Surface Metrology Research Articles

Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3)

In this paper, we propose a novel data curation concept that enables data mining and analytics within the recently described Cyber-Physical Manufacturing Metrology Model (CPM 3 ). The newly proposed methodology is based on organizing the metrology data into tree-based database structures using distance-based unsupervised clustering of the raw metrology data. Compared to traditionally utilized temporally organized lists, the new tree-based database organization of metrology data enables logarithmic acceleration of searches within the data and thus provides dramatic advantages for data mining. The newly proposed data curation methodology was evaluated in case studies involving hyper-spectral metrology of nanopatterned surfaces, coordinate measurement machine (CMM) inspection of aircraft engine turbines and imaging-based metrology of nano-volume droplets in the jet and fill stage of imprint lithography processes. Significant improvements in search speeds with minimal or no losses in search precision and recall were observed in all case-studies, with benefits of tree-based data organization growing with the size of the data.

Advances in research and applications of optical aspheric surface metrology

The predecessor of China Optics was China Optics and Applied Optics Digest, which was founded in 1985. At that time, it was the only retrieval journal in the field of optics in China. At the end of 2008, China Optics and Applied Optics Digest was renamed

A Cluster-Based Method for Quantitative Characterization and Uncertainty Evaluation of Areal Step Height in Structured Surface Metrology

Quantitative characterization and uncertainty evaluation of areal step height is 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 firstly validated with synthetic data. Then two experiments respectively on nominal 5 μm and 90 nm standard artefacts 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.

Characterization of surface structures by using interferometry under challenging environmental conditions

Surface data contains not only information about functionality of a product but also gives hints about the environmental conditions, like processing parameters or vibration. There are different methods to obtain such information and white light interferometers are accepted to be one of the most powerful tools for surface metrology. Besides other metrological characteristics, its vertical resolution in the level of nanometer enables the acquisition of important details in topography. But at the same time, effects of environmental factors like uncontrolled movement or vibrations can be seen in the measurement data if some precautions are not taken. In this paper a new method which reduces the effects of environmental disturbances is described.

Data Analytics for Noise Reduction in Optical Metrology of Reflective Planar Surfaces

On-line data collection from the manufactured parts is an essential element in Industry 4.0 to monitor the production’s health, which required strong data analytics. The optical metrology-based inspection of highly reflective parts in a production line, such as parts with metallic surfaces, is a difficult challenge. As many on-line inspection paradigms require the use of optical sensors, this reflectivity can lead to large amounts of noise, rendering the scan inaccurate. This paper discusses a method for noise reduction and removal in datapoints resulting from scanning the reflective planar surfaces. Utilizing a global statistic-based iterative approach, noise is gradually removed from the dataset at increasing percentages. The change in the standard deviation of point-plane distances is examined, and an optimal amount of noisy data is removed to reduce uncertainty in representing the workpiece. The developed algorithm provides a fast and efficient method for noise reduction in optical coordinate metrology and scanning.

Single-shot high speed aerial chromatic confocal metrology sensor

Chromatic confocal metrology is a widely established optical metrology technique, which allows for noncontact, high-speed three-dimensional surface profiling without the need of mechanical depth scanning. However, current methods are limited by the use of some sort of surface scanning method with mechanically moving parts. Furthermore, the setups involve a spectrometer setup, either through prisms, gratings, or multispectral cameras. This drastically limits the simultaneously measureable positions in lateral direction, as the spectrometer setup will utilize one spatial dimension for the wavelength domain. We present a method for chromatic confocal metrology that enables high-speed and high-resolution one-shot aerial surface metrology. This method is scalable with respect to measurement range in axial as well as in lateral direction and in the number of measurement points that can be measured simultaneously. After deriving the theoretical basis of the approach, a virtual optical design with a field of view of 10 mm × 10 mm and a depth range of 1.5 mm with roughly 1000 measurement points, based mainly on off-the-shelf components will be presented. This virtual system design was used to perform various simulations and explain the design process and considerations as well as the expected system response of the proposed system.

Flexible and high-resolution surface metrology based on stitching interference microscopy

Small optics of 10 mm-scale are widely used in miniature cameras with increasingly sophisticated surface shape. The surface features ranging from low to high frequency need to be measured efficiently for in-process quality control. Wavefront interferometry is applicable with specifically designed null optics for each surface, but not preferred for small optics because the surface radius is approaching the shortest measurable radius limited by the interferometer optics. We present a strategy for flexible surface metrology based on stitching interference microscopy. The full aperture surface is divided into a series of small subapertures with reduced size and slope which are then measurable with a standard interference microscope. The measurement principle is introduced and a method for subaperture design is proposed by checking the subaperture size and slope after coordinate transformation. A simultaneous stitching algorithm is proposed to minimize the overlapping deviations with overlapping points and subaperture configurations determined automatically in a way of alternating optimization. Instrumentation is easy by integrating a multi-axis platform with a commercial interference microscope. Both the lateral and the vertical scales need to be calibrated to give accurate subaperture measurement of three coordinates. The capability of the instrument is finally verified through a series of experiments compared with cross tests such as the null test and the stylus profilometry. It shows high flexibility to measure a variety of complex surfaces including the high-order even asphere, the “gull-wing” surface and microstructured curved surfaces without using any auxiliary null optics. The instrument enables “one-stop” measurement of surface form, waviness and roughness simultaneously.

Surface Metrology Principles for Snow and Ice Friction Studies

Recent advances in surface metrology science are applied to understanding friction with snow and ice. Conventional surface metrology’s measurement, analyses, and characterizations, have inherent limitations for elucidating tribological interactions. Strong functional correlations and confident discriminations with slider surface topographies, textures, or “roughness”, have largely eluded researchers using conventional methods. Building on 4 decades of research using multiscale geometric methods, two surface metrology axioms and corollaries are proposed with good potential to provide new technological insights.

Discrimination of Surface Topographies Created by Two-Stage Process by Means of Multiscale Analysis.

The fundamental issue in surface metrology is to provide methods that can allow the establishment of correlations between measured topographies and performance or processes, or that can discriminate confidently topographies that are processed or performed differently. This article presents a set of topographies from two-staged processed steel rings, measured with a 3D contact profilometer. Data were captured individually from four different regions, namely the top, bottom, inner, and outer surfaces. The rings were manufactured by drop forging and hot rolling. Final surface texture was achieved by mass finishing with spherical ceramic media or cut wire. In this study, we compared four different multiscale methods: sliding bandpass filtering, three geometric length- and area-scale analyses, and the multiscale curvature tensor approach. In the first method, ISO standard parameters were evaluated as a function of the central wavelength and bandwidth for measured textures. In the second and third method, complexity and relative length and area were utilized. In the last, multiscale curvature tensor statistics were calculated for a range of scales from the original sampling interval to its forty-five times multiplication. These characterization parameters were then utilized to determine how confident we can discriminate (through F-test) topographies between regions of the same specimen and between topographies resulting from processing with various technological parameters. Characterization methods that focus on the geometrical properties of topographic features allowed for discrimination at the finest scales only. Bandpass filtration and basic height parameters Sa and Sq proved to confidently discriminate against all factors at all three considered bandwidths.

Measurement techniques to improve the accuracy of x-ray mirror metrology using stitching Shack-Hartmann wavefront sensors.

We describe the development of specific measurement protocols to improve the accuracy of surface metrology of x-ray mirrors using a dedicated commercial instrument based on wavefront sensing techniques. This instrument, SHARPeR, uses measurements from a Shack-Hartmann wavefront sensor combined with a sub-aperture stitching method to provide two-dimensional maps of the surface slope errors and can measure curved mirrors above 1m radii. In this paper, we describe the results of measurement methods developed on a SHARPeR system installed at the European Synchrotron (ESRF) to reduce the contribution of systematic errors to measurements of strongly curved spherical and aspherical x-ray mirrors with intrinsic slope errors of the order of 100-200 nrad rms. We demonstrate how this commercial integrated instrument can provide measurements of these mirrors with comparable accuracy to those measured with a long trace profiler.

An interpretable machine learning based approach for process to areal surface metrology informatics

Surface metrology parameters represent an important class of design variables, which can be controlled because they represent the DNA or fingerprint of the whole manufacturing chain as well as form important predictors of the manufactured component’s function(s). Existing approaches of analysing these parameters are applicable to only a small subset of the parameters and, as such, tend to provide a narrow characterisation of the manufacturing environment.This paper presents a new machine learning approach for modelling the surface metrology parameters of the manufactured components. Such a modelling approach can allow one to understand better and, as a result, control the manufacturing process so that the desired surface property can be achieved whilst manipulating the process conditions. The newly proposed approach utilises a fuzzy logic based-learning algorithm to map the extracted process features to the areal surface metrology parameters. It is fully transparent since it employs IF...THEN statements to describe the relationships between the input space (in-process monitoring variables) and the output space (areal surface metrology parameters). Furthermore, the algorithm includes a ridge penalty based mechanism that allows the learning to be accurate while avoiding over-fitting. This new machine-learning framework was tested on a real-life industrial case-study where it is required to predict the areal parameters of a manufacturing (machining) process from in-process data. Specifically, the case study involves a full factorial experimental design to manufacture seventeen (17) steel bearing housing parts which are fabricated from heat-treated EN24 steel bars. Validation results showed the ability of this new framework not only to predict accurately but also to generalise across different types of areal surface metrology parameters.

A Miniature GaN Chip for Surface Roughness Measurement

In this work, we report on the fabrication and characterization of a miniature GaN chip with a size of $1.1\times 1.1\times0.21$ mm3 for surface roughness measurement. Unlike conventional optical metrology that requires external components for the optical coupling between light source and detector, a monolithic GaN-on-sapphire chip fabricated through wafer-scale processes provides light emission and photodetection functions and is capable of sensing a range of average surface roughness from 0.025 to $1.6~\mu \text{m}$ . The sensing performances are compared with fiber-optic metrology, and the ability to real-time monitor the roughness of the moving surface is demonstrated. The novel chip offers the advantage of non-contact and non-destructive, compact structure, simple operation, and in situ measurement capability, which is highly valuable for various practical and industrial surface metrology applications.

Thickness Effect on Some Physical Properties of RF Sputtered ZnTe Thin Films for Potential Photovoltaic Applications

Zinc telluride thin films with different thicknesses were grown onto glass substrates by the rf magnetron sputtering technique, using time as a variable growth parameter. All other deposition process parameters were kept constant. The deposited thin films with thickness from 75 to 460 nm were characterized using X-ray diffraction, electron microscopy, atomic force microscopy, ellipsometry, and UV-Vis spectroscopy, to evaluate their structures, surface morphology, topology, and optical properties. It was found out that the deposition time increase leads to a larger growth rate. This determines significant changes on the ZnTe thin film structures and their surface morphology. Characteristic surface metrology parameter values varied, and the surface texture evolved with the thickness increase. Optical bandgap energy values slightly decreased as the thickness increased, while the mean grains radius remained almost constant at ~9 nm, and the surface to volume ratio of the films decreased by two orders of magnitude. This study is the first (to our knowledge) that thoroughly considered the correlation of film thickness with ZnTe structuring and surface morphology characteristic parameters. It adds value to the existing knowledge regarding ZnTe thin film fabrication, for various applications in electronic and optoelectronic devices, including photovoltaics.

Review Article] Recent Techniques in Surface Metrology

Review Article] Recent Techniques in Surface Metrology

Geometric analysis of measurement errors in a surface metrology class with closed-loop probes

This paper presents a novel measurement error model for closed-loop surface metrology. In these surface metrology systems, the motion of the probe tip is strictly constrained on a parallel surface that is separated from the measured sample surface of constant displacement by closed-loop controllers. Examples of such metrology systems include constant signal mode scanning probe microscopes and coordinate measuring machines. The combined effect of volumetric errors and surface tracking controllers on the final measurement error was analyzed using an error model developed based on multi-body system theory and surface geometry. A comprehensive overview of the errors of a typical large-scale scanning tunneling microscopy system is provided as an example. Simulations were performed to illustrate the influence of the systematic errors on the final accuracy. Experiments were also conducted on the measurement of a typical micro-structured surface to both verify the proposed error model and establish a possible compensation scheme.

Surface Metrology and Data Science/Analytics Applied to Modern Asian Lacquer Surfaces

This paper presents a new quantitative approach to the study of Asian lacquers using surface metrology, and two data science approaches: feature engineering and convolutional deep neural networks, as used in machine vision or image recognition applications. The types of Asian lacquers and additives have a quantifiable impact on the topography of the resulting surface. To understand the unaged and aged characteristics, 15 different formulas of Asian lacquer were prepared using laccol, thitsiol and urushiol with the most common additives: oils, pigments and resins. These were studied with the surface metrology instrumental technique of confocal microscopy.

Surface metrology of bone surface attachments of knee ligaments.

Textural differences between entheses reflect biomechanical activities of the musculoskeletal system. Methods used to measure these surfaces have limitations. Here, the surface metrology of roughness of articular and entheseal surfaces of the knee are investigated with an optical profiler. Osteological specimens of six femora and seven tibiae were prepared from cadavers. Measurements were obtained to surrogate body mass. Specimens were molded with polyvinylsiloxane and casts prepared with resin, which were scanned using a white light optical profiler. Scans were processed by a computer program. Each scan produced 32 variables, categorized into 6 groups for each location. The distribution of data was mostly normal. Analysis of variance (ANOVA) identified Ssk significant (p-value .002); post hoc Tukey testing indicated significance between femoral PCL and tibial ACL entheses groups (p-value .007), and between tibial ACL and tibial entheses groups (p-value .002) suggesting the ability to differentiate anterior and posterior cruciate ligament entheses. Sku was found significant with a t test between articular and entheseal surfaces. Correlation coefficients were significant between surface metrology parameters and measurements related to body mass. This study distinguished differences between entheses of the anterior and posterior cruciate ligaments, with the Ssk parameter most useful. Differences in articular and entheseal surfaces were found with the Sku parameter most useful. Correlations indicated a relationship between body mass and surface metrology parameters. Finally, these findings suggest this method can be used for further investigation of spondyloarthropathies.

A Morse theoretic approach to the geometrical feature terms specified in ISO 25178-2 and ISO 16610-85

Morse theoretic concepts are today widely employed for the formal characterisation of surfaces and surface features. Although nowhere explicitly mentioned, several core concepts of surface metrology, such as the geometrical feature terms being specified in ISO 25178-2 and ISO 16610-85, are also closely related to Morse theory. The current lack of adequate formal definitions, however, implies that several inconsistencies and ambiguities can actually be found within the two standards. As a consequence, in the present paper the focus is laid on (a) the investigation of the interrelationships between Morse theory and the geometrical feature terms and (b) the presentation of some modifications of the existing definitions in order to eliminate the addressed ambiguities. Apart from the benefit of a consistent topological framework with respect to the definitions of the geometrical feature terms, the application of Morse theory would have the additional advantage that a powerful mathematical tool could be exploited in order to gain new insights into surface structures.

Freeform surface adaptive interferometry assisted with simulated annealing-hill climbing algorithm

The freeform surface adaptive interferometer (FSAI) recently has been employed to realize the unknown freeform surface metrology. A near null interferogram should be acquired from the initial interferogram with undistinguished fringes even dark areas. The direct optimization object in FSAI is just the interferogram rather than the focusing intensity characterization in traditional wavefront-sensorless (WFS) adaptive systems. The simulated annealing-hill climbing (SA-HC) mixed algorithm is employed in the FSAI, which has much better convergence than the stochastic parallel gradient descent (SPGD) algorithm, almost as much as the geneticalgorithm (GA). At the same time, it is much faster than GA and thus applicable to the test of volume-produced in the optical shop. Simulations and experiments validating the algorithm feasibility are presented.

Nano-imprinted subwavelength gratings as polarizing beamsplitters

Polarizing beamsplitters have numerous applications in optical systems, such as systems for freeform surface metrology. They are classically manufactured from birefringent materials or with stacks of dielectric coatings. We present a binary subwavelength-structured form-birefringent diffraction grating, which acts as a polarizing beamsplitter for a wide range of incidence angles −30∘…+30∘. We refine the general design method for such hybrid gratings. We furthermore demonstrate the manufacturing steps with Soft-UV-Nanoimprint-Lithography, as well as the experimental verification, that the structure reliably acts as a polarizing beamsplitter. The experimental results show a contrast in efficiency for TE- and TM-polarization of up to 1:18 in the first order, and 34:1 in the zeroth order. The grating potentially enables us to realize integrated compact optical measurement systems, such as common-path interferometers.