Prediction of cutting tool wear during a turning process using artificial intelligence techniques

Marani, Mohsen; Zeinali, Mohammadjavad; Kouam, Jules; Songmené, Victor; Mechefske, Chris K.

doi:10.1007/s00170-020-06144-6

Cited by 36 publications

(14 citation statements)

References 26 publications

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“…The relationship between tool wear and changes in its dynamic properties is well described in the works of V. P. Astakhov [ 12 ], where the correlation of vibrations and temperature with the evolution of the cutting wedge is shown. However, predicting the development of the wedge wear under metal-cutting is quite a difficult task, and thus, intelligent systems and models, which provide assessing the current wear rate by indirect measurable signs, are widely used [ 13 , 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Turning Tool Wear Estimation Based on the Calculated Parameter Values of the Thermodynamic Subsystem of the Cutting System

Lapshin

2021

Materials

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Today, modern metalworking centers are not yet able to reliably assess the degree of wear of the tool used in metal cutting. Despite the fact that a large number of methods for monitoring the service life of the tool have been developed, this issue still remains a difficult task that needs to be solved. Idea: The article proposes a new, previously unused method for estimating the power of a cutting wedge in metalworking. The aim of the study is to develop a method for indirectly estimating the tool wear rate based on a consistent model of intersystem communication that describes the force, thermal and vibration reactions of the cutting process to the shaping movements of the tool. Research methods: The study consists of experiments on a measuring stand and a homemade measuring complex. It also uses the Matlab mathematical software package for processing and graphical interpretation of data obtained during experiments. The results show that the proposed method of estimating the current tool wear is applicable for the interpretation of experimental data. Statistically, the modified Voltaire operator of the second kind models the temperature more accurately; at the peak, this method is three times more accurate than the other.

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Section: Introductionmentioning

confidence: 99%

Turning Tool Wear Estimation Based on the Calculated Parameter Values of the Thermodynamic Subsystem of the Cutting System

Lapshin

2021

Materials

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“…As a result of the lower SSE, the twohidden-layer networks were chosen, with an RMSE of 2.64 percent on average. e ANFIS models-sigmoidal, triangular, Gaussian, and bell-shaped MFs-were used [59]. e most accurate model was sigmoidal MF, which had a regression coefficient of 0.96775.…”

Section: Accuracies Achieved In Recent Researchmentioning

confidence: 99%

A Cutting‐Edge Survey of Tribological Behavior Evaluation Using Artificial and Computational Intelligence Models

Selvaraj

Raj

Dharnidharka

et al. 2021

Advances in Materials Science and Engineering

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Any metal surface’s usefulness is essential in various applications such as machining and welding and aerospace and aerodynamic applications. There is a great deal of wear in metals, used widely in machines and appliances. The gradual loss of the upper metal layers in all metal parts is inevitable over the machine or component’s lifetime. Artificial intelligence implementations and computational models are being studied to evaluate different metals’ tribological behavior, as technological progress has been made in this field. Different neural networks were used for different metals. They are classified in this paper, together with a description of their benefits and inconveniences and an overview and use of the different types of wear. Artificial intelligence is a relatively new term that uses mechanical engineering. There is still no scientific progress to examine various metal wear cases and compare AI and computational models’ accuracy in wear behavior.

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“…In general, a purely theoretical approach to the phenomenon of contact surfaces wear, with relative motion, is difficult, although not impossible, to model [ 1 , 2 , 3 ]. In the work process of dental milling cutters, the wear phenomenon is closer to the process of milling by cutting metals, at least until appreciable wear of the active side of the dental milling cutter.…”

Section: Introductionmentioning

confidence: 99%

“…Several mathematical models of analysis of the wear phenomenon of the active side of metalworking instruments exist, presented by Olt et al [ 8 ] and Chinchanikar et al [ 11 ], namely the abrasive model, for steels covered with carbide and low carbon content [ 15 ]; the diffusive model, for the material (C-45 steel) of high-velocity milling cutters (HSS) [ 1 ]; the Taylor equation model, adapted for estimating tool life [ 16 ]; the diffusive–adhesive model, for carbide-coated alloy steels and low carbon content [ 17 ]; and the deterministic differential model, for the work process of dental milling cutters [ 11 ]. Thus, the deterministic differential model was used in this paper.…”

Section: Introductionmentioning

confidence: 99%

Study of Wear Phenomenon of a Dental Milling Cutter by Statistical–Mathematical Modeling Based on the Experimental Results

2022

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The wear phenomenon of a dental milling cutter is studied based on experimental results and data and validated by statistical–mathematical modeling. The results of the statistical–mathematical modeling by the interpolation of the experimental results (data) regarding the wear of the dental milling cutter analyzed and obtained in the work process are presented in this paper. These results (data) are important because they lead to polynomial functions which by interpolation approximate very well the dependent parameter, specifically the wear process (mass lost due to dental milling cutter wear, mw), considered in the experimental program. The polynomial interpolation functions are valid, only during the experimental testing range of the dental milling cutter, to describe the wear phenomenon; the extrapolations do not lead to satisfactory results. However, by using a controlled interpolation function with an exponential component, the extrapolation of the results is possible. Therefore, the purpose of this paper is the statistical–mathematical modeling by the interpolation of the experimental results of the mass lost due to dental milling cutter wear, mw, using the deterministic differential model for the work process of it. Thus, interesting conclusions can be drawn relating to the phenomenon. In support of these statements come the results of the statistical–mathematical modeling by the interpolation of the experimental data obtained in the work process of the dental milling cutters, leading to practical applications, such as the extension of the life of dental milling cutter, useful even for its operation optimization; determination of possible criteria for replacing the worn dental milling cutters; the extension of the life of the materials from which dental milling cutters are built; or the provision of ideas for constructive solutions. Based on the modeling results by interpolation, it was found that the dental milling cutter during the milling operation works with high efficiency (mass loss due to wear is very reduced) in the first 11 h of operation, i.e., about a 10% increase in lifetime. After 11 h of operation, mass loss due to wear of the dental milling cutter increases relatively exponentially; thus, it is recommended that, in the normal way, the dental milling cutter be replaced with a new one to ensure high standards of materials processing.

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Prediction of cutting tool wear during a turning process using artificial intelligence techniques

Cited by 36 publications

References 26 publications

Turning Tool Wear Estimation Based on the Calculated Parameter Values of the Thermodynamic Subsystem of the Cutting System

Turning Tool Wear Estimation Based on the Calculated Parameter Values of the Thermodynamic Subsystem of the Cutting System

A Cutting‐Edge Survey of Tribological Behavior Evaluation Using Artificial and Computational Intelligence Models

Study of Wear Phenomenon of a Dental Milling Cutter by Statistical–Mathematical Modeling Based on the Experimental Results

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