Modelling and multiresponse optimization for minimizing burr height, thrust force and surface roughness in drilling of ferritic stainless steel

Günay, Mustafa; Meral, Tolga

doi:10.1007/s12046-020-01490-3

Cited by 26 publications

(14 citation statements)

References 27 publications

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“…41 Several authors have reported the applications of techniques for obtaining multi-objective optimization. 42 It is observed from S/N results that for maximizing the MRR and for minimizing NTC, a higher level of both concentration and the applied voltage is preferred, while for minimizing OC and HAZ, lower levels are preferred as they behave differently ( Figures 21,23,24,25).…”

Section: Grey Relational Based Multi-objective Optimizationmentioning

confidence: 96%

“…Consequently, the problem of multi-objective optimization is acquired through GRA that consists of generating grey relational normalized values trailed by obtaining the grey relational coefficients (GRC), and lastly GRGs. The measured responses are normalized in a span of 0-1 based on equations (19) and (20), respectively. 43 The normalization of the responses is classified into two different characteristics based on the objective, that is, "larger-the-better" objectives like MRR, equation ( 19) is employed, and "smaller-the-better" objectives like OC, NTC, and HAZ, equation ( 20) is used…”

Section: Grey Relational Based Multi-objective Optimizationmentioning

confidence: 99%

“…18 It is a well-known fact that parametric optimization becomes important to achieve the optimum combination of variables for controlling the response characteristics especially when they behave differently. 19 Various studies were reported in the utilization of Taguchi's method for optimization and determination of variable contribution. 20 Manna et al 21 also examined the effect of input variables on hole overcut and MRR during micro-hole fabrication on the fiber-reinforced polymer composite.…”

Section: Introductionmentioning

confidence: 99%

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3D finite element modeling and multi-objective optimization for controlling the electrochemical discharge drilling parameters using the tool feed monitoring system

Rajput

Goud

Suri

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Electrochemical discharge machining drilling (ECDD) is acknowledged as a hybrid machining process that employs the thermal erosion and etching action for drilling. Apart from experimental findings, very rare 3D simulation studies have been covered for analyzing the ECDD. In the present investigation, a 3D simulation of the ECDD process is performed to analyze the process based on the finite element method (FEM). The predicted results are found to be in consensus with the experimental results. An increment of 10.79 mg and 5.04 mg in MRR is noticed with the concentration level increase from 10 wt.% to 60 wt.% and voltage level increase from 35V to 55V. However, a maximum error of 12.68% is observed with the FEM method of prediction when compared to experimental results. The simulation study is followed by the multi-objective optimization (Taguchi’s L16) using grey relational analysis (GRA) for controlling the ECDD parameters. The simultaneous numerical and experimental assessment of the process with 3D Gaussian heat distribution using a novel tool feed monitoring system during soda-lime glass machining leads to the article’s novelty. A unique study on a number of tool contacts (NTC) with the work material is performed to minimize it to improve the geometrical characteristics. Material removal rate, overcut, number of tool contacts, and heat-affected zone are picked as response characteristics while tool feed rate, electrolyte concentration, applied voltage, and inter-electrode gap are selected as input variables. GRA optimized variables are obtained as 40V, 10 wt.%, 3 mm/min, and 35 mm with tool feed rate identified as the ascendant input variable having 35.46 percentage contribution.

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Section: Grey Relational Based Multi-objective Optimizationmentioning

confidence: 96%

Section: Grey Relational Based Multi-objective Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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3D finite element modeling and multi-objective optimization for controlling the electrochemical discharge drilling parameters using the tool feed monitoring system

Rajput

Goud

Suri

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Besides, when the optimum parameter levels found via Taguchi optimization methodology are within the range of experiments performed, confirmation tests are not required as declared in Ref. 38. Nevertheless, a confirmation test was performed at T2 = PVD-coated tool, f1 = 0.1 mm/rev and Vc = 75 m/min to support the industrial applicability of the results.…”

Section: Optimization By Grey Relational Analysismentioning

confidence: 99%

Modeling and multiple optimization in face milling of hardfacing welding applied steel: Force, roughness, power

Günay

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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The coating performance for indexable inserts is very important for the main machinability indicators such as energy consumption, cutting force, and surface quality, especially in milling operations. The present study intend to the comprehensive analysis of machining conditions for above mentioned machinability indicators that can be considered most important for sustainability in hard milling of a worn machine part. First, the worn zone of the shearing blade made of X40CrMoV5-1 hot work tool steel was filled with electric arc welding. Then, hard milling experiments were carried out to analyze the performance of different coated carbide inserts in the machining of the hardfacing welded part. Experiments were performed by applying L18 experimental design for invariable cutting depth, three different cutting speed, and feed rate with PVD-AlTiCrN and CVD-TiCN/Al2O3/TiN coated inserts. Machining parameters for the responses namely the resultant force (Fr), surface roughness (Ra), and cutting power (Pc) were simultaneously optimized via applying Taguchi-based grey relationship analysis. Finally, predictive models for the responses were developed by RSM. The results obtained by both coatings shown that the Fr and Ra are mainly influenced by the feed rate, while cutting speed is the parameter that most influenced the Pc. The optimum results with regards to the responses were obtained with the PVD-AlTiCrN coated tool. In the current study, the developed quadratic models and probability graphs indicated that the responses were highly predictable.

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“…Günay et al studied on drilling of AISI 430 ferritic stainless steel in respect of the burr height, thrust force, and surface roughness by using Taguchi method combined with Grey Relational Grade (GRG). Furthermore, the mathematical models were developed for the machining outputs with response surface methodology [15]. Korkmaz et al investigated the drilling process of AISI 420 martensitic stainless steel material in terms of feed force, moment, and tool temperature with the finite element method.…”

Section: Introductionmentioning

confidence: 99%

Experimental Optimization of Drilling Parameters in Tooling for Euro 7 Nozzle Production

KÜÇÜKTÜRK¹,

KÜÇÜKTÜRK²,

Yavaş³

et al. 2021

International Journal of Automotive Science and Technology

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Within the scope of Euro 7 emission norms, new types of injectors and engine parts are produced in order to reduce fuel consumption to minimum levels in diesel engine vehicles and accordingly to reduce emission rates. The complex geometry, high precision and high strength required by the nozzle design that will meet the requirements of the aforementioned norms have made the produc-tion of the required nozzles on existing production platforms difficult and the manufacturers have faced serious problems. Manufacturing companies needed the development of tooling systems suitable for the existing production platform rather than investing in the high-cost machine park. In this study, it is aimed to increase the tool life by choosing the most appropriate machining parameters for the surface quality obtained in the production of a single nozzle, which is de-signed and manufactured using six different tools, which will enable the use of existing machining platforms in the production of Euro 7 nozzles. The average surface roughness value on the nozzle surfaces was determined as Ra = 0.34 µm and it was observed that the desired surface quality was achieved. Performance tests have shown that the design and production activities are successful and that the developed tooling system can be used for the production of Euro 7 Nozzle from existing production platforms.

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Modelling and multiresponse optimization for minimizing burr height, thrust force and surface roughness in drilling of ferritic stainless steel

Cited by 26 publications

References 27 publications

3D finite element modeling and multi-objective optimization for controlling the electrochemical discharge drilling parameters using the tool feed monitoring system

3D finite element modeling and multi-objective optimization for controlling the electrochemical discharge drilling parameters using the tool feed monitoring system

Modeling and multiple optimization in face milling of hardfacing welding applied steel: Force, roughness, power

Experimental Optimization of Drilling Parameters in Tooling for Euro 7 Nozzle Production

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