Recursive approach to combine expert knowledge and data-driven RSW weldability certification decision making process

نویسندگان

چکیده

• Recursive and collaborative approach where knowledge gained from machine learning models is integrated with ontological knowledge. Ontology-based semantic framework supports recursive communication experts for data-driven RST weldability certification. Extracted RSW concepts the decision trees formalized by ontology converted rules into SWRL rules. Transformed datasets helped to develop improved that work as a new source of prediction. Data-driven techniques have shown promising results in analysis understanding complex welding processes. Data analytics play significant role turn data valuable insights assist certification decision-making Resistance Spot Welding (RSW) well. However, successfully perform associated analytics, domain essential construct more ‘sense-making’ models, often cannot properly capture nuances do not indicate relationship among parameters. Thus, developed rough experimental provide meaningful sensible expert. In this article, we employ between so can be process. An ontology-based while helping instil confidence models. The implemented study helps tap their form expert opinions using are then used learn about transform incorporating features were included earlier transformed help us which knowledge, discovered through our pilot implementation.

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ژورنال

عنوان ژورنال: Robotics and Computer-integrated Manufacturing

سال: 2023

ISSN: ['1879-2537', '0736-5845']

DOI: https://doi.org/10.1016/j.rcim.2022.102428