therefore, not only the design of an individual joint is required but also the dimensioning of the entire joining connection is crucial. However, in comparison to thermal joining techniques, such as spot welding, the evaluation of the joints’ resistance against defined requirements (e.g. types of load, minimal amount of load cycles) mainly relies on the consideration of expert knowledge, a few design principles and a small amount of experimental data. Since this generally implies the involvement of several domains, such as the material characterization or the part design, a tremendous amount of data and knowledge is separately generated for a certain dimensioning process. Nevertheless, the lack of formalization and standardization in representing the gained knowledge leads to a difficult and inconsistent reuse, sharing or searching of already existing information. Thus, this contribution presents a specific ontology for the provision of cross-domain knowledge about mechanical joining processes and highlights two potential use cases of this ontology in the design of clinched and pin joints.

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Section: Related Workmentioning

confidence: 99%

Provision of cross-domain knowledge in mechanical joining using ontologies

Zirngibl

Kügler

Popp

et al. 2022

Prod. Eng. Res. Devel.

View full text Add to dashboard Cite

show abstract

“…Most previous approaches analysed data collected from limited laboratory experiments [67,68]. Ontology in welding has studied the incoherence of standards [69], or was used for ML modelling with semantics [66]. Other works relating ontology to data analysis have discussed improving data understanding [70], or database access with annotations [14,15].…”

Section: Related Workmentioning

confidence: 99%

SemML: Facilitating Development of ML Models for Condition Monitoring with Semantics

Zhou¹,

Svetashova²,

Gusmão³

et al. 2021

SSRN Journal

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“…Meanwhile, the PageRank algorithm was regarded as the foundation of knowledge graph construction and application. Saha et al [ 40 ] solved the issue of instability in the definition of the welding concept by applying ontology. In addition, researchers provided a formalized solution and concurrently standardized the field knowledge.…”

Section: Related Workmentioning

confidence: 99%

An ontology‐based procedure knowledge framework for the process industry

Cao

Zhu

2020

Can J Chem Eng

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Process industry enterprises rely heavily on expert experience in production, and expert knowledge is stored in multiple formats like, pictures, texts, videos, etc. Several isolated islands of information or knowledge are formed, and they are difficult to store, share, and expand upon. Therefore, the same procedure appears multiple times in different application scenarios, such as optimization scheduling, optimization operation, or fault diagnosis. If redundant knowledge is paid too much attention, decision-makers will not be able to comprehensively consider business knowledge. Thus, a novel framework is proposed for the process industry to manage procedure knowledge. This paper first divides the detailed procedure of process plants into four layers, that is, raw materials, intermediate materials, operation, and products based on the P-graph theory, which involves virtual hierarchies, nodes, and operations. Second, the domain ontology-based procedure knowledge model is constructed. Finally, two experimental cases, the Tennessee Eastman (TE) and the ethylene production process, are studied to verify the procedure knowledge framework (PKF). The PKF provides a useful foundation for the subsequent construction of a superstructure model based on the P-graph theory and is different from the previous industrial process industrial ontology model. The PKF has a theoretical basis for simulation calculation and makes future work based on PKF more accurate and interpretable.

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Core domain ontology for joining processes to consolidate welding standards

Cited by 21 publications

References 34 publications

Provision of cross-domain knowledge in mechanical joining using ontologies

Provision of cross-domain knowledge in mechanical joining using ontologies

SemML: Facilitating Development of ML Models for Condition Monitoring with Semantics

An ontology‐based procedure knowledge framework for the process industry

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