Effect of machining parameters on surface roughness in end milling of AISI 1019 steel

Bhardwaj, Bhuvnesh; Kumar, Rajesh; Singh, Premlata

doi:10.1177/0954405413506417

Cited by 33 publications

(18 citation statements)

References 22 publications

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“…Enhancing technical outputs of the milling processes using optimal parameters has been widely analyzed in works published. Former researchers have attempted to minimize the surface roughness for the machining process of stainless 316 [3], AISI 1019 [4], and EN 353 material [5]. Similarly, cutting parameters were optimized in an effort to decrease the roughness value in the milling processes of Al alloy [6][7][8], SKD61 [9], and AISI H13 [10].…”

Section: Introductionmentioning

confidence: 99%

Optimization Parameters of Milling Process of Mould Material for Decreasing Machining Power and Surface Roughness Criteria

et al. 2019

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Improving milling performances is an effective solution to decrease the costs required. This paper addressed a multi-response optimization to simultaneously decrease the machining power consumed Pm, arithmetical roughness Ra, and ten-spot roughness Rz. The Grey-Response Surface Method-Multi Island Genetic Algorithm (GRMA) consisting of grey relational analysis (GRA), response surface method (RSM), and multi-island genetic algorithm (MA) was proposed to predict the optimal parameters and yield optimum milling performances. The experimental trials were conducted with the support of a CNC milling center. The influences of spindle speed (S), depth of cut (ap), feed rate (fz), and tip radius (r) were explored using GRA. The nonlinear relationship between machining parameters and grey grade (GG) model was developed using RSM. Finally, two optimization techniques, including desirability approach (DA) and MA were performed to observe the optimal values. The results indicated that the machining power was greatly affected by processing factors and the radius has a significant impact on the roughness criteria. The measured reductions using optimal parameters of Pm, Ra, and Rz are approximately 77.05%, 50.00%, and 58.02%, respectively, as compared to initial settings. The GRMA can be considered as an effective approach to generate reliable values of processing conditions and technological performances in the milling process.

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Section: Introductionmentioning

confidence: 99%

Optimization Parameters of Milling Process of Mould Material for Decreasing Machining Power and Surface Roughness Criteria

et al. 2019

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“…Increasing energy saving potentials and machined part quality using optimal parameters has been considered by many researchers. Bhardwaj et al examined the impacts of machining parameters on the surface roughness for the end milling of AISI 1019 steel [1] and EN 353 material [2]. A predictive model was proposed to forecast the surface quality of the end milling of stainless steel [3].…”

Section: Introductionmentioning

confidence: 99%

Optimization of milling process parameters for energy saving and surface roughness

Pham¹,

Dang²,

Doan³

et al. 2019

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Improving the technical parameters of the machining process is an effective solution to save manufacturing costs. The purpose of this work is to decrease energy consumption (EC) and average surface roughness(ASR) for the milling process of AISI H13 steel. The spindle speed (S), depth of cut (a), and feed rate (f) were the processing inputs. The milling runs were performed using the experimental plan generated by the Box-Behnken method approach. The relationships between inputs and outputs were established using the response surface models (RSM). The desirability approach (DA) was used to observe the optimal values. The results showed that the reductions of EC and ASR are approximately 33.75% and 40.58%, respectively, as compared to the initial parameter setting. In addition, a hybrid approach using RSM and DA can be considered as a powerful solution to model the milling process and obtain a reliable optimal solution.

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“…Bhardwaj et al 17 investigated surface roughness in end milling operation using carbide inserts on AISI 1019 steel. The work focused on establishing empirical relationships between the machining parameters and average surface roughness using RSM.…”

Section: Introductionmentioning

confidence: 99%

Effect of equal-channel angular pressing on the surface roughness of commercial purity aluminum during turning operation

Abbas

Ragab

El‐Danaf

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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Aluminum has been increasingly used in automotive and aerospace applications due to its beneficial specific strength and chemical properties. Due to its extensive use, machining of aluminum parts has become specifically significant in recent years. One important aspect of machining is the surface quality represented by the surface roughness values. In this article, the effect of equal-channel angular pressing on the surface roughness (R a , R q , R t and R z) of commercial purity aluminum machined by turning was studied. Five starting material conditions, defined as the annealed and equal-channel angular pressing processed up to four passes, were investigated. The independent variables were the cutting speed, depth of cut and feed rate. The fourth parameter (number of equal-channel angular pressing passes) was considered as categorical factor and, hence, was not included in the mathematical model. A full central composite circumscribed design matrix was built to allow the optimization of surface roughness using response surface methodology. The significance of process parameters and their interactions in estimating surface roughness was investigated using analysis of variance. The two parameters, with significant effect on surface roughness, were found to be the feed rate and number of equalchannel angular pressing passes. Minimum depth of cut (0.15 mm) and minimum feed rate (0.05 mm/rev) are needed to achieve minimum surface roughness parameters: R a (0.06 mm), R q (0.057 mm) and R z (0.71 mm) and R t (1.2 mm). The cutting speed, for these optimum roughness values, ranged from 207.5 m/min for R a to 193 m/min for R z. The optimum roughness values were generally achieved with the higher strength materials. Optimum values for R a , R q and R z happened at the four equal-channel angular pressing passes-processed material, while the optimum value of R t happened at the three equal-channel angular pressing passes-processed material.

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Effect of machining parameters on surface roughness in end milling of AISI 1019 steel

Cited by 33 publications

References 22 publications

Optimization Parameters of Milling Process of Mould Material for Decreasing Machining Power and Surface Roughness Criteria

Optimization Parameters of Milling Process of Mould Material for Decreasing Machining Power and Surface Roughness Criteria

Optimization of milling process parameters for energy saving and surface roughness

Effect of equal-channel angular pressing on the surface roughness of commercial purity aluminum during turning operation

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