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Feature-based characterisation of surface topography and its application
Abstract
This keynote paper gives an overview of emerging technologies of feature-based characterisation, for surface topographies having features. It is complementary to conventional surface characterisation using texture field parameters. An original concept, the feature spectrum is proposed to organise surfaces, in order to help select the appropriate characterisation for different types of surface topographies and to achieve a more direct relationship between characterisation, manufacturing process and surface function. The keynote paper focuses on fundamentals and the state of the art for feature-based characterisation technologies. Applications of feature-based characterisation are illustrated and discussed. Guidelines for future industrial applications are laid out, and considerations for future challenges are addressed.
Surfaces, Micro structure, Feature-based Characterisation.
... Looking at LPBF parts in particular, particle agglomerations, spatter or weld tracks may be of interest [18,19]. ...
... This can be especially interesting when looking into part functionality, like mechanical performance, corrosion resistance or adhesion. ISO 25178 comprises feature parameters specifying various geometric properties of hills and dales, such as roundness, Figure 10.: Material ratio curve aspect ratio, equivalent diameter, projected area or enclosed volume [6,16,18,19,82,92]. ...
... In recent years, feature characterisation became a research topic in regard to metal additive surfaces [18,19,65,[97][98][99][100][101][102][103][104]. Selected work is summarised subsequently. ...
In the past decades, additive manufacturing (AM) has evolved from a rapid prototyping technology to a mature manufacturing process, offering significant advantages for lightweight design and specialized applications. Surface quality is crucial for the qualification of metal AM parts, particularly for load-bearing aerospace applications. Surface quality from a laser powder bed fusion (LPBF) AM process is typically characterised by agglomerations of attached powder particles, spatter, and weld or layer tracks, influenced by material, powder properties, build direction, and other factors. This work aims to provide a more comprehensive understanding and holistic description of LPBF surface quality, its formation, characterisation, and role in part functionality, using novel approaches and advanced optical measurement techniques.
The thesis is divided into three parts: "Measurement and Data Post-processing," "Surface Texture and Mechanical Properties," and "Areal Surface Features."
The first part discusses the application of optical measurements and related challenges for as-built and post-processed LPBF surfaces. Current industry practices use stylus contact measurements yielding 2D profiles, which are inadequate for LPBF's complex surface structures. Areal measurements, such as confocal microscopy and fringe projection, offer better surface coverage, reproducibility, and prevent surface damage. The transition from 2D to 3D parameters and from contact stylus to non-contact optical methods is proposed for comprehensive surface data.
The second part suggests describing AM surfaces in terms of part functionality, introducing surface texture parameters from the material ratio curve for fatigue performance, instead of traditional 2D parameters like Rt and Ra. Parameters like Svk, derived from the surface height distribution, relate well to fatigue failure modes in LPBF parts. Optimised processing parameters can achieve surface and mechanical properties comparable to post-processed and conventionally manufactured parts, potentially eliminating the need for surface post-processing.
The third part focuses on process-related surface texture characterisation, advancing functionality-based descriptions. It proposes using the particle size distribution of the processed metal powder to set pruning thresholds for feature segmentation, instead of ISO 25178's extreme value Sz. A novel approach to feature-based segmentation is developed.
These advancements will make AM more accessible and sustainable, broadening its application across various sectors with specialised functionality requirements.
... Surface topographies can disclose surface function: for example, components in assemblies, thermal and optical effects all interact through their surfaces (Bruzzone et al., 2008). In the article Jiang et al. (2021), a feature spectrum (as seen in Fig. 6) is presented to organize surfaces across a feature axis to help pick the proper topography characterization methodology to find viable surface characterization approaches for a wide range of surface topographies. On the left hand of the spectrum, surfaces having a stochastic character are defined primarily by randomness, whereas surfaces with deterministic features on the right side may have small-scale stochastic aspects but are mostly defined by planned patterns. ...
... Other approaches include the use of Fourier and wavelet transformations. To overcome the challenges of nano-roughness analysis of surface texture, a third-generation wavelet The feature spectrum of surfaces as mentioned in Jiang et al. (2021) model by Jiang and Blunt (2004) was created in the previous decade, in which slight shifts in the input signal can produce huge alterations in the relative distribution of energy between wavelet coefficients at different scales. These investigations leverage continuous wavelet transforms to assess and quantify the complete spectrum of surface topographic signals, including roughness and waviness, with no wavelength discontinuity. ...
In the era of Industry 4.0 and the digital transformation of the manufacturing sector, this article explores the significant potential of machine learning (ML) and deep learning (DL) techniques in evaluating surface roughness—a critical metric of product quality. The integration of edge computing with current computational resources and intelligent sensors has revolutionized the application of AI-driven algorithms in smart manufacturing. It provides real-time data analysis and decision-making capabilities that were unattainable only a decade ago. The research effort intends to improve data-driven decision-making for product quality evaluation by leveraging data integration from manufacturing operations and surface quality measurements. Although a substantial amount of research has been conducted in the related fields, it is still difficult to comprehend and compile all the data on surface roughness research predictive assessment in the form of a process pipeline. This thorough systematic analysis examines scholarly articles published between 2014 and 2024 focusing on surface roughness assessment in precision manufacturing settings. The article is thoroughly classified based on the manufacturing processes, datasets, and ML models used, giving light on the present status, prominent approaches, and existing issues in this sector. A table summarizing the relevant works in this domain providing an easy access to the current trends have been provided. The article not only compiles essential findings and identifies research gaps and similarities in existing methodologies, but it also discusses future research directions and open issues in AI-aided surface roughness evaluation. The critical analysis of the literature reveals a scientific gaps which includes consistent development of benchmarked datasets and making the AI models more explainable using the state-of-the-art explainable AI (XAI) algorithms. The ultimate objective of the article is not only to provide a guide for the practitioners in either of the three domains of AI, manufacturing or surface metrology but also to pave the path for more robust, efficient, and accurate surface quality evaluation processes in production.
... According to the concept proposed in [32], describing "feature spectra" as shown in Figure 12, which serve as a support system for selecting the method of surface characterization, surfaces with a stochastic-deterministic character should be characterized in both 2D and 3D perspectives. The results are assumed to depend on the measurement location-hence the recommendations for multiple repetitions and statistical analysis. ...
... Spectrum of surface features[32]. ...
A study was made of the machinability of NiTi alloy in turning, under conditions resulting in a small cutting layer. The experiment involved cutting with variable feeds ranging from 0.01 to 0.1 mm/rev. The cutting conditions were carefully chosen, considering the rounding radius of the cutting edge. The machined surface was examined and measured in 3D using a confocal microscope and in 2D with a contact profilometer. These measurements were used to estimate hmin, leading to the development of a surface formation model that considers both the lateral material flow due to hmin and the lateral material flow due to altered thermodynamic conditions from the previous blade pass. A method for evaluating the surface and selecting its characteristics was proposed based on analyses derived directly from surface features: PCA (Principal Component Analysis) and EMD (Empirical Mode Decomposition) with the Hilbert transform (Hilbert–Huang transform). PCA analysis facilitated the examination of individual surface component variances, while analysis of the IMF components enabled the assessment of surface component energy combined with instantaneous frequencies.
... FBC is a developing area of surface metrology that focusses around the characterisations of features found in topographical data that has been proven effective at identifying expected features on PBF surfaces [242,243]. This approach varies from conventional methods of surface characterisation, such as surface texture parameters like roughness and waviness, by targeting individual features on the surface. ...
... Spatter features are formed by fully molten gobs of material ejected from the processing area and fallen back onto the surface. FBC methods to identify leftover particles and spatter features have been successfully implemented in previous work, however only from labbased surface topography measurement, i.e. not in-situ [243][244][245]. ...
Metal powder bed fusion systems have been rapidly gaining interest from high-value manufacturing sectors, such as aerospace and biomedical, due to the unique benefits the technology can offer in terms of part design flexibility and bespoke manufacturing. In-process monitoring techniques for metal powder bed fusion have become increasingly popular as the technology continues to mature. However, adequate methods of handling data collected from the manufacturing process have yet to be explored in depth. Due to the large quantities of potential data and the temporal constraints when monitoring the PBF process, automated data interpretation is essential to allow for real time defect detection to be achieved. In this thesis, a novel measurement method for PBF systems is proposed that uses multi-view fringe projection to acquire high-resolution surface topography information of the powder bed. Measurements were made using a mock-up of a commercial powder bed fusion system to assess the system’s accuracy and precision in comparison to conventional single-view fringe projection techniques for the same application. Featured based characterisation methods were applied to the measured topography to extract salient information about spatter and particles with the data being compared against a higher resolution reference measurement (focus variation). Results show that the multi-view system is more accurate, but less precise, than single view fringe projection on a point-by-point basis. The multi-view system also achieves a high degree of surface coverage by using alternate views to access areas not measured by a single camera. Measurements from the multi-view fringe projection system achieved similar reconstruction fidelity to the reference focus variation, in particular at the scales required for the largest targeted features (200 µm size and up). Topography partitioning and feature identification results achieved by feature based characterisation were comparable between fringe projection and focus variation.
... There were many digital filters provided for the extraction of form from the data such as spline [22,23], wavelet [24,25], morphological [26,27], fast Fourier transform (FFTF) [28,29], and many others [30]. Very popular in recent studies is multi-scale characterisation [31][32][33] or analysis based on feature consideration [34,35]. These techniques separate the received raw measured data in various frequencies using different methods, and filters in some cases [36]. ...
... However, this property was received when the ACFs were thresholded. These techniques, and especially their validity, have been widely introduced and considered for surface roughness analysis in many previous studies [35,64,89,90]. ...
Studies of surface topography including processes of measurement and data analysis have an influence on the description of machined parts with their tribological performance. Usually, surface roughness is analysed when a scale-limited (S-L) surface, excluding short (S-) and length (L-) components from the raw measured data, is defined. Errors in the precise definition of the S-L surface can cause the false estimation of detail properties, especially its tribological performance. Errors can arise when the surface contains some burnished details such as oil pockets, dimples, scratches, or, generally, deep or wide features. The validation of proposed methods for S-L surface definition can also affect the accuracy of the ISO 25178 surface topography parameter calculation. It was found that the application of commonly used procedures, available in commercial software (e.g., least-square fitted cylinder element or polynomial planes, regular or robust Gaussian regression, spline, median or fast Fourier transform filters) can be suitable for precise S-L surface definition. However, some additional analyses, based on power spectral densities, autocorrelation function, texture direction graphs, or spectral characterisation, are strongly required. The effect of the definition of the S-L surface on the values of the ISO 25178 parameters was also comprehensively studied. Some proposals of guidance on how to define an appropriate S-L surface with, respectively, an objective evaluation of surface roughness parameters, were also presented.
... According to the Emberger bioclimatic classification, the area exhibits characteristics of an upper sub-humid stage, featuring a fresh and temperate to semi-arid cool climate (Ghazal, 2008). The terrain is distinguished by its complex topography, encompassing intricate networks of topographic formations (Jiang et al., 2021). Elevations within the region vary significantly, ranging from 240 to 1140 m above sea level. ...
This study provides a comprehensive assessment of soil erosion dynamics in the El-Sarout River Watershed, encompassing 598.15 km² within the humid mountainous ecosystems of the eastern Mediterranean. Using the Coordination of Information on the Environment (CORINE) model, integrated with Geographic Information Systems and remote sensing, the research evaluates soil erosion susceptibility across varied landscapes. The CORINE model facilitates the creation of thematic maps essential for understanding soil erosion dynamics, including the Potential Soil Erosion Risk (PSER) and Actual Soil Erosion Risk (ASER) maps. PSER, derived from the Soil Erodibility Index, Erosivity Index, and Slope Index, identifies areas at risk under natural conditions. ASER refines this assessment by incorporating the Land Cover Index, which reflects current land use and management practices. Findings reveal that 18.56% (111.01 km²) of the watershed, particularly in the complex terrain of the southwest and north, faces high erosion risk. Another 11.7% (70.0 km²) exhibits moderate risk, while the majority, 69.74% (417.14 km²), experiences low risk. These results align with field observations of erosion features such as rills and gullies. The study emphasizes the complexity of soil erosion processes, highlighting the interaction between rainfall intensity, vegetation cover, and topography. Contrary to common assumptions, areas with dense vegetation may still be highly susceptible to erosion, particularly in steep regions subject to intense rainfall. The study calls the need for further research to establish negative thresholds for influencing factors and to incorporate rainfall intensity indicators into erosion models, aiming to enhance the precision and efficacy of soil conservation strategies.
... One innovative approach is to use surface features, like e.g. a watershed method with a featurebased strategy to partition scale-limited surfaces into hill or dale segments. The latest version of ISO 25178 includes such feature parameters that describe various geometric properties of these hills and dales [6][7][8][9]. Feature-based characterisation has the potential to obtain a more adequate surface description using physically relevant characteristics. For metal AM surfaces, these inputs may be related to the particle size distribution, melt pool size, welds, or other material-process-related parameters [9,10]. ...
The surface texture of AM parts, particularly those used in load-bearing applications, significantly impacts their fatigue performance. Traditional 2D surface texture characterisation methods, e.g. contact stylus, are inadequate for representing the complex 3D surfaces produced by AM processes like laser powder bed fusion (LPBF). This limitation is highlighted by the inability of standard 2D parameters, such as Ra and Rt, to distinguish between surfaces with different functional behaviours. Consequently, there is a need for novel characterisation methods that consider the unique features of 3D surfaces, e.g. the watershed method for feature-based analysis, which can provide more realistic and relevant data. This work highlights the limitations of 2D and 3D height-based surface texture characterisation. Feature-based options and their potential applications, specifically in the context of metal PBF, are presented.
... The surface roughness of wood is influenced by inherent wood variables like constituent cells [5,6], contents, cell wall density, porosity, and moisture content [7], as well as processing methods, including tool types, knife sharpness, and the operator's expertise [8,9]. Given the complexity of surface textures, characterized by form, waviness, and roughness, accurately conveying surface roughness with a single metric is challenging [10,11]. Researchers have explored various techniques to enhance the surface quality of manufactured parts [12,13]. ...
This study evaluated the effects of planning methods—pushing and pulling—on the surface topographic characteristics of Cedrela sinensis and Korean Paulownia wood boards according to ISO 25178 standards. Surface roughness was assessed using a stylus profilometer (Mitutoyo SJ301) and a 3D Optical Profilometer (VR-6000, Keyence). The parameters measured included arithmetical mean height (Ra and Sa), root mean square roughness (Rq), average maximum height of the surface (Rz and Sz), texture aspect ratio (Str), the spatial parameter of the surface (Spc), and developed interfacial area ratio (Sdr). These parameters collectively provide a comprehensive description of a surface’s texture, aiding in assessing its roughness, directionality, and functional characteristics. On average, Cedrela sinensis push-finished surfaces showed Ra of 16.78 μm, while pull-finished surfaces showed Ra of 11.22 μm. For Paulownia, push-finished surfaces had Ra of 6.04 μm, while pull-finished surfaces had Ra of 5.83 μm. Statistical t-test results showed no significant differences between push and pull planning methods (p > 0.05). The surface roughness analysis reveals that Cedrela sinensis surfaces exhibit higher roughness, more significant height variations, and more complex textures than Paulownia. These findings are valuable for the woodworking industry, offering insights into optimizing planning methods for specific wood species and applications.
... However, advancements in manufacturing techniques, such as ultra-precision technology and additive manufacturing, have led to more intricate surfaces with deterministic patterns. Structured surfaces, which are precisely engineered to deliver specific functionalities, have gained prominence in metrology due to their customised applicability through tailored structural designs [5]. Such surfaces are increasingly taking centre stage in metrology, given their tailor-made applicability through customised structural introductions. ...
Denoising plays a vital role in freeform structured surface metrology. Traditional techniques, such as Gaussian and partial differential equation-based diffusion filters, often involve a time-consuming calibration process, particularly for complex surfaces. The main challenge lies in automating the denoising operation while accurately preserving features for varied surface textures. To address this challenge, an automatic approach PI-DnCNN based on small sample learning is presented in this paper. Denoising convolutional neural network (DnCNN) is employed as the basic architecture of this approach, due to its effectiveness in tackling mix-level Gaussian noise and adapting to small training datasets. Acknowledging the constraints of limited datasets, a novel physics-informed denoising loss function marrying filtering techniques is proposed to improve model performance. Additionally, a hybrid data augmentation strategy is developed to enhance the recognition of complex components. The paper also reports a set of experiments to demonstrate the presented approach in terms of performance over conventional techniques, enhancements with limited sample sizes, and applicability in general image denoising. The experiment results suggest that the presented approach consistently achieves higher average scores compared to traditional filters and emerges superior compared to the conventional DnCNN loss across different dataset sizes. In addition, the proposed loss also shows effectiveness in general image denoising, which suggests the robustness and universality of the approach.
... The main aim of the proposed procedure was to improve the verification of the (2) issue. Surfaces after ground, honed and milled treatments, are topographies with deterministic patterns, where examples of this type of textures were comprehensively studied by Jiang et al. [78]. For the specimens considered, one or two dominant directions were obliged. ...
... Therefore, effective segmentation methods are required to overcome this limitation [7]. Segmentation involves dividing the surface into distinct components, allowing researchers to identify and analyze specific features or regions of interest, thus enabling a deeper understanding of their contribution to the overall functionality of surface textures [8]. ...
Understanding surface topography is vital for optimizing the performance of engineering components. Featured surfaces, with distinct patterns and textures, have garnered attention for their potential to reduce friction and wear. However, accurately describing their topography poses challenges, necessitating effective segmentation methods in many applications. This paper proposes utilizing the Gaussian Mixture Models (GMMs) clustering method as a novel approach for surface metrology analysis of featured surfaces. The GMMs provide an approach to identify and analyze specific surface features and enhance comprehension of their contributions to functionality. The paper presents a comprehensive methodology involving surface characterization, GMMs clustering, plateau reference plane location, and calculation of essential topography parameters. Results from four different surfaces are discussed, demonstrating the effectiveness of the proposed GMMs-based methodology in segmenting plateau regions, grooves, and porosity.
... Therefore, the surface profile quality monitoring method proposed in this paper is of great significance for the manufacturing process of complex surfaces . According to the difference in geometrical properties, the engineering workpiece surfaces can divide into Euclidean surfaces and non-Euclidean surfaces (Jiang et al., 2021). The Gaussian curvature of the Euclidean surface is zero everywhere and it usually appears as a plane or a cylinder, while the non-Euclidean surface appears as curved surfaces with non-zero and variable Gaussian curvature including a sphere surface or a freeform surface. ...
With the development of high-end manufacturing, a variety of sophisticated parts with complex curved surfaces have emerged, and curved surface profile monitoring is of great importance for achieving the higher performance of a part. Benefiting from the recent advancements in non-contact measurement systems, millions of high-density point clouds are rapidly collected to represent the entire curved surface, which can reflect the geometrical and spatial features. The traditional discrete key quality characteristics-based monitoring approaches are not capable of handling complex curved surfaces. A novel curved surface profile monitoring approach based on geometrical-spatial joint features is proposed, which consists of point cloud data preprocessing, Laplace–Beltrami spectrum calculation, spatial geodesic clustering degree definition, and multivariate control chart construction. It takes full advantage of the entire wealth information on complex curved surfaces and can detect the small shifts of geometrical shape and spatial distribution information of non-Euclidean surfaces. Two real-world engineering surfaces case studies illustrate the proposed approach is effective and feasible.
... Topographic analysis of surfaces is used in many different areas of human life and activity, among which conventional and unconventional machining processes [9], tribology [10], wear [11] and friction [12] are the most frequently mentioned. There are many different techniques for digitizing surface in micro scale [13], with different advanced options of extracting interesting features [14,15]. Surface topography influences on adhesion and related processes, including energy phenomena [16]. ...
El poliuretano termoestable es un material utilizado en el sector de modelizado y actualmente está sustituyendo a piezas estructurales en maquetas de control del sector del automóvil y aeronáutico, por su facilidad de mecanizado, además de aportar unas buenas propiedades mecánicas. En este trabajo se ha experimentado el mecanizado robotizado de un material poliuretano comercial tipo Necuron® 651. El mecanizado robotizado ofrece una amplia posibilidad de mecanizar y modelar materiales con la ventaja de aumentar la accesibilidad a las piezas, en comparación con los centros de mecanizado convencionales de tres o más ejes. El mecanizado se ha llevado a cabo con una instalación consistente en un robot ABB® 6640-235 con un cabezal de alta velocidad Peroni® y mesa rotativa ABB. La desventaja del mecanizado robotizado, causado por la falta de rigidez de la morfología del robot, son los errores macro y micro dimensionales. Se han realizado geometrías sencillas con herramientas enterizas de acero rápido. La programación CAM se ha obtenido con el software Powermill® de la compañía DELCAM, teniendo en cuenta dos tipos de estrategias de limitación de grados de libertad del robot, para verificar resultados geométricos. Finalmente se ha medido y analizado la superficie generada mediante interferómetro autofocus Alicona y se ha medido la macrogeometría de las muestras en máquina de medición por coordenadas. Los resultados muestran que los errores tanto micro como macro disminuyen significativamente si se hacen fijos alguno de los siete ejes, del sistema robotizado.
... While feature-based characterization has not been used for propagation of measurement uncertainty [49], Leach et al. [50] asserted that precision of an instrument is not dependent on the type of material and topography and the precision of an instrument can be determined regardless of the measured surface. Precision of instruments can be estimated in the same way for all surfaces. ...
This paper describes and illustrates a convenient, new method for checking repeatability and reproducibility by direct comparisons of measured heights. Focus variation, confocal, and interferometric optical areal profiling have been integrated as modes on the Sensofar S neox and are used here. Repeated, sequential measurements are made with these different types of measurement without repositioning the measurand. Several different positions are measured on the same measurand, an electroformed, standard areal surface with an irregular topography. Height (z) measurements at individual locations (x,y) are plotted between repeated measurements at the same position on the measurand, and are called H–H plots. These plots can be used for rapid evaluations of topographic measurement repeatability on ordinary topographic measurements. Exceptionally, such plots can also be used to see how well one type of measurements can reproduce another, such as confocal, focus variation, and interferometric, when they are integrated as modes on the same measurement instrument. Only when different types of measurement are included as modes on the same instrument can different measurement types be compared directly for reproducing each of the large numbers of locations (>105) in topographic measurements at the same position on a measurand. One way of quantifying repeatability and reproducibility is with coefficients of determination (R2) and slopes of linear regression analyses on these H–H plots.
... Particular attention was paid to the modeling of two-process random surfaces. The selection of a suitable method for the random modeling of different types of surface topographies to obtain the dependence of the surface characteristics, production process, and surface function was discussed by Jiang et al. [3]. In their conclusions, the authors stated that further research needs to focus on the development of a generalized feature-based technology tool-kit (an interdisciplinary subject, involving computer vision, image processing, and geometric modeling) with robustness for universal application, including fast algorithms, soft gauges, and uncertainty, to guarantee computational fidelity. ...
Lattice and gyroid structures are often subjected to additive technologies to produce various types of products, and the current market has a number of 3D printers that can be used for their production. The quality of the products produced in this way can be assessed on the basis of technical parameters and the filament used. Such an approach, however, is insufficient. In terms of quality, other product parameters need to be assessed, such as the surface texture and the internal structure’s porosity. For such an assessment, we can use the industrial tomography method and the method of roughness measurement via an optical microscope. The paper presents research on the assessment of the surface texture and porosity in lattice and gyroid structures. For the research, two types of test specimens—a specimen with a lattice structure and a specimen with a gyroid structure—were prepared. The obtained results proved that the 3D printing technology directly impacted the surface texture and porosity. For experimental specimens produced by SLS technology, we found that it was very important to carefully remove the excess powder, as unremoved powder can significantly affect the porosity results. For specimens produced by FDM technology, the research confirmed that some “gaps” between the layers were not pores but defects created during specimen production. When analyzing the surface using the Alicon Infinite G5 optical microscope, we found that the measured roughness results were directly impacted by the specimen’s surface color, the structure’s geometry, and the ambient light, which was confirmed by a red lattice experimental specimen, the surface of which could not be scanned. Based on the above, it can be stated that the selection of 3D technology for additive production needs must be given adequate attention regarding the quality of the created structures and textures.
... Analysis of the topography of the areal surface can add new information compared to profile analysis; therefore, many new parameters have been introduced, such as feature parameters characterizing the peaks [14,15]. The amplitude parameters are believed to mostly affect the surface properties, for example, they are related to friction and wear. ...
Average surface height and maximum amplitude can affect surface functions. In the industry, these parameters can be obtained based on profile measurements. However, variability in maximum profile height is high. A more stable parameter can be obtained from the results of the areal surface topography measurements as the average value of the parallel profiles. The aim of this study is to establish this parameter directly from the result of the areal surface texture by correcting the maximum surface height to material ratios in the range of 0.13–99.87%. This method was tested by measuring 100 surface topographies with a stylus profilometer and a white light interferometer. It can be utilized correctly for deterministic textures and random one- and two-process surfaces for which the correlation between neighboring profile ordinates is not very high. In other cases, the method should be modified. Employing this method, the maximum profile amplitude Pt and parameters characterizing the average profile height Pq, Pa, and the ratios Pq/Pa and Pp/Pt describing the shape of the profile ordinate distribution can be correctly estimated. Pq/Pa and Pp/Pt were more stable than the kurtosis Pku and skewness Psk. The corrected maximum height S±3σ can be adopted as a parameter that characterizes the areal surface texture as more stable than the maximum surface height St. Pq/Pa and Pp/Pt were more steady than kurtosis Pku and skewness Psk.
... It is based on a novel approach to localize lead structures as individual elements in high-resolution topography measurement data. The motivation for this type of evaluation is feature-based surface characterization, described, among others, in [35,36]. The structurebased lead analysis requires optical measurement data which provide high-resolution topographies and form the basis for the further application of segmentation algorithms. ...
The leak tightness of the sealing system rotary shaft seal is based on the formation of an active back-pumping effect of the sealing ring. Here, the sealing ring pumps the fluid in the sealing gap back into the housing. However, this active sealing mechanism is disturbed by so-called “lead structures”. Lead structures include all types of directional structures on the sealing counterface which create rotation-dependent axial fluid pumping. Lead-affected sealing counterfaces can thus cause leakage or insufficient lubrication of the sealing contact. To ensure leak tightness, lead must be avoided or tolerated. This article investigates how different structural characteristics of lead affect the amount of fluid pumped by the shaft surface. For this purpose, 26 shafts are subjected to surface analyzing methods and an experimental pumping rate test. The interaction of various geometric features of the lead structures and their combined effect on the pumping capacity is modeled based on the measured data. Appropriated correlation models are discussed and relationships between shaft lead and its pumping effect are shown. The aim is to estimate shaft pumping rates based on surface measurements in future. The results contribute to the derivation of measurable tolerance values for lead and to the prevention of leakage.
... Contrary to surface data filtering techniques, algorithms based on the deviation or slope can be successfully used [36]. Many encouraging results for data suppression were presented by Jiang et al. [58] based on the thresholding technique which refers to a family of segmentation methods. This approach was found especially suitable when the reduction in time of the data processing is important. ...
In this paper, the methods of compensation of differences in the results of entire bending-fatigued fracture surface topographies were presented. The roughness evaluation was performed with a focus variation microscope and confocal surface topography measurement techniques. The differences in the ISO 25178 roughness parameters were investigated and procedures for their compensation were studied. It was found that various types of optical measurements can cause differences in the errors occurring in the measurement process, such as outliers, and noise. The reduction of differences in the various optical roughness measurements can be attained when measurement errors are compensated. For this study, the applications of general procedures available in commercial software can be suitable for improvements of the roughness measurement results, such as raw data thresholding technique, digital filtering (S-filter), power spectral density, and autocorrelation function analyses. The validation of measurement techniques was proposed for areal and profile studies, including analysis of differences in the calculation areal ISO 25178 roughness parameters.
... Numerical modeling of a rough surface is required to solve three problems. First, the prediction of standard texture parameters in the manufacture of products and the identification of the reasons for non-compliance with the specified values [1,2]. Secondly, modeling of physical processes during the operation of a product, for example, for tribology of surface mating [3,4] or assembly of products [5][6][7]. ...
Numerical modeling of a rough surface is required to predict the quality in the manufacture and physical simulate of the product. Another important application is the testing of filtering methods in metrology. The transition from standard texture parameters to an analytical description of the surface geometry makes it possible to solve these problems at a higher level. In digital manufacturing, this step is extremely important. Additive manufacturing products have manufacturing features, that distinguish them from other processing methods. The real surface is a complex geometric object and contains deterministic and stochastic components. There is a pronounced deterministic component from the trajectory and scanning speed of the laser and a stochastic component from the physics of powder melting. The main scientific idea of this article is to model texture as a superposition of two deterministic and two Gaussian components with different parameters under given constraints. Surfaces were modeled using a combination of four component errors. For simulated surfaces, the problem of identifying relationships between model parameters and standard surface texture parameters was solved. The numerical simulation performed showed a good agreement with the real data of surface texture measurements.
... Frequently observed features in powder-based AM are particle agglomerations of different size. In recent years, extensive work has been done on developing methods for segmentation and feature detection and their application to AM surfaces [8][9][10][11][12][13][14][15]. In this work, we focus on the evaluation of surface properties related to powder particle agglomerations, such as size and quantity, as well as the area portion of the surface covered by attached particles and their relation to the particle size distribution of the powder used in the process. ...
Additive manufacturing (AM) technologies show potential for the development of functionally integrated lightweight designs, biomimetic structures and material savings. Typically, as-built surfaces show powder particle agglomerations and re-entrant features, leading to rough surfaces, which are associated with poor fatigue performance. To benefit from the full range of advantages with special focus on aerospace applications, critical features for crack initiation when subjected to fatigue loading need to be identified and mitigated. A first step toward achieving this goal is the surface texture characterisation based on the quantification of surface features. In this paper, selected areal height, functional and feature parameters from ISO 25178-2:2022 are generated and process-specific features are examined for as-built AlSi7Mg0.6 from laser powder bed fusion (PBF-LB). A connection with the particle size distribution of the used powder is demonstrated. It is shown that surface feature analysis opens up opportunities to use physically meaningful surface characteristics in future quality assurance and part qualification processes.
... Frequently observed features in powder-based AM are particle agglomerations of different size. In recent years, extensive work has been done on developing methods for segmentation and feature detection and their application to AM surfaces [8][9][10][11][12][13][14][15]. In this work, we focus on the evaluation of surface properties related to powder particle agglomerations, such as size and quantity, as well as the area portion of the surface covered by attached particles and their relation to the particle size distribution of the powder used in the process. ...
Additive manufacturing (AM) technologies show potential for the development of functionally integrated lightweight designs, biomimetic structures and material savings. Typically, as-built surfaces show powder particle agglomerations and re-entrant features, leading to rough surfaces, which are associated with poor fatigue performance. To benefit from the full range of advantages with special focus on aerospace applications, critical features for crack initiation when subjected to fatigue loading need to be identified and mitigated. A first step toward achieving this goal is the surface texture characterisation based on the quantification of surface features. In this paper, selected areal height, functional and feature parameters from ISO 25178-2:2022 are generated and process-specific features are examined for as-built AlSi7Mg0.6 from laser powder bed fusion (PBF-LB). A connection with the particle size distribution of the used powder is demonstrated. It is shown that surface feature analysis opens up opportunities to use physically meaningful surface characteristics in future quality assurance and part qualification processes.
... The reduction in errors in the feature characterization is another encouraging task to be resolved [31]. In general, each of the actions provided on the surface topography data, including those with the feature-based characterization, is provided for a more direct relationship between characterization, manufacturing process, and surface function [32]. The effect of feature size, density, and distribution was found crucial in the validation of methods for both an areal form removal and high-frequency measurement noise reduction [33]. ...
Characterization of surface topography, roughly divided into measurement and data analysis, can be valuable in the process of validation of the tribological performance of machined parts. Surface topography, especially the roughness, can respond straightly to the machining process and, in some cases, is defined as a fingerprint of the manufacturing. When considering the high precision of surface topography studies, the definition of both S-surface and L-surface can drive many errors that influence the analysis of the accuracy of the manufacturing process. Even if precise measuring equipment (device and method) is provided but received data are processed erroneously, the precision is still lost. From that matter, the precise definition of the S-L surface can be valuable in the roughness evaluation allowing a reduction in the rejection of properly made parts. In this paper, it was proposed how to select an appropriate procedure for the removal of the Land S-components from the raw measured data. Various types of surface topographies were considered, e.g., plateau-honed (some with burnished oil pockets), turned, milled, ground, laser-textured, ceramic, composite, and, generally, isotropic. They were measured with different (stylus and optical) methods, respectively, and parameters from the ISO 25178 standard were also taken into consideration. It was found that commonly used and available commercial software methods can be valuable and especially helpful in the precise definition of the S-L surface; respectively, its usage requires an appropriate response (knowledge) from the users.
... The formation of the quality parameters of the treated surface is due to the friction of the smooth part of the tool and the opposite movement of the inclined groove on the contact surface of the workpiece. Based on the features of topography defined in [44], the results of the analysis of the topographies of the treated surfaces (see Figure 9) show that the location of the peaks is more uniform for the surface after the MPT with the tool with the oppositely directed grooves on the working surface than it is after the treatment using another tool. The surface waviness in the transverse direction is more pronounced than it is in the longitudinal one ( Figure 10). ...
A surface nanocrystalline steel layer in the low alloy steel 41Cr4 was fabricated by using mechanical-pulse treatment (MPT) with different deformation modes. The structure parameters, the physical and mechanical properties, the wear resistance, and the surface topography parameters of the treated steel depending on the deformation mode were investigated. A tool with a smooth working surface was used for inducing unidirectional deformation in the top surface layer (shear), and a tool with the oppositely directed grooves was used for generating multidirectional deformation. The surface layer with a nanocrystalline structure formed by MPT using both of the tools was characterised by enhanced mechanical properties and wear resistance compared with those of the untreated or heat-treated steels. Inducing multidirectional deformation during the MPT resulted in a decrease in the grain size and an increase in the depth and microhardness of the surface layer due to it facilitating the generation of dislocations compared to those formed under unidirectional deformation. The results also demonstrated that favourable surface topography parameters providing the highest wear resistance of the steel were obtained at MPT using multidirectional deformation.
... Dabei werden Täler und Hügel voneinander getrennt und Elemente, die den Prunenschwellwert (i.d.R. angegeben in %Sz) unterschreiten, mit dem nächstgelegenen größeren Element kombiniert, wie veranschaulicht in Bild 3. In der ISO 25178[3] ist für einige Elementparameter der Standard-Schwellwert mit 5% angegeben. Für detaillierte Informationen wird auf[3][4][5][6] verwiesen. Kombination kleiner Täler durch WolfbeschneidungFigure 3: Combination of small dales by Wolf pruningEs werden in dieser Arbeit Charakteristika von Senken betrachtet, da in Folgearbeiten vor allem der Zusammenhang mit der Dauerfestigkeit thematisiert wird. ...
Additive manufacturing (AM) technologies show potential for the development of functionally integrated lightweight designs, biomimetic structures and material savings. Typically, as-built surfaces are characterized by powder particle agglomerations and re-entrant features, leading to a high initial surface roughness, which is associated with poor fatigue performance. In order to make use of the full range of advantages with special focus on aerospace applications, critical features for crack initiation when subjected to fatigue loading need to be identified and mitigated. A first step toward achieving this goal is the surface texture characterization based on the quantification of surface features by means of surface feature parameters. Selected areal feature parameters are evaluated and compared for three different as-built surface conditions of aluminium alloy samples from laser powder bed fusion (LPBF).
... In contrast, this current paper assumes that Uncertainties are Topographically and Material Dependent, called UTMD, i.e., uncertainties depend on the material properties and complexities of topographies [7]. For this reason, some surfaces are manufactured to be closer to industrial topographies and, therefore, more appropriate for estimating practical UTMD. ...
A top-down method is presented and studied for quantifying topographic map height (z) fluctuations directly from measurements on surfaces of interest. Contrary to bottom-up methods used in dimensional metrology, this method does not require knowledge of transfer functions and fluctuations of an instrument. Fluctuations are considered here to be indicative of some kinds of uncertainties. Multiple (n), successive topographic measurements (z = z(x,y)) are made at one location without moving the measurand relative to the measurement instrument. The measured heights (z) at each position (x,y) are analyzed statistically. Fluctuation maps are generated from the calculated variances. Three surfaces were measured with two interferometric measuring microscopes (Bruker ContourGT™ and Zygo NewView™ 7300). These surfaces included an anisotropic, turned surface; an isotropic, sandblasted surface; and an abraded, heterogeneous, multilayer surface having different, complex, multiscale morphologies. In demonstrating the method, it was found that few non-measured points persisted for all 100 measurements at any location. The distributions of uncertainties are similar to those of certain features on topographic maps at the same locations, suggesting that topographic features can augment measurement fluctuations. This was especially observed on the abraded ophthalmic lens; a scratch divides the topographic map into two zones with different uncertainty values. The distributions of fluctuations can be non-Gaussian. Additionally, they can vary between regions within some measurements.
... Furthermore, the statistical properties of feature aggregations, such as mean or standard deviation, may be more intuitive or related to functionality and could be assessed with a feature-based characterisation. Moreover, isolating relevant topographic formations, regularly defined as features, is a developing field of study in surface topography measurement [46,47]. Examples of feature characterisation are methods with excluding valleys approaches [48,49]. ...
Errors that occur when surface topography is measured and analysed can be classified depending on the type of surface studied. Many types of surface topographies are considered when frequency-based errors are studied. However, turned surface topography is not comprehensively studied when data processing errors caused by false estimation (definition and suppression) of selected surface features (form or noise) are analysed. In the present work, the effects of the application of various methods (regular Gaussian regression, robust Gaussian regression, and spline and fast Fourier Transform filters) for the suppression of high-frequency measurement noise from the raw measured data of turned surface topography are presented and compared. The influence and usage of commonly used available commercial software, e.g., autocorrelation function, power spectral density, and texture direction, which function on the values of areal surface topography parameters from selected (ISO 25178) standards, are also introduced. Analysed surfaces were measured with a stylus or via non-contact (optical–white light interferometry) methods. It was found that the characterisation of surface topography, based on the analysis of selected features, can be crucial in reducing measurement and data analysis errors when various filters are applied. Moreover, the application of common functions can be advantageous when feature-based studies are proposed for both profile and areal data processing.
... A Sisma MYSINT100 LPBF machine was used to fabricate parts, whose surface topography was acquired using the CT device described in Section 2.2 to exploit the CT capability of measuring also re-entrant surface features [24]. The obtained surfaces (see the example in Fig. 6a) were analyzed with two different methods: feature-based analysis to segment and measure the features on the surface [25] (see the example in Fig. 6b), and characterization of surface profiles including re-entrant features (see the example in Fig. 6c). The featurebased analysis was performed through a specifically developed procedure implemented combining the use of VGStudio MAX 3.2 and ImageJ to evaluate the equivalent spherical diameter of surface features (dsf). ...
Metal powder has a significant influence on the quality and performance of laser powder bed fusion (LPBF) processes and products. A key requirement for metal powder is to have shape and size distribution designed to have adequate flowability, packing behavior and laser absorption, as well as to fabricate parts with acceptable density, surface finish and mechanical properties. Accurate three-dimensional (3D) characterizations of powder particles are fundamental to enable relevant research, for example on powder reuse and material waste reduction in LPBF. This work studies advanced measurement approaches, based on X-ray computed tomography (CT), for the 3D geometrical characterization of powder particles. The work includes comparisons with conventional powder characterization methods, considering different materials and powder morphologies. Results show the potential of the CT-based approaches to provide accurate and complete 3D powder geometrical measurements, and to exploit the obtained results for the enhancement of surface topography analyses and LPBF development.
... Evaluating the surface coatings' properties is correlated to the characterization of selected features. Very popular in the analysis of ST are, as commonly called, featurebased algorithms [34] or feature-based procedures [35], used for segmentation [36] of the measured surface topography area. Additionally, methods based on multi-scale analysis are also popular in surface metrology [37]. ...
Coatings, taking comprehensive studies into account, cannot be considered without their functional performance [...]
High voltage DC relays are a crucial component in new energy vehicles. Due to the high failure rate caused by contact sticking (fusion welding), existing technologies can only analyze contact morphology after failure. There is an urgent need to determine the quantitative characterization value of contact surface morphology and the correlation between morphology, failure mechanisms, and working conditions. In this study, an Olympus DSX1000 microscope is used to extract surface topography data, and a quantitative topography characterization method based on a machine vision system is proposed to quantitatively analyze contact surface changes after arc erosion. Grey correlation analysis was applied to explore the relationship between electrical parameters such as voltage, current, and capacitance, and the contact morphology features. The results show that current and capacitance have the greatest influence on contact surface features after arc erosion, while voltage has a relatively smaller influence. This conclusion is consistent with the experimentally observed arc erosion features. Finally, an arc ion sputtering deposition model was developed to analyze the material transfer mode and its influence on the contact failure mechanism. The results provide a scientific basis for the analysis and design improvement of high voltage DC relays.
The vast majority of surface texture parameters are field parameters. The term “field” refers to the use of every data point measured in the evaluation area, as opposed to feature parameters (see Chap. 3) that only take into account specific points, lines or areas. Field parameters allow the characterisation of surface heights, slopes, complexity, wavelength content and other surface characteristics. They are defined in the specification standard ISO 25178 part 2. In this chapter, the ISO areal field parameters will be presented along with limited guidance on their use.
In parallel to using ISO field parameters, the areal texture of a surface can be described in terms of the shape, size and spatial arrangement of its most relevant regions, here referred to as areal features. This approach is known as feature-based characterisation and is particularly useful in situations where it is convenient to represent a surface as the result of a spatial arrangement of its most relevant regions, or where it is required that specific portions of a surface are isolated to undergo dedicated assessment. A specific approach to spatially partitioning a surface into regions and computing the regions’ properties to describe the entire surface has been formalised by ISO through feature parameters. However, feature-based characterisation is now emerging as an increasingly larger family of methods that includes the ISO feature parameters and allows freedom on how the topography is partitioned, how feature relevance is determined and how the individual features are described. Feature-based characterisation addresses a wide range of needs, from finding new ways to describe an entire surface, to finding dedicated ways to characterise a selected number of features. The motivation, main methods and applications of feature-based characterisation are described in this chapter.
Additive manufacturing is one of the most quickly growing paradigms in today’s manufacturing landscape. Within additive manufacturing, metal powder bed fusion is one of the most popular process technologies, capable of producing metal parts featuring geometries that have never been possible using subtractive manufacturing or forming. However, with new manufacturing technologies come new challenges for metrologists, and metal additive surfaces are some of the most complex ever seen by the surface measurement and characterisation community. In this Chapter, the characterisation challenges present in the metal additive case are covered, by first examining good practice in metal additive surface characterisation. Then, two case studies are presented, examining methods for understanding internal surface measurement using X-ray computed tomography and feature-based surface characterisation, respectively. In the first of these case studies, methods for validating X-ray computed tomography data through comparison to other surface measurement technologies are provided. In the latter case study, common metal additive surface features and example automated methods developed to characterise these features are presented.
The delineation of two‐dimensional ascending and descending manifolds represents the theoretical basis for a large number of applications in which functions are used to describe phenomena related to climate, economy, or engineering, to mention only a few. Whereas the applications are related to the pits, passes, peaks, courses, ridges, basins, and hills, of mathematical interest are the corresponding critical points, separatrices as well as two‐dimensional ascending and descending manifolds. The present article demonstrates how the boundaries of the latter, which represent the pre‐images of basins and hills, can be characterized in a graph‐theoretic way. An algorithm for their extraction, which is based on a newly proved theorem, is presented together with its implementation in C#. Finally, the modus operandi of the algorithm is illustrated by two examples, thereby demonstrating how it works even in the case of surfaces with topologically complicated structures.
Purpose
Micro-texture is processed on the surface to reduce the friction of the contact surface, and its application is more and more extensive. The purpose of this paper is to create a texture function model to study the influence of surface parameters on the accuracy of the simulated surface so that it can more accurately reflect the characteristics of the real micro-textured surface.
Design/methodology/approach
The microstructure function model of rough surfaces is established based on fractal geometry and polar coordinate theory. The offset angle θ is introduced into the fractal geometry function to make the surface asperity normal perpendicular to the tangent of the surface. The 2D and 3D contour surfaces of the surface groove texture are analyzed by MATLAB simulation. The effects of fractal parameters (D and G) and texture parameter h on the curvature of the surface micro-texture model were studied.
Findings
This paper more accurately characterizes the textured 3D curved surface, especially the surface curvature. The scale coefficient G significantly affects curvature, and the influence of fractal dimension D and texture parameters on curvature can be ignored.
Originality/value
The micro-texture model of the rough surface was successfully established, and the range of fractal parameters was determined. It provides a new method for the study of surface micro-texture tribology.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0298/
For technical surfaces, it is important to know their functional purpose and to characterize them accordingly. Therefore, ISO 21920-2 in 2D and ISO 25178-2 in 3D offer parameters that can assess surface functional properties. The topographic portions of a surface, for example hills and dales, can be classified as features and evaluated using feature parameters. However, no parameter exists to describe the spatial distribution of features with regard to the degree of homogeneity for aperiodic surfaces. Here we show the application of the Delaunay triangulation to quantify the spatial distribution respectively the geometric relationship of features. Therefore, the feature points are determined by watershed analysis and the resulting point cloud is meshed in 2D. Based on that mean and standard deviation of the triangle side lengths and the area disorder (AD) are calculated as new parameters. The method is demonstrated for sandblasted and chrome-plated specimens. In addition simulation is used to generate more data for analysis. With the proposed approach the distinction and extent of uniform, homogeneous or inhomogeneous spatial distributions of features with parameter AD can be determined.
Laser powder bed fusion (LPBF) is increasingly used to produce metal industrial components for high value-added sectors, such as aerospace, automotive and biomedical. However, mechanical and structural properties of LPBF parts are often hindered by the large quality variability, poor geometrical and dimensional characteristics, complex surface texture and low density. The quality of the feedstock material is an important aspect to be taken into account, as it significantly influences such possible issues. In particular, metal powder used in LPBF should have shape and size distribution designed to facilitate good flowability, spreading and packing behaviour, so that the final fabricated parts have acceptable density, surface finish and mechanical properties. This work focuses on the accuracy of simultaneous measurement of powder size and shape from three-dimensional reconstructions obtained by X-ray computed tomography (CT). Results of CT measurements are compared with results from other methods based on laser diffraction and scanning electron microscopy. Different materials and powder morphologies were investigated. In addition, the CT-measured powder characteristics can be used to improve other CT analyses of LPBF parts.
3D topography metrology of optical micro-structured surfaces is critical for controlled manufacturing and evaluation of optical properties. Coherence scanning interferometry technology has significant advantages for measuring optical micro-structured surfaces. However, the current research faces difficulties of designing high accuracy and efficient phase shifting, and characterization algorithms for optical micro-structured surface 3D topography metrology. In this paper, parallel unambiguous generalized phase-shifting and T-spline fitting algorithms are proposed. To avoid phase ambiguity and improve the accuracy of the phase-shifting algorithm, the zero-order fringe is determined by the iterative envelope fitting with Newton’s method, and the accurate zero optical path difference is determined by a generalized phase-shifting algorithm. In particular, the calculation procedures of the multithreading iterative envelope fitting with Newton’s method and generalized phase shifting are optimized with the graphics processing unit-Compute Unified Device Architecture kernel function. Additionally, to fit the base form of optical micro-structured surfaces and characterize the surface texture and roughness, an effective T-spline fitting algorithm is proposed by optimizing the preimage of the T-mesh with image quadtree decomposition. Experimental results show that the surface reconstruction of optical micro-structured surfaces using the proposed algorithm is more accurate, and the efficiency is 10 times higher than that of current algorithms; the time of the surface reconstruction is less than 1 s. Compared with the current B-spline method, the accuracy of roughness characterization using the proposed T-spline algorithm is improved by more than 10%.
The manufacturing process defines not only the component’s geometry, but also how its surface senses and interacts with the outside world via its topography. Every manufactured surface is rough, but the component can benefit from the roughness control. Topography in functional surfaces is optimized either by controlling the manufacturing parameters or by post-manufacturing surface patterning technologies. However, how are topographic features measured and characterized? How do rough surfaces contact each other? What happens if fluid is present at the contact interface? And what are the mechanisms that correlate surface topography and its functionalities? This article will cover the engineering of surface topography in manufacturing by addressing empirical advancements and scientific understanding in the field. The functionalities covered are adhesion, friction, and convective heat transfer. Relatively large surface structures used for heat transfer mainly take advantage of recent advances in additive manufacturing, while conventional manufacturing processes and deterministic surface patterning techniques are discussed for the control of adhesion and friction.Graphical abstract
Quantitative characterization and uncertainty evaluation of areal step height are of increasing importance for semiconductor manufacturing. However, step characterizations often confront problems of repeatability and reproducibility due to fitting of upper and lower planes. To solve this problem, we propose a cluster-based method for step height characterization and uncertainty evaluation. By data reconstruction and
K
-means clustering, our method converts characterizing steps into approximating Euclidean distances, without necessity to fit planes. Moreover, it can evaluate uncertainties simultaneously with parameterization. The proposed method is first validated with synthetic data. Then, two experiments, respectively, on nominal 5
and 90 nm standard artifacts are carried out. The characterization results highly conform to the calibrated values, with 0.0986% and 1.22% differences, respectively. Comparing to the latest ISO method, the cluster-based method presents better performance on repeatability and reproducibility. The experimental results demonstrate that the method works well for measurement either with or without outliers.
The wetting state of a water droplet remarkably affecting its sliding behavior is characterized by the droplet boundary contact line. This paper presents experimental studies of the apparent contact angle against droplet deposition time, as well as contact angle hysteresis, and compares the results with the Wenzel and Cassie-Baxter models. Observations indicate that different intermediate wetting phenomena exist. The sliding performance of a droplet under intermediate wetting states is also investigated. It is found that the droplet does not slide under partial wetting but slides when the side walls of the grooves have been wetted by part of the droplet. Further, that droplets under different wetting states on surfaces with varied groove spacing and widths, under the same groove spacing to width ratio, present altered sliding performance before rolling off from the micro-grooves in a parallel direction. This study broadens the characterization method of intermediate wetting states, which determines the condition of anisotropic sliding on micro-grooves. The findings have great potential for application to artificial self-cleaning surfaces.
We consider the problem of partitioning a set of m points in the n-dimensional Euclidean space into k clusters (usually m and n are variable, while k is fixed), so as to minimize the sum of squared distances between each point and its cluster center. This formulation is usually the objective of the k-means clustering algorithm (Kanungo et al. (2000)). We prove that this problem in NP-hard even for k = 2, and we consider a continuous relaxation of this discrete problem: find the k-dimensional subspace V that minimizes the sum of squared distances to V of the m points. This relaxation can be solved by computing the Singular Value Decomposition (SVD) of the m × n matrix A that represents the m points; this solution can be used to get a 2-approximation algorithm for the original problem. We then argue that in fact the relaxation provides a generalized clustering which is useful in its own right.Finally, we show that the SVD of a random submatrix—chosen according to a suitable probability distribution—of a given matrix provides an approximation to the SVD of the whole matrix, thus yielding a very fast randomized algorithm. We expect this algorithm to be the main contribution of this paper, since it can be applied to problems of very large size which typically arise in modern applications.
Feature characterization of rough surfaces is of growing interest in terms of a function oriented description of technical surfaces. Feature characterization requires a segmentation of significant hills and dales of the measured profile. The segmentation can be done in several ways. One method is the so called crossing-the-line segmentation which will be part of ISO 16610 part 45 and ISO 21920 part 2. The crossing-the-line segmentation described in this publication represents an extension of the algorithm proposed by Scott (Scott P, 2006, Meas. Sci. Technol. 17 , 559–564) and is based on new knowledge gathered over the last ten years. As an example, the feature parameters R S m and R c according to ISO 4287:1997 are evaluated.
With the advancement of modern enabling technologies, surfaces of high value-added products are changing from traditional simple geometries to complex geometries that feature freeform shapes. The analysis of topographical features on freeform surfaces is challenging because surface shapes are no longer planar and measurement data often require surface description in the form of triangular meshes. An approach is proposed to extend the watershed segmentation from planar surfaces to freeform surfaces. Surface topography is first extracted from measured surfaces (mesh surfaces) using proper mathematical operations, e.g. fitting and filtration. The watershed segmentation based on Maxwell’s theory is extended to 3D triangular meshes and applied to the extracted surface topography defined as a scalar function associated with the vertices of the mesh surface. Critical surface points such as peaks, pits and saddles are identified to construct a Pfaltz graph. Ridge lines and course lines are then traced starting from saddles and following the steepest uphill and downhill paths to peaks and pits, respectively. Wolf pruning of the change tree is employed to merge over-segmented regions. The extended watershed segmentation method is applied to segment surface topography of the additively processed scaffold and lattice surfaces.
We propose a microlens array (MLA) construction method based on sub-channel optimal design and splicing, and an integrated projection imaging analysis method by using ray tracing and image warping. Our stop mask greatly improves imaging quality and eliminates crosstalk. We realize various projection distances, required projection imaging dimensions, and design optimization of sub-lens structures, providing freedom and possibility for MLA structure design requirements. Optical system chief ray tracing and sub-image generation is combined by using radial basis function forward image warping. Imaging distortion and overlap misalignment from short focal projection, multi-aperture offset, and complicated surfaces are perfectly corrected. Sub-image warping pixel mapping facilitates real-time replacement of projected images. We conduct substantial MLA integration imaging designs and precision analysis of different sub-aperture sizes, MLA sizes, and projection distances.
In manufactured microfluidic channels, geometrical imperfections resulting from the manufacturing process are challenging in terms of reliability and functionality of the microfluidic device. In this work, a methodology for the geometrical and dimensional characterization of microfluidic channels using quantitative 3D optical microscopy is proposed. The methodology is based on a holistic approach including the identification of functionally relevant geometrical features and critical dimensions at design stage, as well as the related verification process at the manufacturing stage. At design stage, the critical geometrical characteristics are identified on the basis of their relation with the performance of the microfluidic device. Verification is based on a novel methodology in which measurement results collected by a surface topography measuring instrument are processed on the basis of concepts and procedures commonly applied to data generated by a coordinate measuring system. The method is presented using as an example the characterisation of a microfluidic channel realized by soft lithography and constituting part of a membrane micro valve. The geometry of the microfluidic channel is acquired by using an imaging confocal microscope.
Illumination for line-scan machine vision systems is required to produce a highly asymmetric elliptical beam pattern, to maximize system speed and accuracy. The use of LED emitters with symmetric Lambertian emission patterns is challenging in this context, requiring significant beam reshaping. A design for a collimated line-light, with long working distance, utilizing LEDs with symmetric Lambertian emission patterns, is presented. Using a combination of Fresnel lenses and total internal reflection (TIR) optics, an elliptical beam with a high degree of collimation is achieved. TIR elements are designed based on an adaptation of a freeform lens design method published by Chen et al. [Opt. Express 20, 10 (2012)]. Practical performance of the design is verified experimentally using a prototype unit. In addition, the design is compared, using ray tracing software, to line-lights constructed using commercially available symmetric and elliptical TIR lenses, and its superior performance is confirmed. The optical design described is fully manufacturable and suitable for both small and large scale production.
Hybrid micro-optics of infrared (IR) materials are of great advantage in realizing the function integration and minimization of advanced IR optical systems. However, due to the hard-and-brittle nature of IR materials, it is still challenging for both non-mechanical and mechanical technologies to achieve one-step generation of hybrid infrared micro-optics with high form accuracy. In the present study, a flexible method, namely ultra-precision side milling (UPSM), is first introduced to achieve one-step generation of infrared hybrid micro-optics in ductile mode, and the corresponding reflective diffraction characteristics are analyzed. In UPSM, the reflective/refractive primary surface of the hybrid micro-optics is formed via the removal of workpiece material, and the high-frequent secondary diffractive micro/nanostructures are simultaneously generated by the tool residual marks of cutting trajectories. With the consideration of the changing curvature of the primary surface, the optimal toolpath generation strategy is introduced to acquire the desired shapes of the secondary micro/nanostructures, and the selecting criteria of the machining parameters is discussed to avoid the brittle fractures of IR materials. In practice, two types of hybrid micro-optic components, namely hybrid micro-aspheric arrays and sinusoid grid surface with high-frequent secondary unidirectional phase gratings, are successfully fabricated on single-crystal silicon to validate the proposed method. The method adopted in this study is very promising for the deterministic fabrication of hybrid micro-optics on infrared materials.
Powder bed fusion (PBF) is a popular additive manufacturing (AM) process with wide applications in key industrial sectors, including aerospace, automotive, healthcare, defence. However, a deficiency of PBF is its low quality of surface finish. A number of PBF process variables and other factors (e.g. powders, recoater) can influence the surface quality. It is of significant importance to measure and characterise PBF surfaces for the benefits of process optimisation, product performance evaluation and also product design. A state-of-the-art review is given to summarise the current research work on the characterisation of AM surfaces, particularly PBF surfaces. It is recognised that AM processes are different from conventional manufacturing processes and their produced surface topographies are different as well. In this paper, the surface characterisation framework is updated to reflect the unique characteristics of PBF processes. The surface spatial wavelength components and other process signature features are described and their production mechanisms are elaborated. A bespoke surface characterisation procedure is developed based on the updated framework. The robust Gaussian regression filter and the morphological filters are proposed to be used for the separation of the waviness component due to their robustness. The watershed segmentation is enhanced to extract globules from the residual surface. Two AM components produced by electron beam melting (EBM) and selective laser melting (SLM), are measured and characterised by the proposed methodology. Both of the two filters are qualified for the extraction of melted tracks. The watershed segmentation can enable the extraction of globules. The standard surface texture parameters of different surface wavelength components are compared. A set of bespoke parameters are intentionally developed to offer a quantitative evaluation of the globules.
Areal optical surface topography measurement is an emerging technology for industrial quality control. However, neither calibration procedures nor the utilization of material measures are standardized. State of the art is the calibration of a set of metrological characteristics with multiple calibration samples (material measures). Here, we propose a new calibration sample (artefact) capable of providing the entire set of relevant metrological characteristics within only one single sample. Our calibration artefact features multiple material measures and is manufactured with two-photon laser lithography (direct laser writing, DLW). This enables a holistic calibration of areal topography measuring instruments with only one series of measurements and without changing the sample.
Roll-to-roll (R2R) processing on film substrates has been demonstrated to have the potential for achieving high throughput manufacturing of organic electronic systems at low cost. However, the ever-growing mobile devices market accompanied by the developments in information and communication technologies require high performance systems at very low power operation, sometimes on larger substrates having sizes in the range of a few metres. Organic electronics often fall short of fulfilling the required computing performance and power requirements of most of the common use cases. Hybrid integration of inorganic monocrystalline silicon chips on polymer films is a means to fulfil the aforementioned requirements. In this context, it is opportune to report our recent activities on R2R processing of plastic films for hybrid integration of flexible electronics. Hybrid integration can be performed with conventional, rigid surface mount devices as well as flexible, ultra-thin bare silicon chips. The first section of the paper is dedicated to a brief overview of R2R manufacturing of electronic devices with an example of production of radio frequency identification tags as well as to a discussion emphasising the targets for hybrid integration. Then, detailed descriptions about our processes for R2R manufacturing of metal wiring lines on films and hybrid integration are included. Three-dimensional integration of films and a temperature sensor label manufactured using hybrid integration process are also elaborated on. Furthermore, key results from fatigue reliability assessment of R2R metallised wiring lines are reported. Finally, some of the challenges in transferring the R2R processes for hybrid integration on film substrates from research labs to industrial manufacturing are highlighted.
Traceability in micro-metrology requires an infrastructure of accredited metrology institutes, effective performance verification procedures, and task specific uncertainty estimation. Focusing on the latter, this paper proposes an approach for the task specific uncertainty estimation based on simulation for a generic 3D microscope. The proposed simulation approach is based on the identification and a successive parameter estimation of an empirical model of measured points. The model simulates the probing error of the 3D microscope based on a Gaussian process model, thus including the correlation among close points. Parameters for the error simulation are estimated by a deep analysis of error sources of the 3D microscope. Validations of the proposed simulation approach are carried out in the case of focus variation microscopy (FVM), considering several case studies. The procedure proposed in the ISO/TS 15530-4 standard are applied for validation.
Efficient sampling methods enable the reconstruction of a generic surface with a limited amount of points. The reconstructed surface can therefore be used for inspection purpose. In this paper a sampling method that enables the reconstruction of a curve or surface is proposed. The input of the proposed algorithm is the number of required samples. The method takes into account two factors: the regularity of the sampling and the complexity of the object. A higher density of samples is assigned where there are some significant features, described by the curvature. The analysed curves and surfaces are described through the B-splines spaces. The sampling of surfaces generated by two or more curves is also discussed.
The use of state-of-the-art areal topography measurement instrumentation allows for a high level of detail in the acquisition of topographic information at micrometric scales. The three-dimensional geometric models of surface topography obtained from measured data create new opportunities for the investigation of manufacturing processes through characterisation of the surfaces of manufactured parts. Conventional methods for quantitative assessment of topography usually only involve the computation of texture parameters; summary indicators of topography-related characteristics that are computed over the investigated area. However, further useful information may be obtained through characterisation of signature topographic formations, as more direct indicators of manufacturing process behaviour and performance. In this work, laser powder bed fusion of metals is considered. An original algorithmic method is proposed to isolate relevant topographic formations and to quantify their dimensional and geometric properties, using areal topography data acquired by state-of-the-art areal topography measurement instrumentation.
The challenges of measuring the surface topography of metallic surfaces produced by additive manufacturing are investigated. The differences between measurements made using various optical and non-optical technologies, including confocal and focus-variation microscopy, coherence scanning interferometry and x-ray computed tomography, are examined. As opposed to concentrating on differences which may arise through computing surface texture parameters from measured topography datasets, a comparative analysis is performed focussing on investigation of the quality of the topographic reconstruction of a series of surface features. The investigation is carried out by considering the typical surface features of a metal powder-bed fusion process: weld tracks, weld ripples, attached particles and surface recesses. Results show that no single measurement technology provides a completely reliable rendition of the topographic features that characterise the metal powder-bed fusion process. However, through analysis of measurement discrepancies, light can be shed on where instruments are more susceptible to error, and why differences between measurements occur. The results presented in this work increase the understanding of the behaviour and performance of areal topography measurement, and thus promote the development of improved surface characterisation pipelines.
Selective laser melting (SLM) of metals produces surface topographies that are challenging to measure. Multiple areal surface topography measurement technologies are available, which allow reconstruction of information rich, three-dimensional digital surface models. However, the capability of such technologies to capture intricate topographic details of SLM parts has not yet been investigated. This work explores the topography of a SLM Ti6Al4V part, as reconstructed from measurements by various optical and non-optical technologies. Discrepancies in the reconstruction of local topographic features are investigated through alignment and quantitative assessment of local differences. ISO 25178-2 areal texture parameters are computed as further comparison indicators.
In this paper, the state of art of ultrasonicassisted machining technologies used for fabrication of micro/nano-textured surfaces is reviewed. Diamond machining is the most widely used method in industry for manufacturing precision parts. For fabrication of fine structures on surfaces, conventional diamond machining methods are competitive by considering the precision of structures, but have limitations at machinable structures and machining efficiency, which have been proved to be partly solved by the integration of ultrasonic vibration motion. In this paper, existing ultrasonic-assisted machining methods for fabricating fine surface structures are reviewed and classified, and a rotary ultrasonic texturing (RUT) technology is mainly introduced by presenting the construction of vibration spindles, the texturing principles, and the applications of textured surfaces. Some new ideas and experimental results are presented. Finally, the challenges in using the RUT method to fabricate micro/ nano-textured surfaces are discussed with respect to texturing strategies, machinable structures, and tool wear.
Many applications that exploit the manufacturing flexibility of additive manufacturing (AM) produce surfaces, primarily internal features, which cannot be measured using conventional contact or line-of-sight optical methods. This paper evaluates the capability of a novel technique to extract areal surface data from micro-focus x-ray computed tomography (XCT) from AM components and then generate surface parameter data per ISO 25178-2. This non-destructive evaluation of internal features has potential advantages during AM product research and commercial production. The data extracted from XCT is compared with data extracted using a focus variation instrument. A reference dimensional artefact is included in all XCT measurements to evaluate XCT surface determination performance and dimensional scaling accuracy. Selected areal parameters generated using the extraction technique are compared, including Sa, for which the nominal difference between the value obtained using XCT and used the focus variation method was less than 2.5%.
In this review, the use of x-ray computed tomography (XCT) is examined, identifying the requirement for volumetric dimensional measurements in industrial verification of additively manufactured (AM) parts. The XCT technology and AM processes are summarised, and their historical use is documented. The use of XCT and AM as tools for medical reverse engineering is discussed, and the transition of XCT from a tool used solely for imaging to a vital metrological instrument is documented. The current states of the combined technologies are then examined in detail, separated into porosity measurements and general dimensional measurements. In the conclusions of this review, the limitation of resolution on improvement of porosity measurements and the lack of research regarding the measurement of surface texture are identified as the primary barriers to ongoing adoption of XCT in AM. The limitations of both AM and XCT regarding slow speeds and high costs, when compared to other manufacturing and measurement techniques, are also noted as general barriers to continued adoption of XCT and AM.
Multiscale structured surfaces are a way to provide advanced, otherwise not attainable functionality on a technical part. Applications of such parts can be manifold, and numerous works have already covered the transfer of natural examples into bio-inspired surfaces or the geometrical and functional metrology of such surfaces. After briefly presenting typical functionalities of multiscale structured surfaces, this keynote paper will focus on the available manufacturing processes and review their capabilities to generate multiscale structured surfaces. To compare such processes, the so-called “multiscality” is defined that characterizes the structured surfaces according to the lateral and vertical extent of the individual stacked elements and is used as a first indicator to assess the difficulty of their manufacture. As the boundaries of what is considered a multiscale structure are diffuse, ranges of low, medium and high multiscality are defined instead. After presenting the state of the art of manufacturing processes currently utilized for the manufacture of (not only multiscale) structured surfaces, this keynote paper summarizes the capabilities of single-step and multi-step/multi-physics approaches for their applicability across different scales and gives an outlook on which processes could potentially become relevant in the future.
The chapters of this volume are based on talks given at the eleventh international Sampling Theory and Applications conference held in 2015 at American University in Washington, D.C. The papers highlight state-of-the-art advances and trends in sampling theory and related areas of application, such as signal and image processing. Chapters have been written by prominent mathematicians, applied scientists, and engineers with an expertise in sampling theory. Claude Shannon’s 100th birthday is also celebrated, including an introductory essay that highlights Shannon’s profound influence on the field. The topics covered include both theory and applications, such as:
• Compressed sensing
• Non-uniform and wave sampling
• A-to-D conversion
• Finite rate of innovation
• Computational neuroscience
• Time-frequency analysis
• Operator theory
• Mobile sampling issues
Sampling: Theory and Applications is ideal for mathematicians, engineers, and applied scientists working in sampling theory or related areas.
Definition of "stratified surface" in the CIRPedia, CIRP Encyclopedia of Production Engineering.
The study of how surface topography is affected by build orientation is important for understanding the capability of metal additive manufacturing (AM) processes, such as those based on powder bed fusion. Due to the layer-based nature of the process, surfaces built at varying orientations will be differently affected by a wide array of process-induced topographic modifications, including the staircase effect, and the presence of protruded formations (spatter, un-melted or partially melted particles) in some cases significantly occluding the underlying topography. All such process-induced topographic modifications can significantly influence the choices for surface post-processing. Most research investigating surface texture in metal AM has focused on laser powder bed fusion (LPBF) [1-6].Whilst electron beam powder bed fusion (EBPBF) is somewhat similar [7], it features some rather significant differences in the surfaces it produces [4,5,8]. To assess the topography of AM surfaces as a function of orientation, most researchers [1-6,8] have investigated surface texture parameters (profile-ISO 4287 [9] and areal-ISO 25178-2 [10]). In parallel to studying surfaces as a function of orientation, recent work on metal AM has investigated ways to describe the complex topography of additive surfaces via approaches alternative to texture parameters, focusing on the characterisation of topographic formations that populate the typical metal additive surface (weld tracks, spatter formations, particles) [11-13]. These approaches can be collectively referred to as feature-based characterisation. In this work, the topography of EBPBF surfaces as a function of orientation was investigated using a combined approach including both texture parameters and feature-based characterisation. A Ti6Al4V test part (125 × 125 × 25) mm was manufactured using EBPBF with an Arcam A2XX and designed to possess 36 sides to produce surfaces with orientations varying in 10° increments (0°, 10°, 20°, etc.) (Figure 1a). The surfaces were left in their as-built state, except for minimal post-processing, which consisted of grit blasting, typically applied to remove the sintered cake within the EBPBF process. All support structures were removed. The custom characterisation approach featured multiple steps, beginning with the automated identification and separation of all the protruding formations (spatter, partially melted and un-melted particles), such as those Abstract submitted to the www.metprops2019.org conference
A key challenge of meta-surface research is locally controlling at-will nano-scale geometric features on meter-scale apertures. Such a technology is expected to enable large aperture meta-optics, and revolutionize fields such as long-range imaging, lasers, LADARs, and optical communications. Furthermore, these applications are often more sensitive to light-induced and environmental degradation, which constrains the possible materials and fabrication process. Here, we present a relatively simple and scalable method to fabricate a substrate-engraved meta-surface, with the locally-printed index determined by the induced illumination, and therefore addresses both the challenges of scalability and durability. In this process, a thin metal film is deposited onto a substrate and transformed into a mask via local laser-induced dewetting into nanoparticles. The substrate is then dry-etched through this mask and selective mask removal finally reveals the meta-surface. We show that the masking by the local nano-particle distribution, and therefore the local index, is dependent on the local light-induced dewetting temperature. We demonstrate a printing of a free-form pattern engraved into a fused silica glass substrate using a laser raster scan. Large scale spatially controlled engraving of metasurfaces has implications on other technological fields beyond optics, such as surface fluidics, acoustics, and thermo-mechanics.
The needs, requirements, and ongoing and future research issues in geometrical metrology for metal additive manufacturing are addressed. The infrastructure under development for specification standards in AM is presented, and the research on geometrical dimensioning and tolerancing for AM is reviewed. Post-process metrology is covered, including the measurement of surface form, texture and internal features. In-process requirements and developments in AM are discussed along with the materials metrology that is pertinent to geometrical measurement. Issues of traceability, including benchmarking artefacts, are presented. The information in the review sections is summarized in a synthesis of current requirements and future research topics.
Micro-structured functional surfaces have achieved widespread applications in various advanced scientific, technological, industrial, and engineered fields due to their excellent performances, which are vitally limited by their feasible fabrication. Currently, ultra-precision machining, typically including ultra-precision diamond turning, ultra-precision diamond milling, ultra-precision diamond scratching, ultra-precision grinding, and ultra-precision polishing, is developed as a very-promising solution for the micro-structured functional surface fabrication with high quality, high efficiency, high flexibility, and low cost. Therefore, this paper aims to briefly review the current state of the art in the investigation into ultra-precision machining characteristics of micro-structured functional surfaces with a focus on their typical advanced applications as the significant achievements of their ultra-precision machining fabrication, discuss the key challenges, and further provide new insights into ultra-precision machining of micro-structured functional surfaces for the future research and their further advanced applications.
The Handbook of Surface and Nanometrology explains and challenges current concepts in nanotechnology. It covers in great detail surface metrology and nanometrology and more importantly the areas where they overlap, thereby providing a quantitative means of controlling and predicting processes and performance. Trends and mechanisms are explained with numerous practical examples. Bringing engineering and physics together at the nanoscale reveals some astonishing effects: geometric features such as shape change meaning; roughness can disappear altogether; signals from instruments have to be dealt with differently depending on scale. These and other aspects are dealt with for the first time in this book. It is relevant not only for today's technology but also for future advances. Many aspects of nanotechnology and precision engineering are considered in chapters on manufacture, characterization, standardization, performance and instrumentation. There is a special chapter on nanometrology and this subject permeates the whole book. The Handbook of Surface and Nanometrology is the only book that covers these subject areas and is the definitive work in this field. This book is indispensable for firms making, trading, and researching semiconductor devices, MEMS, and micro-optics, as well as tradition precision engineering products. It will also be useful in quality control as well as for research scientists, development engineers, and production managers.
Atomic force microscopes (AFMs) are commonly and broadly regarded as being capable of three-dimensional imaging. However, conventional AFMs suffer from both significant functional constraints and imaging artifacts that render them less than fully three dimensional. To date a widely accepted consensus is still lacking with respect to characterizing the spatial dimensions of various AFM measurements. This paper proposes a framework for describing the dimensional characteristics of AFM images, instruments, and measurements. Particular attention is given to instrumental and measurement effects that result in significant non-equivalence among the three axes in terms of both data characteristics and instrument performance. Fundamentally, our position is that no currently available AFM should be considered fully three dimensional in all relevant aspects.
The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more. Incorporating image processing and analysis examples at all scales, from nano- to astro this Seventh Edition: Features a greater range of computationally intensive algorithms than previous versions Provides better organization, more quantitative results, and new material on recent developments. Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis. Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines. Presents 500+ entirely new figures and images, with more than two-thirds appearing in color.
Textures are abundantly exploited in nature for securing superior functionalities including adhesion, color manipulation, anti-reflection, and drag management. Over millions of years, these advanced properties are endowed to various organisms on the planet to survive and adapt in harsh environmental conditions. Texture characteristics such as feature size, shape, periodicity, aspect ratio, orientation and hierarchy are critical in nature's ‘tool-box’. Manufacturing of cutting-edge products require multi-functionalities for efficiency, durability and sustainability for improving the quality of life of growing population. This paper analyzes and discusses convergence and underlying science and engineering of well proven natural strategies of surface textures and their effective synthetic implementation in engineered products.
One of the major issues of the micro-milling operations pertains to burrs formation, which affects the quality of the final product, and, thus, the capability to meet the part desired performances. Burrs characterization and evaluation are still a challenging task in micro-machining, especially if on-machine monitoring of burrs is desired. This paper proposes a newly developed method based on optical microscopy, a-priori information on the manufacturing process, and an unconventional use of void pixels for fast and non-destructive evaluation of multiple geometrical quantities. Newly defined parameters on burrs lateral distribution and axial depth of cut are presented in addition to the standard surface texture parameters. The proposed methodology is applied to slotting micro-milling operations on pure titanium grade II. The obtained results show the method potential that can be exploited for on-machine monitoring of micro-milling operations.
This work studies multiscale analyses and characterizations of surface topographies from the engineering and scientific literature with an emphasis on production engineering research and design. It highlights methods that provide strong correlations between topographies and performance or topographies and processes, and methods that can confidently discriminate topographies that were processed or that perform differently. These methods have commonalities in geometric characterizations at certain scales, which are observable with statistics and measurements. It also develops a semantic and theoretical framework and proposes a new system for organizing and designating multiscale analyses. Finally, future possibilities for multiscale analyses are discussed.