Online measuring method of the axial section line in ring forging process

Wang, Ying; Wang, Yongjie; Zhang, Yucun; Fu, Xiang

doi:10.1049/iet-smt.2017.0327

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“…It will give a good analysis of causes of forging. Figure 2 represents the identification of defect in forging process [17,18].…”

Section: Problem Statementmentioning

confidence: 99%

Smart Diagnostic Expert System for Defect in Forging Process by Using Machine Learning Process

Mewada

Saroliya²,

Chandramouli³

et al. 2022

Journal of Nanomaterials

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Integrating machine learning into one of the manufacturing processes, i.e., forging, is mainly concerned with making the system more intelligent by incorporating them to exhibit global understanding. Sometimes the engineer/operator can find the defects during or after the forging operation. So, the system will need some input to identify the different types of categorized defects. And also, according to that, we will develop the intelligent fault diagnosis process. We should calculate the statistical probability theory. Now, we implement the system which is the structure of the fault analysis system for the forging process. In the structure, we demonstrate the defect of the forged part, use the given imported probability to find the possible causes, and provide some remainders to reduce the fault. For enhancement of feature needs, this work includes more integration of AI with forging.

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“…It will give a good analysis of causes of forging. Figure 2 represents the identification of defect in forging process [17,18].…”

Section: Problem Statementmentioning

confidence: 99%