A Comprehensive Analysis of Surface Roughness, Vibration, and Acoustic Emissions Based on Machine Learning during Hard Turning of AISI 4140 Steel

Asiltürk, İlhan; Kuntoğlu, Mustafa; Binali, Rüstem; Akkuş, Harun; Salur, Emin

doi:10.3390/met13020437

Cited by 11 publications

(3 citation statements)

References 31 publications

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“…Furthermore, for the evaluation of flank wear of small-diameter drill bits, deep-feature-distribution modelling (a method for image-level anomaly detection and anomaly segmentation in time-series signal analysis) has been proposed by Nakano et al [33]. In addition to these reports, studies on AE sensing by using AI, machine learning, or deep learning are also being actively conducted [34][35][36][37]. Consequently, AE sensing studies are becoming increasingly complex.…”

Section: Introductionmentioning

confidence: 99%

In Situ Measurement of the Machining State in Small-Diameter Drilling by Acoustic Emission Sensing

Hase

2024

Preprint

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In drilling small holes with diameters of 1 mm or less, minute clogging and twining of chips or adhesion of the workpiece material can become factors in causing breakages of the drill bit; moreover, it can be difficult to identify the machining state. Acoustic emission (AE) sensing is a nondestructive inspection technique that measures the elastic-stress waves that are generated when a material is deformed and fractured. AE sensing permits highly sensitive measurements to be made without changing the rigidity of the experimental system, unlike force sensing of cutting resistance, etc. In the present study, attempts were made to identify the machining state and tool wear, and to predict abnormalities in small-diameter drilling by using the change in the frequency of AE signal waveforms arising from deformation and fracture. It was shown that it is possible to predict the breakage of the drill bit by detecting the high-frequency AE signals caused by adhesion. In addition, a correlation map of the AE frequency spectrum for identifying the machining state in a drilling operation is suggested.

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Section: Introductionmentioning

confidence: 99%

In Situ Measurement of the Machining State in Small-Diameter Drilling by Acoustic Emission Sensing

Hase

2024

Preprint

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“…In addition, the analysis of variance (ANOVA) showed that cutting speed has a significant effect on power consumption. Asiltürk et al [7] measured the surface roughness, vibration, and acoustic emission values, which were measured after turning experiments of AISI 4140 steel on a CNC machine. A rule-based fuzzy logic model was created using MATLAB program, after which the fuzzy model results were compared with experimental ones, which showed that the rule-based fuzzy logic model is quite successful.…”

Section: Introductionmentioning

confidence: 99%

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron

Rayes

Abbas

Al-Abduljabbar

et al. 2023

Metals

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This paper investigated the influence of cutting parameters, including feed rate, cutting speed, tool nose radius, and wet or dry cutting conditions, on the resultant force, cutting edge/workpiece temperature, and surface roughness when turning grey cast iron. Results showed that increasing the feed rate increased the resultant force, cutting temperature, and surface roughness. At the same time, increasing the cutting speed and nose radius increased the cutting temperature, which in turn reduced the resultant force. For practical applications, basic mathematical calculations based on the sole effect of each parameter on the output of the experiments were used to estimate the extent of percentage increase in cutting temperature due to increasing feed rate, cutting speed, and nose radius. Similarly, the same approach was used to estimate the effect of increasing feed rate, cutting speed, and nose radius on average surface roughness. Results showed that increasing the feed rate increases the cutting temperature by 5 to 11% depending on the nose radius and cutting speed. On the other hand, increasing the cutting speed was found to have limited effect on cutting temperature with small nose radius whereas this effect increases with increasing the nose radius reaching about 11%. Increasing the nose radius also increases the cutting temperature, depending mainly on cutting speed, reaching a maximum of 21% at higher cutting speeds. Results also showed that increasing the feed rate increased the average surface roughness considerably to about 120% at high cutting speeds and a large nose radius. On the other hand, increasing the cutting speed and nose radius reduced the surface roughness (i.e., improved surface quality) by a maximum of 29 and 23%, respectively. In order to study the combined effects of the cutting parameters on the three responses, namely, the resultant cutting force, cutting temperature, and surface roughness, full factorial design and ANOVA were used, where it was found to be in good agreement with mathematical calculations. Additionally, the desirability function optimization tool was used to minimize the measured responses whilst maximizing the material removal rate.

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“…The problem of the intense wear of the cutting edge under increased mechanical and thermal loads during cutting is well known [1][2][3]. Many scientists have devoted their research to the effect of microtexturing on the performance and operational life of cutting tools [4,5].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Mechanical and Thermal Loads and Microtexturing of Ceramic Cutting Inserts in Turning a Nickel-Based Alloy

Волосова

Okunkova

Hamdy

et al. 2023

Metals

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This paper is devoted to the problem of wear resistance in square Si3N4 ceramic cutting inserts, which exhibit high hardness and strength, in combination with brittleness, in machining super alloys (e.g., a nickel-based alloy of Inconel 718 type) for aviation purposes, when subjected to increased mechanical and thermal loads. Microtextures were proposed to reduce the intensity of the contact loads on the pad between the cutting edge and the workpiece. The simulation of the mechanical and thermal loads demonstrated the superior ability of the faces with the preformed microgrooves (125 µm in width) compared to microwells (ø100 µm). The tense state was 4.97 times less, and there were 2.96 times fewer deformations. It was shown that they hamper the development of thermal fields at 900 °C. Two types of microtextures (210 µm-wide microgrooves and microwells 80 µm in diameter) were produced on the rake faces of the cutting inserts via an innovative and integrated approach (the electrical discharge machining of dielectrics using multifunctional and TiO2-assisted powder), and a conductive and wear-resistant TiN coating was deposited via magnetron vacuum plasma sputtering (95%N2/5%Ar). The failure criterion in turning was 400 µm. An increase of 30% in tool wear resistance was demonstrated.

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A Comprehensive Analysis of Surface Roughness, Vibration, and Acoustic Emissions Based on Machine Learning during Hard Turning of AISI 4140 Steel

Cited by 11 publications

References 31 publications

In Situ Measurement of the Machining State in Small-Diameter Drilling by Acoustic Emission Sensing

In Situ Measurement of the Machining State in Small-Diameter Drilling by Acoustic Emission Sensing

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron

Simulation of Mechanical and Thermal Loads and Microtexturing of Ceramic Cutting Inserts in Turning a Nickel-Based Alloy

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