Geometry and Volume Measurement of Worn Cutting Tools With an Optical Surface Metrology Device

Danzl, Reinhard; Helmli, Franz; Rolland, P.; Scherer, Stefan

doi:10.1002/9780470611371.ch32

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…The operating principle is based on Focus-Variation, which combines the small depth of focus of an optical system with vertical scanning. This technique enables high-resolution measurements of surfaces with strongly varying roughness with steep flanks up to 80° [28,[30][31][32]. The chosen magnification was 20x, with 7 million captured points, each point size being 438 nm, with a unified cut-off wavelength \ c = 200 urn.…”

Section: Surface Characterisationmentioning

confidence: 99%

Laser shock peening without absorbent coating (LSPwC) effect on 3D surface topography and mechanical properties of 6082-T651 Al alloy

Trdan

Porro

Ocaña

et al. 2012

Surface and Coatings Technology

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The influence of nanosecond laser pulses applied by laser shock peening without absorbent coating (LSPwC) with a Q-switched Nd:YAG laser operating at a wavelength of \ = 1064 nm on 6082-T651 Al alloy has been investigated. The first portion of the present study assesses laser shock peening effect at two pulse densities on three-dimensional (3D) surface topography characteristics. In the second part of the study, the peening effect on surface texture orientation and micro-structure modification, i.e. the effect of surface craters due to plasma and shock waves, were investigated in both longitudinal (L) and transverse (T) directions of the laser-beam movement. In the final portion of the study, the changes of mechanical properties were evaluated with a residual stress profile and Vickers micro-hardness through depth variation in the near surface layer, whereas factorial design with a response surface methodology (RSM) was applied. The surface topographic and micro-structural effect of laser shock peening were characterised with optical microscopy, InfiniteFocus® microscopy and scanning electron microscopy (SEM). Residual stress evaluation based on a hole-drilling integral method confirmed higher compression at the near surface layer (33 um) in the transverse direction (Omin) of laser-beam movement, i.e. -407 ±81 MPa and -346 ± 124 MPa, after 900 and 2500 pulses/cm 2 , respectively. Moreover, RSM analysis of micro-hardness through depth distribution confirmed an increase at both pulse densities, whereas LSPwC-generated shock waves showed the impact effect of up to 800 um below the surface. Furthermore, ANOVA results confirmed the insignificant influence of LSPwC treatment direction on micro-hardness distribution indicating essentially homogeneous conditions, in both I and T directions.

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Section: Surface Characterisationmentioning

confidence: 99%

Laser shock peening without absorbent coating (LSPwC) effect on 3D surface topography and mechanical properties of 6082-T651 Al alloy

Trdan

Porro

Ocaña

et al. 2012

Surface and Coatings Technology

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“…Another employed technique is focus variation microscopy, which was introduced by Danzl et al [ 56 ] This approach involves an optical system with a limited depth of field coupled with vertical scanning. A series of images is captured as the optics moves vertically along the optical axis, producing a vertical stack of images.…”

Section: Surface Texture Evaluationmentioning

confidence: 99%

On the Post‐Processing of Complex Additive Manufactured Metallic Parts: A Review

Pourrahimi,

Hof

2024

Adv Eng Mater

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Additive manufacturing (AM) is gaining more attention due to its capability to produce customized and complex geometries. However, one significant drawback of AM is the rough surface finish of the as‐built parts, necessitating post‐processing for achieving the desired surface quality that meets application requirements. Post‐processing of complex geometries, such as parts with internal holes, lattice structures, and free‐form surfaces, poses unique challenges compared to other components. This review classifies various post‐processing methods employed for complex AM parts, presenting the experimental conditions for each treatment alongside the resulting improvement in surface roughness as a success criterion. The post‐processing methods are categorized into four groups: electrochemical polishing (ECP), chemical polishing (CP), mechanical polishing, and hybrid methods. Notably, mechanical methods exhibit the highest roughness improvement at 69.9%, followed by ECP (59.9%), hybrid methods (47.4%), and CP (49.5%). Nevertheless, mechanical post‐processing techniques are less frequently utilized for lattice parts, making chemical or electrochemical methods more promising alternatives. In summary, all four categories of post‐processing methods can improve the internal surfaces quality of AM holes. While mechanical methods offer the most substantial roughness improvement overall, chemical and electrochemical methods show particular potential for addressing the challenges associated with complex geometries.This article is protected by copyright. All rights reserved.

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“…Figures 3 and 4 show Alicona 3D surface topography of the notch surface of the tested specimen for both the nondamaged state and damaged state, respectively. 31,32 In this study, the measured surface topography parameters are the arithmetical mean height (S a ), root-mean-square height (S q ), maximum peak height (S p ), maximum valley depth (S v ), maximum height (S z ), and 10-point height (S z10 ).…”

Section: The Computer-controlled Fatigue Testing Machinementioning

confidence: 99%

Feature selection of surface topography parameters for fatigue‐damage detection using Pearson correlation method and neural network analysis

Alqahtani

Ray

2023

Fatigue Fract Eng Mat Struct

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The global objective of this study was to investigate the best features of the surface topography for fatigue‐damage detection and classification. The presence of the stress concentration in valleys of the surface topography causes a grain slip and a crack initiation at the surface of the machined structure and finally leads to fatigue failures. Therefore, the surface topography has a major influence on the fatigue strength of the machined structure. An optical confocal measurement system (Alicona) was applied to measure six surface topography parameters. In this paper, feature selection using the Pearson correlation method was adopted to select the best surface textures that provide best the neural network (NN) model performance. The NN model is capable of detecting and classifying the damage with an accuracy of up to ∼ 94.4%.

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Geometry and Volume Measurement of Worn Cutting Tools With an Optical Surface Metrology Device

Cited by 5 publications

References 4 publications

Laser shock peening without absorbent coating (LSPwC) effect on 3D surface topography and mechanical properties of 6082-T651 Al alloy

Laser shock peening without absorbent coating (LSPwC) effect on 3D surface topography and mechanical properties of 6082-T651 Al alloy

On the Post‐Processing of Complex Additive Manufactured Metallic Parts: A Review

Feature selection of surface topography parameters for fatigue‐damage detection using Pearson correlation method and neural network analysis

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