ANOVA and fuzzy rule based evaluation and estimation of flank wear, temperature and acoustic emission in turning

Kuntoğlu, Mustafa; Sağlam, Hacı

doi:10.1016/j.cirpj.2021.07.011

Cited by 35 publications

(9 citation statements)

References 59 publications

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“…A detailed explanation about the procedure of the practice of this method was given in the previous works of the author. 83,84 Figure 15 was prepared to show the percent contribution of the parameters along with F values and p -values for the representation of the parameter influences. Statistical analysis was carried out in 95% confidence interval which shows the significance of a parameter if the p -value is lower than 0.05 values.…”

Section: Resultsmentioning

confidence: 99%

Measurement and analysis of sustainable indicators in machining of Armox 500T armor steel

Kuntoğlu

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Armox 500T is a special type of armor steels possessing superior mechanical properties suitable for use in vehicles and buildings need for first priority protection. Since these products are large-scale, welding groove need to be created before joining which can be done by milling operations. This study aims to address this point by questioning the impact of clean environments namely dry, minimum quantity lubrication (MQL) and LN2 based cryogenic cooling on the machining performance measures during milling. The novelty of this paper is the investigation of the effects of different cutting environments on the milling performance of Armox 500T armor steel. The results from this study showed that cryogenic medium has an impressive impact on controlling the temperatures at tool-chip interface which directly reduces flank wear development. In addition, cryogenic and MQL-assisted machining is much better than dry environment in achieving improved surface properties, chip shape and energy consumptions. Cryogenic cooling seems as the best option for hard milling pursued by MQL and dry environments respectively from the sustainability and machinability point of view.

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Section: Resultsmentioning

confidence: 99%

Measurement and analysis of sustainable indicators in machining of Armox 500T armor steel

Kuntoğlu

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Thus, peak current

, pulse on time

, porosity

, and voltage are the most significant parameters for the MRR response. The accuracy and validation of the developed statistical models are further examined by finding the coefficient of determination (R-Sq) for MRR values [ 29 ]. The analysis of variance given R-Sq for the MRR response is 94.76%, as shown in Table 6 .…”

Section: Resultsmentioning

confidence: 99%

Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques

et al. 2022

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Electric discharge machining is an essential modern manufacturing process employed to machine porous sintered metals. The sintered 316L porous stainless steel (PSS) components are widely used in diverse engineering domains, as interconnected pores are present. The PSS material has excellent lightweight and damping properties and superior mechanical and metallurgical properties. However, conventional machining techniques are not suitable for porous metals machining. Such techniques tend to block the micro-pores, resulting in a decrease in porous materials’ breathability. Thus, the EDM process is an effective technique for porous metal machining. The input process parameters selected in this study are peak current (Ip), pulse on time (Ton), voltage (V), flushing pressure (fp), and porosity. The response parameters selected are material removal rate (MRR) and tool wear rate (TWR). The present work aims to obtain optimum machining process parameters in the EDM of porous sintered SS316L using two meta-heuristic optimization techniques, i.e., Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithms, to maximize the MRR and minimize the TWR values. In the case of PSS having a 12.60% porosity value, PSO and TLBO algorithms give same optimum machining parameters. However, for PSS having an 18.85% porosity value, the PSO algorithm improves by about 5.25% in MRR and by 5.63% in TWR over the TLBO. In the case of PSS having a 31.11% porosity value, the PSO algorithm improves about 3.73% in MRR and 6.46% in TWR over the TLBO. The PSO algorithm is found to be consistent and to converge more quickly, taking minimal computational time and effort compared to the TLBO algorithm. The present study’s findings contribute valuable information in regulating the EDM performance in machining porous SS316L.

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“…After the experiments, ANOVA-based statistical analysis and Taguchi S/N ratio-based optimization were carried out using Minitab 16 software (Philadelphia, PA, USA). Since the Taguchi-based design and analysis is reliable and preferred for assessing machinability, it was selected in this study for modeling and optimization [33].…”

Section: Experimental Design Optimization Approach and Statistical Analysismentioning

confidence: 99%

The Effects of MQL and Dry Environments on Tool Wear, Cutting Temperature, and Power Consumption during End Milling of AISI 1040 Steel

Salur

Kuntoğlu

Aslan

et al. 2021

Metals

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Minimum quantity lubrication (MQL) is a sustainable method that has been efficiently applied to achieve machinability improvements with various materials in recent years, such as hardened steels, superalloys, soft metals, and composites. This study is the first to focus on the performance evaluation of MQL and dry milling environments with AISI 1040 steel. The tool wear, cutting temperature, and power consumption were considered as the quality responses while cutting speed, feed rate and machining environment are taken as input parameters. The effects of the influential factors are analyzed using analysis of variance (ANOVA) and bar charts. Additionally, Taguchi signal-to-noise (S/N) ratios are utilized in order to determine the optimum parameters for the best quality responses. The results show that the MQL system provides better performance compared to dry milling by reducing the tool wear, cutting temperature, and power consumption. According to the ANOVA results, the cutting environment affects the cutting temperature (37%) and power consumption (94%), while cutting speed has importance effects on the tool wear (74%). A lower cutting speed (100 m/min) and feed rate (0.10 mm/rev) should be selected under MQL conditions to ensure minimum tool wear and power consumption; however, a higher feed rate (0.15 mm/rev) needs to be selected along with a low cutting speed and MQL conditions to ensure better temperatures. A comparative evaluation is carried out on the tool wear, cutting temperature, and power consumption under MQL and dry environments. This investigation is expected to contribute to the current literature, highlighting the superiority of sustainable methods in the milling of industrially important materials.

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ANOVA and fuzzy rule based evaluation and estimation of flank wear, temperature and acoustic emission in turning

Cited by 35 publications

References 59 publications

Measurement and analysis of sustainable indicators in machining of Armox 500T armor steel

Measurement and analysis of sustainable indicators in machining of Armox 500T armor steel

Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques

The Effects of MQL and Dry Environments on Tool Wear, Cutting Temperature, and Power Consumption during End Milling of AISI 1040 Steel

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