2011
DOI: 10.4028/www.scientific.net/kem.486.91
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The Investigation of Prediction Surface Roughness from Machining Forces in End Milling Processes

Abstract: Surface roughness is one of the most significant parameters to determine quality of machined parts. Surface roughness is defined as a group of irregular waves in the surface, measured in micrometers (μm). Many investigations have been performed to verify the relationship between surface roughness and cutting parameters such as cutting speed, feed rate and depth of cut. To predict the surface produced by end milling, surface roughness models have been developed in this paper using the machining forces by assumi… Show more

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Cited by 6 publications
(6 citation statements)
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“…Though the off-line prediction models of surface roughness lay foundations for designing the machining parameters, they do not consider the effects of uncertain factors in the machining process on the surface roughness, such as the vibration, chip residue and so on. Therefore, many researchers have focused on constructing the on-line prediction models of the surface roughness with the aids of measured dynamic information such as milling force signals and acceleration signals [15][16][17][18]. García et al [19] proposed two methods for enhancing the surface roughness monitoring, including the individual analysis of principal components and the grouping analysis of correlated principal components, and the grouping analysis of correlated principal components proved to be a more efficient method.…”
Section: Introductionmentioning
confidence: 99%
“…Though the off-line prediction models of surface roughness lay foundations for designing the machining parameters, they do not consider the effects of uncertain factors in the machining process on the surface roughness, such as the vibration, chip residue and so on. Therefore, many researchers have focused on constructing the on-line prediction models of the surface roughness with the aids of measured dynamic information such as milling force signals and acceleration signals [15][16][17][18]. García et al [19] proposed two methods for enhancing the surface roughness monitoring, including the individual analysis of principal components and the grouping analysis of correlated principal components, and the grouping analysis of correlated principal components proved to be a more efficient method.…”
Section: Introductionmentioning
confidence: 99%
“…Then, choosing cutting tools and based on condition of feed, speed, and of cut to machine material could be affected to quality of product especially in this case is surface roughness [2]. Cutting tool as carbide tool is of many tools used for cutting material to have a good quality of surface roughness because it provides better solution for this [3]. Therefore, based on these conditions to have better surface roughness for milling material especially stainless steel, the objectives of this study were to study the factors, which were speed, feed, and coolant affected to surface roughness of milling stainless steel (AISI/SUS 304).…”
Section: Introductionmentioning
confidence: 99%
“…Previous study reported that effect of milling parameters in various process on surface roughness. Such as, the milling operation and factors affected to finished surface of medium carbon steel [2], aluminum [3], cobalt-based alloy [4], titanium alloy [5,6], mold steel [7] and polymer [8].…”
Section: Introductionmentioning
confidence: 99%
“…The previous studies for surface finish of steel such as stainless steel [1], medium carbon steel [2][3] were studied. The others material has been studied such as titanium alloy [4][5], nickel alloy [5][6], aluminum alloy [7] and polymer [8]. They conclude that conditions of milling parameters based on feed rate, cutting speed, and depth of cut could be affecting to surface finish especially in case of steel.…”
Section: Introductionmentioning
confidence: 99%