2019
DOI: 10.3390/ma12101674
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Comparison of Laser Milling Performance against Difficult-To-Cut Alloys: Parametric Significance, Modeling and Optimization for Targeted Material Removal

Abstract: During laser milling, the objective is not always to maximize the material removal rate (MRR). Milling of new material with targeted MRR is challenging without prior knowledge and established sets of laser parameters. The laser milling performance has been evaluated for three important aerospace alloys, i.e., titanium alloy, nickel alloy and aluminum alloy using the response surface method experimental plan (54 experiments for each alloy). Parametric effects of five important laser parameters, statistical anal… Show more

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Cited by 8 publications
(4 citation statements)
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“…The composite desirability of each response based on the optimization criteria is indicated in Table 12. It can be noticed that the composite desirability for each measured property at optimal setting is far over 0.7, which is regarded as a qualifying requirement for a good prediction and optimality search (Ahmed, et al , 2019). Thus, by using the recommended optimum parameters, an enormous amount of searching for suitable parametric combinations and unnecessary experiments may be avoided.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The composite desirability of each response based on the optimization criteria is indicated in Table 12. It can be noticed that the composite desirability for each measured property at optimal setting is far over 0.7, which is regarded as a qualifying requirement for a good prediction and optimality search (Ahmed, et al , 2019). Thus, by using the recommended optimum parameters, an enormous amount of searching for suitable parametric combinations and unnecessary experiments may be avoided.…”
Section: Resultsmentioning
confidence: 99%
“…The prime importance of SLM is governed by its ease of fabrication toward the custom-designed complex parts with near-zero wastage. Several phenomenon occurs during SLM such as heat transfer, laser absorption and scattering, chemical reactions, evaporation, phase transformation and fluid dynamics within the melt pool (Ninpetch et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…Finally, it is worth mentioning the employment of techniques based on the DOE and regression techniques that have also been widely used for the study of technological variables found in manufacturing processes as shown in research studies such as that of Airao et al [54] which analyzed the effect of cutting speed, feed rate, and axial depth of cut on surface roughness obtained in end-milling of a stainless steel, that of Kasdekara et al [55], which employed a 2 4 full factorial (DOE) for determining the most important factors which influence MRR in Electro-chemical machining of AA6061 by using MLP and regression, and that of Ahmed et al [56] in which the MRR, in laser milling of three alloys (Ti6Al4V, Inconel 718 and AA 2024), was evaluated using the response surface method and DOE. On the other hand, Aslantas et al [57] obtained empirical relations between cutting speed, feed rate, depth of cut and surface roughness parameters using the RSM for the micro-turning process in a Ti6Al4V alloy and Su et al [58] employed a multi-objective optimization method based on grey relational analysis and RSM along with Taguchi method for analyzing surface roughness and MRR in turning of an AISI 304 austenitic stainless steel.…”
Section: State Of the Artmentioning
confidence: 99%
“…Along with different process parameters, significant effects of material properties such as thermophysical and optical properties on the laser machining performance have been reported in previous studies. Ahmed et al [16] illustrated the effect of input variables such as scanning speed and laser intensity for laser milling operation on alloys of titanium(Ti6Al4V), nickel(Inconel 718) and aluminum (AA 2024). They concluded that material properties such as thermal conductivity and emissivity are chief contributors to the difference in the value of MRR for the same machining parameters.…”
Section: Introductionmentioning
confidence: 99%