Experimental investigation of different NN approaches for tool wear prediction based on vision system in turning of AISI 1045 steel

Bagga, Prashant J.; Makhesana, Mayur A.; Bhavsar, Dhrumil L.; Joshi, Jaymin; Jain, Krutik; Patel, Kaushik M.; Oza, Ankit D.; Joshi, Ankita

doi:10.1007/s12008-022-01072-z

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…Although IOC has timeliness and its role in the defense process may be reduced or even lost, for attacking organizations, each attack will last for a long time. Early threat intelligence can be used for early warning and defense in the later stage [11,12]. The time at which each attack organization initiates an attack varies, and the identity information of the attack organization can be inferred from the time.…”

Section: Threat Intelligence Multidimensional Analysis Modelmentioning

confidence: 99%

Research and Design of an Automated Security Event Analysis and Handling Framework Based on Threat Intelligence

Xie,

Liao,

2024

SCPE

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In order to deeply explore and utilize the value of threat intelligence, strengthen research on attack organizations, and grasp the correlation between attack organizations, the author proposes the research and design of an automated security event analysis and handling framework based on threat intelligence. The author extracts the behavioral characteristics of the attack organization based on known APT attacks, and uses the machine learning framework Light GBM to establish a multi classification model to complete the analysis of unknown APT attack organizations. Through the study of multi-dimensional analysis of multi-source threat intelligence, attack organization correlation and judgment, an attack organization correlation and judgment system has been designed and implemented. The system includes six modules: threat intelligence collection module, threat intelligence multi-dimensional analysis module, attack organization fingerprint library module, attack organization correlation module, attack organization analysis module, and user module, providing attack organization correlation and judgment services for network security. The test results show that the intelligence reading and search query function can achieve the reading of various information of attack organizations, and achieve visual display of threat intelligence. The intelligence management function can achieve operations such as adding, deleting, and updating intelligence. The user management function of the system can achieve the management of administrator users and ordinary users. After testing, all functions of the system have been implemented and meet expectations.

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Section: Threat Intelligence Multidimensional Analysis Modelmentioning

confidence: 99%

Research and Design of an Automated Security Event Analysis and Handling Framework Based on Threat Intelligence

Xie,

Liao,

2024

SCPE

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Empirical relationship for fracture energy in machining processes: a FEM-based investigation with AISI 1045 steel

Damahe,

Sumesh,

Ramesh

2023

Int J Interact Des Manuf

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An application of hybrid Taguchi-ANN to predict tool wear for turning EN24 material

Kamble,

Giri,

Makki

et al. 2024

AIP Advances

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This work is an attempt to predict tool wear for turning EN24 material by the hybrid Taguchi-ANN (Taguchi-Artificial Neural Network) method. The objective is to minimize the tool wear. The independent factors are cutting environment, feed rate, depth of cut, nose radius, and tool type. A Spinner numerical control lathe is used to assess performance. As per the Taguchi orthogonal array, 27 experiments are conducted for each value of the uncontrollable factor (spindle vibration). Optimal setting is structured by Taguchi analysis and the response table. The additive model is used to predict the response. Conformity test is carried out to check whether the predicted and experimental values of response are within the range given by the confidence interval. Furthermore, the ANN is used to predict and analyze the tool wear. The result showed that the supremely important parameter is depth of cut and the least important parameter is tool type. The ideal set found is A3, B3, C3, D1, and E3. Through ANN analysis, it is observed that the experimental values are very close to the predicted values of tool wear. The predicted value at optimal setting is 0.0401 mm. The experimental values at optimal setting is 0.0422 mm. In addition, the study showed that when the feed rate and nose radius are both set to high levels and the depth of cut is medium, using an uncoated tungsten carbide tool with minimal lubrication results in the least amount of tool wear.

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Experimental investigation of different NN approaches for tool wear prediction based on vision system in turning of AISI 1045 steel

Cited by 3 publications

References 41 publications

Research and Design of an Automated Security Event Analysis and Handling Framework Based on Threat Intelligence

Research and Design of an Automated Security Event Analysis and Handling Framework Based on Threat Intelligence

Empirical relationship for fracture energy in machining processes: a FEM-based investigation with AISI 1045 steel

An application of hybrid Taguchi-ANN to predict tool wear for turning EN24 material

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