Mono-objective and multi-objective optimization of performance parameters in high pressure coolant assisted turning of Ti-6Al-4V

Mia, Mozammel; Khan, Awal; Rahman, Saadman Sakib; Dhar, Nikhil Ranjan

doi:10.1007/s00170-016-9372-z

Cited by 73 publications

(33 citation statements)

References 32 publications

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“…Mia et al [25] optimized cutting forces, surface roughness, cutting temperature, and chip reduction coefficient when turning of Ti-6Al-4V in dry and high-pressure coolant condition using GRA combined with the Taguchi method. In their next paper [26] they experimentally investigated surface roughness, cutting force, and feed force when turning the same workpiece material under cryogenic (liquid nitrogen) condition. They performed multiresponse optimization according to the models of responses by response surface methodology (RSM) and artificial neural network.…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis and Optimization of the Controllable Parameters in Turning of en Aw-2011 Alloy; Dry Machining and Alternative Cooling Techniques

2020

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The latest trends in machining research show that great efforts are being made to understand the impact of different cooling and lubrication techniques as well as cutting parameters on machining performances. This paper presents the investigation results of different cutting parameters and different cutting environments such as dry machining, minimum quantity lubrication (MQL) and minimum quantity lubrication with compressed cold air (MQL+CCA) on average surface roughness, cutting force and material removal rate. The experiments were designed based on three input parameters and three different cutting environments when turning of EN AW-2011 alloy. Taguchi-based grey relational analysis was used to identify the optimal process parameters by which minimum values of surface roughness, minimum value of cutting force and maximum value of material removal rate will be achieved. The results showed that minimum quantity lubrication in the stream of compressed cold air, in comparison to dry and minimum quantity lubrication machining, gives the best machining performances. Therefore, the use of MQL + CCA method, which reduces the amount of lubricant may represent in the described extent of turning operations an alternative to turning processes most often carried out by wet method that causes considerable costs for purchasing, maintaining and using cutting fluids.

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Section: Introductionmentioning

confidence: 99%

Experimental Analysis and Optimization of the Controllable Parameters in Turning of en Aw-2011 Alloy; Dry Machining and Alternative Cooling Techniques

2020

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“…It reduces complex multi-objective objective problems into a single object effectively and efficiently. Mia et al [27] successfully employed a GRA method to optimize the cutting force and surface roughness in end milling under MQL conditions. On the other side, Deb et al [28] proposed a fast and elitist heuristic method know as Non-dominated Sorting Genetic Algorithm NSGA-II; researchers have been successfully using the NSGA II to optimize machining parameters.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Energy Consumption and Surface Quality in Nanofluid SQCL Assisted Face Milling

et al. 2019

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Considering the significance of improving the energy efficiency, surface quality and material removal quantity of machining processes, the present study is conducted in the form of an experimental investigation and a multi-objective optimization. The experiments were conducted by face milling AISI 1045 steel on a Computer Numerical Controlled (CNC) milling machine using a carbide cutting tool. The Cu-nano-fluid, dispersed in distilled water, was impinged in small quantity cooling lubrication (SQCL) spray applied to the cutting zone. The data of surface roughness and active cutting energy were measured while the material removal rate was calculated. A multi-objective optimization was performed by the integration of the Taguchi method, Grey Relational Analysis (GRA), and the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The optimum results calculated were a cutting speed of 1200 rev/min, a feed rate of 320 mm/min, a depth of cut of 0.5 mm, and a width of cut of 15 mm. It was also endowed with a 20.7% reduction in energy consumption. Furthermore, the use of SQCL promoted sustainable manufacturing. The novelty of the work is in reducing energy consumption under nano fluid assisted machining while paying adequate attention to material removal quantity and the product’s surface quality.

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“…To obtain favorable performance characteristics such as material removal rate, cutting force, and surface roughness during dry turning of AISI 304 austenitic stainless steel, Nayak et al [19] combined Taguchi method and GRA to optimize the machining parameters such as cutting speed, feed rate, and depth of cut. Mia et al [20] first attempted to optimize cutting forces, surface roughness, cutting temperature, and chip reduction coefficient during turning of Ti-6Al-4V under dry and high-pressure coolant using GRA integrated with Taguchi method. Afterwards, they experimentally investigated surface roughness, cutting force, and feed force during turning of Ti-6Al-4V under cryogenic (liquid nitrogen) condition and performed the desirabilitybased multi-response optimization according to the models of responses by RSM and artificial neural network [21].…”

Section: Introductionmentioning

confidence: 99%

Multi-response optimization of Ti-6Al-4V turning operations using Taguchi-based grey relational analysis coupled with kernel principal component analysis

Yong-jie

Kong

2019

Adv. Manuf.

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Ti-6Al-4V has a wide range of applications, especially in the aerospace field; however, it is a difficultto-cut material. In order to achieve sustainable machining of Ti-6Al-4V, multiple objectives considering not only economic and technical requirements but also the environmental requirement need to be optimized simultaneously. In this work, the optimization design of process parameters such as type of inserts, feed rate, and depth of cut for Ti-6Al-4V turning under dry condition was investigated experimentally. The major performance indexes chosen to evaluate this sustainable process were radial thrust, cutting power, and coefficient of friction at the toolchip interface. Considering the nonlinearity between the various objectives, grey relational analysis (GRA) was first performed to transform these indexes into the corresponding grey relational coefficients, and then kernel principal component analysis (KPCA) was applied to extract the kernel principal components and determine the corresponding weights which showed their relative importance. Eventually, kernel grey relational grade (KGRG) was proposed as the optimization criterion to identify the optimal combination of process parameters. The results of the range analysis show that the depth of cut has the most significant effect, followed by the feed rate and type of inserts. Confirmation tests clearly show that the modified method combining GRA with KPCA outperforms the traditional GRA method with equal weights and the hybrid method based on GRA and PCA.

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Mono-objective and multi-objective optimization of performance parameters in high pressure coolant assisted turning of Ti-6Al-4V

Cited by 73 publications

References 32 publications

Experimental Analysis and Optimization of the Controllable Parameters in Turning of en Aw-2011 Alloy; Dry Machining and Alternative Cooling Techniques

Experimental Analysis and Optimization of the Controllable Parameters in Turning of en Aw-2011 Alloy; Dry Machining and Alternative Cooling Techniques

Multi-Objective Optimization of Energy Consumption and Surface Quality in Nanofluid SQCL Assisted Face Milling

Multi-response optimization of Ti-6Al-4V turning operations using Taguchi-based grey relational analysis coupled with kernel principal component analysis

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