The effect of vibration and cutting zone temperature on surface roughness and tool wear in eco-friendly MQL turning of AISI D2
Onur Özbek,Hamit Saruhan +1 more
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TLDR
In this article, the AISI D2 cold work tool steel, a material widely used in the mold industry, was used as the workpiece and experiments were carried out using two different cutting tool coating types (CVD-chemical vapor deposition and PVD-physical vapor deposition) and three different cutting speeds (60, 90 and 120m/min) at a constant cutting depth (1 mm) and feed rate (0.09Abstract:
Today, developments in technology have gained momentum more than ever, and the need for efficiency in production as well as in the ecological domain has increased significantly. Studies examining dry machining and coolant removal have been superseded by those presenting new cooling and lubrication techniques. The effects on surface roughness directly related to final product quality are being investigated in terms of tool life and employee health. This has resulted in more frequent use of the eco-friendly minimum quantity lubrication (MQL) technique, which has now become a major competitor to dry and coolant machining. In this study, AISI D2 cold work tool steel, a material widely used in the mold industry, was used as the workpiece. Tests were carried out under dry and MQL conditions and the temperature, cutting tool vibration amplitude, tool wear, surface roughness and tool life were evaluated. The experiments were carried out using two different cutting tool coating types (CVD-chemical vapor deposition and PVD-physical vapor deposition) and three different cutting speeds (60, 90 and 120 m/min) at a constant cutting depth (1 mm) and feed rate (0.09 mm/rev). Results revealed that tool wear, cutting temperature and cutting tool vibration amplitude were lower by 23, 25, and 45%, respectively, compared to dry cutting. Because of these improvements, the surface roughness of the workpiece was improved by 89% and tool life was increased by up to 267%.read more
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Tribology of enhanced turning using biolubricants: A comparative assessment
Xiaoming Wang,Changhe Li,Yanbin Zhang,Hafiz Muhammad Ali,Shubham Sharma,Runze Li,Min Yang,Zafar Said,Xin Liu +8 more
TL;DR: In this paper , the cooling lubrication mechanism and technical iteration motivation of minimum quantity lubrication (MQL) were initially analyzed, and a quantized comparative assessment of cutting force, cutting temperature, tool wear, and surface quality under enhanced environmentally friendly lubrication turning, including parts enhanced by nanoparticles, cryogenic medium, ultrasonic vibration, and textured tools, was performed.
Journal ArticleDOI
A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends.
Mustafa Kuntoğlu,Abdullah Aslan,Danil Yurievich Pimenov,Üsame Ali Usca,Emin Salur,Munish Kumar Gupta,Munish Kumar Gupta,Tadeusz Mikolajczyk,Khaled Giasin,Wojciech Kapłonek,Shubham Sharma +10 more
TL;DR: In this paper, the effect of sensorial data on tool wear by considering previous published papers is discussed, and the main aim is to discuss the impact of sensual data on tools' wear and surface roughness.
Journal ArticleDOI
Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning
Mustafa Kuntoğlu,Haci Saglam +1 more
TL;DR: Monitoring of the cutting area with different type of sensors requires confirmation for composing sensor fusion to obtain longer tool life and high-quality product to enable more reliable, robust and consistent machining.
Journal ArticleDOI
Modeling of Cutting Parameters and Tool Geometry for Multi-Criteria Optimization of Surface Roughness and Vibration via Response Surface Methodology in Turning of AISI 5140 Steel
Mustafa Kuntoğlu,Abdullah Aslan,Danil Yurievich Pimenov,Khaled Giasin,Tadeusz Mikolajczyk,Shubham Sharma +5 more
TL;DR: A good agreement between predicted and measured values was obtained with the developed model to predict surface roughness and vibration during turning of AISI 5140 within a 10% error range.
Journal ArticleDOI
Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140.
Mustafa Kuntoğlu,Abdullah Aslan,Haci Saglam,Danil Yurievich Pimenov,Khaled Giasin,Tadeusz Mikolajczyk +5 more
TL;DR: This 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.
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