Coherence scanning interferometry (CSI), based on the principle of interference, can achieve sub-nanometer precision for height measurements. On the other hand, focus variation microscopy (FVM), ...combining the small depth of field of the objective, is a widely used surface topography measurement method suited to surface topography that is mostly optically rough. In this paper, we propose a method to simultaneously obtain the interferometric fringe data and focus variation FVM image stack, from a single vertical scanning process, using a CSI instrument without any hardware modifications. Using a 3D Fourier transform, the FVM signal, looks takes the form of a “bowtie” and the CSI signal resembles two “umbrellas” that are separated in 3D K-space. The signal is recovered using a 3D inverse Fourier transform and the surface topography can be determined by fusing the CSI and FVM signals. Since both signals come from the same instrument and scanning process, there is no need for coordinate registration and data interpolation during the data fusion process. Our method combines the features of CSI and FVM measurement, thereby improving the robustness and data coverage of the measurement. An all-in-focus surface topography map can also be generated using this method. This focusing feature has the potential to significantly improve the defect detection and quality control ability of CSI instruments.
•Extracting focus variation data from coherence scanning interferometry without any hardware modifications.•No need for coordinate registration and data interpolation during the data fusion process.•Combining the features of CSI and FVM measurement, thereby improving the robustness and data coverage of the measurement.•All-in-focus surface topography map can be generated using this method for defect detection and quality control.
This publication addresses the adaptive control of manufacturing deviations in micro gear hobbing. We aim to establish Zero Defect Manufacturing in a series production using manipulated parts with a ...small sample size and machine learning. Therefore, optical focus variation metrology is used to measure gears inline. Afterward, the evaluation of measurement results based on trained models and the transfer of correction parameters back to the machine tool through control algorithms are established. Critical parameters of the manufacturing process are identified through preliminary tests, which are varied using Latin Hypercube Sampling. The resulting experimental plan defines manipulated deviations for manufacturing 200 sample gears representing production variations. The evaluation according to parameter-based gear deviations enables the modeling of influencing quantities using machine learning. This information provides a control algorithm for the feedback of correction values to the machine tool based on data analyses. After validation, it is shown that the current state of measurement technology enables the inline quality control of micro-components. The final control loop achieved accuracies in the micrometer range at detection levels of over 90%. Consequently, these results form a basis for implementing future adaptive quality control loops within data-driven production.
•Modular approach for implementing adaptive quality control loops.•Use case: Control of manufacturing deviations in micro gear hobbing.•Series production usage based on manipulated parts and machine learning.•System accuracies in the micrometer range at detection levels of over 90%.•Optical focus variation metrology is implemented to measure gears inline.
This paper contains analysis of fatigue fracture surfaces parameters of circumferential v-notched 10HNAP (S355J2G1W) steel specimens. Fatigue tests were performed under bending, torsion and ...combinations of bending MB and torsional MT moments. Stationary and ergodic random loadings had normal probability distribution and wide-band frequency spectra from 0 to 60 Hz.
Thirty years after fatigue tests, the fracture surfaces of the specimens were subjected to observations with the use of a focus variation microscope (FVM), which allows data sets with a large depth of field to be obtained. Surface topography analysis was performed on the entire fracture using height parameters and functional parameters (volume) in accordance with ISO 25178, as was the fractal dimension.
Tendencies of changes in height, functional and fractal fracture surface texture parameters for three types of loadings were analysed. The examined fracture surfaces showed the dependence of the loading history on their topography. Parameters that were responsive to surface irregularities were selected, because they can be used, for example, to investigate the causes of material damage. Regression analysis of the relationship between values of areal parameters was also carried out.
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•The effect of the percentage shares of bending and torsional loadings on the fracture surface was evaluated.•Surface parameters were evaluated for entire fracture areas of 10HNAP ring notched specimens.•The relationship between areal surface texture parameters following random fatigue tests was analysed.
This work presents the relationship between fracture surface morphology, fatigue loading conditions and notch radius. Some specimens have been destroyed during fatigue tests under bending with ...torsion. Then, the fracturing surfaces of the rectangular cross-section specimens AW-2017A-T4 with notches have been analysed.
This study presents fractal analysis for quantification of the geometry of the fracture surface. Surface geometry analysis is carried out on the whole fracture surface, using fractal dimensions and, surface isotropy. Fracture surfaces are observed using a focus variation microscope (FVM), which allows the acquisition of data sets with large depth of focus.
A correlation between fractal dimension and stress concentrator, fatigue loading history, and total fatigue life is examined. These systematic dependencies may serve as a basis for extracting fatigue loading information from fracture surfaces of destroyed materials and structures.
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•The effects of the fatigue loading history and notch geometry on the fracture surface are evaluated.•Fractal based characterisation is used.•Fractal dimension in the context of the fatigue fracture surface description is checked.•Surface morphology is evaluated on the total areas of fractures.
Particle shape affects the mechanical behaviour of soil and is thus a parameter of interest in geotechnical engineering. Shape is commonly described by form, angularity and roughness. Form describes ...the overall aspect ratio, angularity the sharpness of the edges and corners, and roughness the small surface irregularities. This work explores the characterisation of form and angularity of sand particles. Our results show that focus variation microscopy principles can be implemented in a conventional compound microscope to measure particle heights as small as 60 μm without having to observe a lateral view of the particle. The robustness of the procedure is demonstrated by implementing it on sand-sized particles from six different sources. Importantly, the compound microscope employed by the procedure is likely to be accessible to many soil laboratories. Heights measured using focus variation were used to assess particle form. Contrary to assumptions in previous works, form varied significantly within a given soiltype and a narrow particle size range. Regarding angularity, there is a systematic correlation between particle form and the angularity metric known as 'ellipseness'. Furthermore, while ellipseness is adequate to distinguish between angular and rounded particles, it cannot distinguish between sub-rounded and well-rounded particles.
Estimating a 3D shape from 2D images is a classic computer vision problem. Shape from focus is a commonly used method for this purpose. With shape from focus, 3D depth is estimated using a so-called ...focus measure operator. Pixel focus follows a Gaussian-like distribution in which the location of the peak is an indicator of the 3D depth. Locating the peak in this distribution is complicated due to noise coming from various sources. We investigate the accuracy of some existing algorithms and introduce a new algorithm based on phase correlation. Phase correlation is a powerful method for finding correlations between signals, especially in a noisy environment. The accuracy and robustness to noise of the proposed method are tested and proven by applying it to synthetic data as well as measurements of a calibration target. The proposed method is over 30% more accurate than comparable methods, yet requires more computational effort.
•Novel peak detection method for shape from focus.•Phase correlation can be used for precision shape from focus measurements.•Slower but more accurate compared to default methods.•3D Surface Reconstruction.
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•Three preparation methods for making solid dispersion investigated.•UV imaging of pseudo IDR showed web-like strand migrating to the top of quartz cell potentially responsible for ...low IDR values.•Capsule tip coming off for drug dissolution to occur UV imaged for the first time.•Solid dispersions in ratio 1:1 and 1:3 sufficient to show significant dissolution profiles from UV imaging.
This work explores the use of UV imaging in solid dispersion systems. Solid dispersions are one of the common strategies used in improving the dissolution of poorly soluble drugs. Three manufacturing techniques (spray drying (SD), freeze drying (FD) and homogenising (HG)) are investigated. Differential Scanning Calorimetry (DSC) and X-Ray Powder Diffraction (XRPD) was used in characterising the solid dispersions. Advanced imaging was implemented to give an insight into how these solid dispersions performed. The DSC and XRPD results showed that all three methods and the various ratios studied produced amorphous solid dispersions. Ultra-Violet (UV) imaging of the pseudo Intrinsic Dissolution Rate (IDR) deduced only two samples to have superior pseudo IDR values to the IDR of the parent drug indomethacin (INDO). The whole dose imaging of the capsule formulation however showed all the samples (SD, FD and HG) to have superior dissolution to that of INDO which was in contrast to the IDR results. The UV images obtained from the determination of the pseudo IDR also showed a phenomenon the authors are reporting for the first time where increased polymer (Soluplus) content produced “web-like” strands that migrated to the top of the quartz cell which may have been responsible for the low pseudo IDR values. The authors also report for the first time using this UV imaging technique, the tip of a capsule coming off for drug to go into solution. The area under the curve suggested the best five samples dissolution wise to be 1:3 SD > 1:1 HG > 1:1 SD > 1:3 FD > 1:3 HG meaning a ratio of INDO to SOL in these dispersion of up to 1:3 being sufficient to produce significant dissolution increases. The developed interfacial (surface) area ratio (Sdr) highlighted how the surface area of the IDR compacts varied between the batches, in particular highlighting larger surface area gains for the FD and HG compacts. A choice of instrumentation/techniques to use in making solid dispersions may well come down to cost or instrument availability for a formulator as all three techniques were successful in improving the dissolution of indomethacin. This work thus highlights the importance of having both complimentary IDR and whole dosage imaging techniques in giving a better understanding of solid dispersion systems.
In this work, the performance of a focus variation instrument for measurement of areal topography of metal additive surfaces was investigated. Samples were produced using both laser and electron beam ...powder bed fusion processes with some of the most common additive materials: Al-Si-10Mg, Inconel 718 and Ti-6Al-4V. Surfaces parallel and orthogonal to the build direction were investigated. Measurement performance was qualified by visually inspecting the topographic models obtained from measurement and quantified by computing the number of non-measured data points, by estimating local repeatability error in topography height determination and by computing the value of the areal field texture parameter Sa. Variations captured through such indicators were investigated as focus variation-specific measurement control parameters were varied. Changes in magnification, illumination type, vertical resolution and lateral resolution were investigated. The experimental campaign was created through full factorial design of experiments, and regression models were used to link the selected measurement process control parameters to the measured performance indicators. The results indicate that focus variation microscopy measurement of metal additive surfaces is robust to changes of the measurement control parameters when the Sa texture parameter is considered, with variations confined to sub-micrometre scales and within 5% of the average parameter value for the same surface and objective. The number of non-measured points and the local repeatability error were more affected by the choice of measurement control parameters. However, such changes could be predicted by the regression models, and proved consistent once material, type of additive process and orientation of the measured surface are set.
Tool wear, caused by high machining temperatures, cutting speed or mechanical load, can have various characteristics. Current solutions for metrological quantification are limited with respect to ...their viewing dependency and user influence. Here, a measurement solution which is based on 3D focus variation measurements is presented. The quantification is carried out by the automatic evaluation of flank wear parameters (ISO 3685:1993, ISO 8688-1:1989) and plastic deformation impression and depression parameters on 3D dataset series. This allows the visualization and assessment of wear over a period of time and provides crucial information for the manufacturing and machining process.
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