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Information-rich surface metrology
Abstract
Published in Commercial Micro Manufacturing
... Intelligence refers to the challenges to build intelligent in-line optical instruments and includes the utilisation and application of machine learning (ML) methods, that are only now being utilised for measurement applications, to enhance the capability and performance of the instruments, for example, the capability to understand surface orientations [13] , to automatically segment 3D point clouds [14] and to infer surface information from missing data using a priori information [15] . Recently, deep learning neural network methods have been used in many applications, for example, to automatically segment objects, especially for machine vision applications [16,17] . ...
... An IRM framework is an essential element and the foundation of the proposed methodology [15,82] . IRM is a term referring to the use of any available information that can be included to improve a measurement process [15,82] . ...
... An IRM framework is an essential element and the foundation of the proposed methodology [15,82] . IRM is a term referring to the use of any available information that can be included to improve a measurement process [15,82] . The available information can be information about a measured object, a manufacturing process that makes the object, the instrument-surface interaction, optical instrument characteristics. ...
The productivity rate of a manufacturing process is limited by the speed of any measurement processes at the quality control stage. Fast and effective in-line measurements are required to overcome this limitation. Optical instruments are the most promising methods for in-line measurement because they are faster than tactile measurements, able to collect high-density data, can be highly flexible to access complex features and are free from the risk of surface damage. In this paper, a methodology for the development of fast and effective in-line optical measuring instruments for the surfaces of parts with millimetre- to micrometre-size is presented and its implementation demonstrated on an industrial case study in additive manufacturing. Definitions related to in-line measurement and barriers to implementing in-line optical measuring instruments are discussed.
... Dzięki bardzo różnym pasmom przenoszenia można wydzielić z powierzchni szereg jej składowych, co pokazano na rys. 9 [12]. Zastosowano odporny filtr Gaussa (odpowiednio: HP - górnoprzepustowy, LP - dolnoprzepustowy, BP - pasmowoprzepustowy) o wartości odcięcia (na rys. 9 oznaczonej jako L): 6,9,10,13,15,19,23,29,36,45,56,74,99,127,178, 297 i 446 μm. ...
... Takie podejście do pomiarów nierówności powierzchni wpisuje się również w rozwijaną ostatnio strategię metrologii powierzchni bogatej w informacje (information-rich surface metrology), wykorzystującej nie tylko wyniki pomiaru, ale i wiedzę związaną z jego uwarunkowaniami. Pokazano to na rys. 10 [13]. ...
... Można ją podzielić na trzy etapy (przykład na rys. 11) [13]: identyfikację cechy (cecha jest identyfikowana za pomocą szablonu kształtu i wielkości podanych w informacjach referencyjnych), wyodrębnienie cechy (izolacja cechy z bazowego zbioru jako niezależnego tworu geometrycznego) i charakteryzację cechy (opis cechy pod kątem wielkości, kształtu i parametrów). ...
In the paper a concept of length and angle metrology in fourth industrial revolution known as Industry 4.0 was presented. Problems and conditions as well as limitations connected with measurement possibilities from devices and man point of view were shown. Scale as metrology term with its division to different ranges, i.e. macro, micro and meso were described. For each of these areas digitization and its tasks were presented.
... AM technologies have been documented as an example where advanced measurement techniques are needed due to complex geometries and a lack of uniform material properties [19]. Therefore, a wide range of sensors, such as visual cameras, infrared thermometers, acoustic emission (AE) measurements, vibration sensors, and accelerometers, is employed to collect the data during the printing process, monitor the printer's health conditions, and detect product anomalies [20]. ...
To improve additive manufacturing (AM), from being limited to creating prototypes to fabricating functional parts with low failure rates and high precision, several challenges have to be addressed. In-situ AM process monitoring plays a central role in the quality assurance of fabricated parts during the actual build job. This paper studies the feasibility of utilizing long short-term memory (LSTM) networks in the real-time monitoring of fused deposition modeling (FDM) processes for detecting pre-specified types of anomalies. Several hybrid LSTM models are developed and validated using the time-series sensor data collected during the operation of a Delta 3D printer. In particular, two distinct approaches are tailored to pre-process the sensor data before being fed into the LSTM classifiers: (i) a handcrafted feature extraction method that leverages statistical abstractions of the data; and (ii) an intelligent feature extraction method through the so-called anomaly images, adopted from the human activity recognition literature. The results show that all image-based LSTM models are more reliable and robust against noise than the models trained using handcrafted feature extraction. The highest mean accuracy of the LSTM models is 99.85%, and the required time for a prediction task is sub-millisecond, making the model feasible for real-time process monitoring and anomaly detection. It is also shown that the proposed system substantially outperforms the traditional machine learning alternatives.
... This is a determinant of the emergence of techniques integrating measurements at different scales, both in terms of hardware and software. The combination of data from different scales in a single model allows, among others, the use of data set in advanced simulations, and the use of the information rich metrology concept [25]. ...
In the paper a possibility of drones application in length and angle metrology was discussed. Some basic issues of metrology in mechanical engineering scale was presented. The use of drones for micro, meso and macro scale was briefly described. Different options and configurations were shown, including benefits and possible problems. Uncertainty issues were also discussed. From that point of view the future of drones in metrology looks bright, as it is also in other areas of human life. Due to rising labor costs, replacing a human being by a system solution is very desirable.
... Senin and Leach [58] developed a smart information-rich surface metrology technique using multi-sensor data fusion and ML. They identified AM as an example where advanced measurement techniques are needed due to complex geometries and lack of uniform material properties. ...
Variability in product quality continues to pose a major barrier to the widespread application of additive manufacturing (AM) processes in production environment. Towards addressing this barrier, monitoring AM processes and measuring AM materials and parts has become increasingly commonplace, and increasingly precise, making a new wave of AM-related data available. This newfound data provides a valuable resource for gaining new insight to AM processes and decision making. Machine Learning (ML) provides an avenue to gain this insight by 1) learning fundamental knowledge about AM processes and 2) identifying predictive and actionable recommendations to optimize part quality and process design. This report presents a literature review of ML applications in AM. The review identifies areas in the AM lifecycle, including design, process plan, build, post process, and test and validation, that have been researched using ML. Furthermore, this report discusses the benefits of ML for AM, as well as existing hurdles currently limiting applications.
... Intelligent behaviour is achieved through automated self-assessment of measurement performance, while the measurement itself is being executed [1]. The decisional process is supported by multiple sources of information [2], namely: knowledge of part specifications (CAD model, dimensional and geometric tolerances, materials); knowledge of the manufacturing process and the material, leading to predictability of likely types of form error; knowledge of the measurement instrument itself (metrological performance and behaviour), and how it is expected to interact with any specific material and part geometry. The optical measurement technologies covered by the project produce point clouds: the work presented in this paper focuses on algorithmic processing of point clouds, and deals with the following, specific challenges: a) automated point cloud localisation within the part geometry, i.e. identifying what surfaces have been captured by any given point cloud, acquired from a part of unknown position and orientation; b) automated assessment of coverage and sampling density for the exposed surfaces, including recognition of critical regions (i.e. ...
... Therefore, colour information-based surface roughness measurement methods are often simple and easy to understand. Additionally, compared with grey information-based feature indices, colour information-based feature indices have the advantage of being able to account for more information, which can better objectively represent a rough surface [40,41,42]. ...
This paper conducts a series of imaging experiments under different conditions to optimize the experimental parameters in the colour image-based roughness measurement method. The conditions consist of three colour blocks (a red-green (RG) colour block, red-blue (RB) colour block, and blue-green (BG) colour block), two roughness ranges and four light source brightness levels. The results show that the assessment effect of the HVS and the performance of the CDSM-based feature indices can be improved by using an RB colour block; the resolution of the HVS-based surface roughness evaluation method decreases with the increase in surface roughness; the energy index Ep can be used to measure a grinding surface with 0 Ra 0.1 μm (100 nm) with a mean absolute error (MAE) of 10.7 nm; even under low energy field, the selected feature indices can be used to measure grinding surface roughness, which is significant for energy saving.
... The involvement of digital technologies in most rapid product development and fabrication processes, in particular when additive manufacturing is involved, gives rise to numerous information sources that could be exploited to develop smarter measurement solutions. Information-rich metrology (IRM) is a recently introduced paradigm [2] which promotes the development of smart, digital measurement systems that can make use of any available source of information (a priori or from sensors) to automatically plan and optimise a measurement process, or correct it during execution. Sources of information may pertain to the object being measured, the measurement system itself and its interaction with the part materials and surfaces, or the environment where the measurement is taking place. ...
As part of a project to develop a smart 3D form measurement system for quality control of complex 3D parts, we present early work in algorithmic assessment of coverage achieved on the surfaces of a part subjected to optical measurement from a single pose. The method performs an automated detection of pose by finding the best-matching position of the measured point cloud to a reference CAD model. The point cloud is then partitioned by associating measured points to individual CAD surfaces and coverage quality indicators, such as sampling density and covered area, are computed for each surface. The method is developed as part of a smart measurement solution that will provide real-time feedback to the measurement system on the success of the measurement acquisition and autonomously adapt the measurement strategy for complex 3D geometries in real-time to achieve an optimised measurement result. As proof of concept, a prototype implementation is presented that involves the combination of commercial measurement hardware and 3D modelling software components. Form metrology, smart optical systems, adaptive measurement, geometric alignment of point clouds and CAD geometry, geometric sampling and coverage.
The objective of this work is to investigate the relationship between wettability and surface microgeometry of 6060 aluminum alloy created by electric discharge machining (EDM). The analyzes are enriched with the calculation of the correlation strengths between contact angles and geometric characteristics of surface topographies changing with the scale of observations. Surface topographies are measured by focus variation microscope and characterized with ISO parameters, geometric motifs and multiscale curvature tensor analysis. The wettability of the finished structures is investigated indirectly by contact angle measurements. The analysis were carried out using aqueous solutions of the semi-synthetic polymer, with different concentration and viscosity. The study showed that wetting behaviour of aluminum alloy can be easily controlled through appropriate EDM finishing.
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.
The speed of manufacturing processes today depends on a trade-off between the physical processes of production, the wider system that allows these processes to operate and the co-ordination of a supply chain in the pursuit of meeting customer needs. Could the speed of this activity be doubled? This paper explores this hypothetical question, starting with examination of a diverse set of case studies spanning the activities of manufacturing. This reveals that the constraints on increasing manufacturing speed have some common themes, and several of these are examined in more detail, to identify absolute limits to performance. The physical processes of production are constrained by factors such as machine stiffness, actuator acceleration, heat transfer and the delivery of fluids, and for each of these, a simplified model is used to analyse the gap between current and limiting performance. The wider systems of production require the co-ordination of resources and push at the limits of human biophysical and cognitive limits. Evidence about these is explored and related to current practice. Out of this discussion, five promising innovations are explored to show examples of how manufacturing speed is increasing - with line arrays of point actuators, parallel tools, tailored application of precision, hybridisation and task taxonomies. The paper addresses a broad question which could be pursued by a wider community and in greater depth, but even this first examination suggests the possibility of unanticipated innovations in current manufacturing practices.
With the definition and further standardisation of 2.5-D roughness measuring methods and parameters, the demand of traceability and uncertainty estimation for measurements and parameters automatically becomes eminent. This paper gives an overview of the problems and possibilities that appear when uncertainties have to be put to values that are derived from a measured surface topography such as: the Ra-value of a periodic specimen, the RSm-value of a typeD standard, the Sa-value of a single cutoff length of a type D standard. It is shown that straightforward implementation of the methods described in the GUM leads to impossible and impracticable equations because of the correlations between some millions of measurement points. A practical solution is found in taking the main aspects of uncertainty, as these are given in the recent ISO 25178 standards series and apply these to a measured surface topography as a whole.
The measurement and characterisation of surface topography is crucial to modern manufacturing industry. The control of areal surface structure allows a manufacturer to radically alter the functionality of a part. Examples include structuring to effect fluidics, optics, tribology, aerodynamics and biology. To control such manufacturing methods requires measurement strategies. There is now a large range of new optical techniques on the market, or being developed in academia, that can measure areal surface topography. Each method has its strong points and limitations. The book starts with introductory chapters on optical instruments, their common language, generic features and limitations, and their calibration. Each type of modern optical instrument is described (in a common format) by an expert in the field. The book is intended for both industrial and academic scientists and engineers, and will be useful for undergraduate and postgraduate studies.
Despite the advancement of additive manufacturing/3-dimensional (3D) printing, single-step fabrication of multifunctional parts using AM is limited. With the view of enabling multifunctional AM (MFAM), in this study, sintering of metal nanoparticles was performed to obtain conductivity for continuous line inkjet printing of electronics. This was achieved using a bespoke three dimensional (3D) inkjet-printing machine, JETx®, capable of printing a range of materials and utilizing different post processing procedures to print multi-layered 3D structures in a single manufacturing step. Multiple layers of silver were printed from an ink containing silver nanoparticles (AgNPs) and infra-red sintered using a swathe-by-swathe (SS) and layer-by-layer sintering (LS) regime. The differences in the heat profile for the SS and LS was observed to influence the coalescence of the AgNPs. Void percentage of both SS and LS samples was higher towards the top layer than the bottom layer due to relatively less IR exposure in the top than the bottom. The results depicted a homogeneous microstructure for LS of AgNPs and showed less deformation compared to the SS. Electrical resistivity of the LS tracks (13.6 ± 1µ cm) was lower than the SS tracks (22.5 ± 1 µ cm). This study recommends the use of LS method to sinter the AgNPs to obtain a conductive track in 25% less time than SS method for MFAM.
A comprehensive analysis of literature pertaining to surface texture metrology for metal additive manufacturing has been performed. This review paper structures the results of this analysis into sections that address specific areas of interest: industrial domain, additive manufacturing processes and materials; types of surface investigated; surface measurement technology and surface texture characterisation. Each section reports on how frequently specific techniques, processes or materials have been utilised and discusses how and why they are employed. Based on these results, possible optimisation of methods and reporting is suggested and the areas that may have significant potential for future research are highlighted.
Selective Laser Sintering (SLS) is an additive manufacturing technique whereby a laser melts polymer powder layer by layer to generate three-dimensional parts. It enables the fabrication of parts with high degrees of complexity, nearly no geometrical restrictions, and without the necessity of a tool or a mold. Due to the orientation in the building space, the processing parameters, and the powder properties, the resulting parts possess an increased surface roughness. In comparison to other manufacturing techniques, e.g. injection molding, the surface roughness of SLS parts results from partially melted powder particles on the surface layer. The actual surface roughness must thus be characterized with respect to the part's eventual application. At the moment, there is no knowledge regarding which measuring technique is most suitable for detecting and quantifying SLS parts' surface roughness. The scope of this paper is to compare tactile profile measurement methods, as established in industry, to optical measurement techniques such as Focus Variation, Fringe Projection Technique (FPT), and Confocal Laser Scanning Microscope (CLSM). The advantages and disadvantages of each method are presented and, additionally, the effect of tactile measurement on a part's surface is investigated.
Tessellated surfaces are a class of structured surfaces where texture has been engineered to reproduce a periodic pattern, specifically designed to meet a functional requirement. Despite having gained considerable acceptance in industrial production, tessellated surfaces still pose considerable challenges in terms of their metrological verification. The small scale of the dominant texture features requires the application of instruments typical of surface metrology; however, the computation of conventional surface texture parameters generally is not sufficient to capture the geometric properties and regularity aspects, which are fundamental for a complete characterisation of the pattern. In the work reported here, the characterisation of a periodic texture pattern is approached as a dimensional metrology problem, where the aim is the determination of target dimensional and geometric properties directly mapped to the design specifications. To illustrate the approach presented in this paper a specific test case, involving laser textured dimpled patterns designed to reduce friction in bearing applications, has been selected. This test case is used to highlight the many issues and critical aspects involved in the characterisation of tessellated surfaces.
This paper gives an overview of the progress which has been made in surface metrology over the past ten years. It updates the surface classification system, and discusses the practical and theoretical reasons for the technological shifts which have occurred. This includes the use of surfaces with predetermined features as an alternative to traditional machined surfaces, and the move from simple to freeform shapes. The paper discusses technological shifts in association, filtration, numeric parametric techniques, fractals associated with function and standardisation. Many examples are given in order to contextualise the significance of these technological changes. This paper should help to predict the direction of future developments in surface metrology, and therefore emphasise its importance in functional applications in advanced manufacture.
To extract patterns from observable measurements we need to be able to define and identify stable features in observable measurements that persist in the presence of small artificial features such as noise, measurement errors, etc. The representational theory of measurement is used to define the stability of a measurement procedure. A technique, 'motif analysis', is defined to identify and remove 'insignificant' features while leaving 'significant' features. This technique is formalized and three properties identified that ensure stability. The connection of motif analysis with morphological closing filters is established and used to prove the stability of motif analysis. Finally, a practical metrology example is given of motif analysis in surface texture. Here motif analysis is used to segment a surface into its significant features.
This paper describes future trends in surface metrology. Measurement techniques are briefly mentioned. A special attention was paid to tactile and optical methods. Selected problems of surface topography characterization are described. The effects of sampling and filtering on surface topography representation are analysed. Structured surfaces are becoming both technologically and economically critical. Therefore their description is a problem of a great practical importance. Multi-process textures are very important from functional point of view. Various methods of their description are compared. Surface texturing as a means for enhancing tribological properties of frictional pairs started to be extremely popular from for about last 10 years. The effects of surface texturing on improving tribological properties of sliding assemblies are analysed. The other influences of surface topography are mentioned in this paper.
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