Experimental study on correlation between turning temperature rise and turning vibration in dry turning on aluminum alloy

Yu, Qin; Li, Shuncai; Xin, Zhang; Shao, M.

doi:10.1007/s00170-019-03506-7

Cited by 19 publications

(14 citation statements)

References 30 publications

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“…The effect of the depth of cut on V B has been investigated [ 22 ], and it has been revealed that with the change in AE signals, the increase in depth of cut affects V B more than cutting speed and feed. Yu et al found that the cutting temperature, which had a huge impact on wear, reached the highest level with an increase in the depth of cut [ 68 ]. Mia et al found that the most effective parameter on V B was the depth of cut [ 69 ].…”

Section: Resultsmentioning

confidence: 99%

“…According to ANOVA results, depth of cut and cutting speed influence V B , while feed rate and depth of cut seem effective on Ra , which is represented in Figure 2 on three-dimensional graphs. V B is directly proportional to the depth of cut for all cutting speed values ( Figure 2 a), which can be understood as an effect of the larger chip cross-section that aggravates chip removal [ 68 ]. Furthermore, the cutting temperature rises with increasing depths of cut, and temperature is accepted as the major trigger of tool wear [ 72 ].…”

Section: Resultsmentioning

confidence: 99%

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Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Kuntoğlu

Aslan

Sağlam

et al. 2020

Sensors

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Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%).

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Kuntoğlu

Aslan

Sağlam

et al. 2020

Sensors

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“…In another study which supported these evaluations belonging to [48], the effect of depth of cut on temperature and TW was investigated, and they reported that depth of cut was the dominant cutting parameter rather than cutting speed and feed rate. There were other studies [62,67] which indicated the most important parameters were depth of cut on the temperature increase and TW progression. In [31,39,48,[61][62][63][64][65][66][67][68], it was reported that a correlation between cutting temperature and TW was found, mostly triggered by cutting conditions and cutting speed.…”

Section: Temperaturementioning

confidence: 99%

“…There were other studies [62,67] which indicated the most important parameters were depth of cut on the temperature increase and TW progression. In [31,39,48,[61][62][63][64][65][66][67][68], it was reported that a correlation between cutting temperature and TW was found, mostly triggered by cutting conditions and cutting speed. Temperature based measurement provided significant contribution for detecting TW progress and El Hakim et al [39] indicated that in hard turning of high alloy steel with secondary hardening operation, temperature and flank TW demonstrated an increasing trend.…”

Section: Temperaturementioning

confidence: 99%

Section: Indirect Tool Condition Monitoring Systemsmentioning

confidence: 99%

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A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends

Kuntoğlu

Aslan

Pimenov

et al. 2020

Sensors

192

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The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0.

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Experimental study on coupling characteristics of cutting temperature rise and cutting vibration under different tool wear states

et al. 2021

Int J Adv Manuf Technol

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Experimental study on correlation between turning temperature rise and turning vibration in dry turning on aluminum alloy

Cited by 19 publications

References 30 publications

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends

Experimental study on coupling characteristics of cutting temperature rise and cutting vibration under different tool wear states

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