Defect and thickness inspection system for cast thin films using machine vision and full-field transmission densitometry

Quick mass production of homogeneous thin film material is required in paper, plastic, fabric, and thin film industries. Due to the high feed rates and small thicknesses, machine vision and other nondestructive evaluation techniques are used to ensure consistent, defect-free material by continuously assessing post-production quality. One of the fastest growing inspection areas is for 0.5-500 micrometer thick thin films, which are used for semiconductor wafers, amorphous photovoltaics, optical films, plastics, and organic and inorganic membranes. As a demonstration application, a prototype roll-feed imaging system has been designed to inspect high-temperature polymer electrolyte membrane (PEM), used for fuel cells, after being die cast onto a moving transparent substrate. The inspection system continuously detects thin film defects and classifies them with a neural network into categories of holes, bubbles, thinning, and gels, with a 1.2% false alarm rate, 7.1% escape rate, and classification accuracy of 96.1%. In slot die casting processes, defect types are indicative of a misbalance in the mass flow rate and web speed; so, based on the classified defects, the inspection system informs the operator of corrective adjustments to these manufacturing parameters. Thickness uniformity is also critical to membrane functionality, so a real-time, full-field transmission densitometer has been created to measure the bi-directional thickness profile of the semi-transparent PEM between 25-400 micrometers. The local thickness of the 75 mm x 100 mm imaged area is determined by converting the optical density of the sample to thickness with the Beer-Lambert law. The PEM extinction coefficient is determined to be 1.4 D/mm and the average thickness error is found to be 4.7%. Finally, the defect inspection and thickness profilometry systems are compiled into a specially-designed graphical user interface for intuitive real-time operation and visualization.M.S.Committee Chair: Tequila Harris; Committee Member: Levent Degertekin; Committee Member: Wayne Dale

Interferometer response characterization algorithm for multi-aperture Fabry-Perot imaging spectrometers

In recent years, the demand for hyperspectral imaging devices has grown significantly, driven by their ability of capturing high-resolution spectral information. Among the several possible optical designs for acquiring hyperspectral images, there is a growing interest in interferometric spectral imaging systems based on division of aperture. These systems have the advantage of capturing snapshot acquisitions while maintaining a compact design. However, they require a careful calibration to operate properly. In this work, we present the interferometer response characterization algorithm (IRCA), a robust three-step procedure designed to characterize the transmittance response of multi-aperture imaging spectrometers based on the interferometry of Fabry-Perot. Additionally, we propose a formulation of the image formation model for such devices suitable to estimate the parameters of interest by considering the model under various regimes of finesse. The proposed algorithm processes the image output obtained from a set of monochromatic light sources and refines the results using nonlinear regression after an ad-hoc initialization. Through experimental analysis conducted on four different prototypes from the Image SPectrometer On Chip (ImSPOC) family, we validate the performance of our approach for characterization. The associated source code for this paper is available at https://github.com/danaroth83/irca.Comment: 20 pages, 11 figures. (Revised structure, added experiments

In-line quality control for Zero Defect Manufacturing: design, development and uncertainty analysis of vision-based instruments for dimensional measurements at different scales

Lo scopo di questo progetto di dottorato industriale finanziato attraverso una borsa di studio della Regione Marche è stato quello di sviluppare ricerca con potenziale impatto su un settore industriale, promuovere il coinvolgimento delle fabbriche e delle imprese locali nella ricerca e innovazione svolta in collaborazione con l'università e produrre ricerca in linea con le esigenze dell'ambiente industriale, non solo a livello regionale. Quindi, attraverso la collaborazione con una torneria locale (Zannini SpA) e una piccola azienda high-tech focalizzata sull'introduzione dell'innovazione meccatronica nel settore della tornitura (Z4Tec srl), e anche grazie a una collaborazione internazionale con l'Università di Anversa, abbiamo progettato e sviluppato nuovi strumenti per il controllo qualità in linea, basati su tecnologie senza contatto, in particolare tecnologie elettro-ottiche. Portando anche l'attenzione sull'importanza di prendere in considerazione l'incertezza, poiché è fondamentale nel processo decisionale basato sui dati che sono alla base di una strategia di Zero Defect Manufacturing. Infatti, la scarsa qualità delle misure può pregiudicare la qualità dei dati. In particolare, questo lavoro presenta due strumenti di misura che sono stati progettati e sviluppati con lo scopo di effettuare controllo qualità in linea di produzione e l’incertezza di misura di ogni strumento è stata analizzata in confronto ad altri strumenti presenti sul mercato. Nella parte finale di questo lavoro si è valutata l’incertezza di un profilometro a triangolazione di linea laser. Pertanto, la ricerca condotta in questa tesi può essere organizzata in due obiettivi principali: lo sviluppo di nuovi sistemi di misura dimensionale basati sulla visione da implementare in linea di produzione e l'analisi dell'incertezza di questi strumenti di misura. Per il primo obiettivo ci siamo concentrati su due tipi di misure dimensionali imposte dall'industria manifatturiera: macroscopiche (misure in mm) e microscopiche (misure in µm). Per le misure macroscopiche l'obiettivo era il controllo in linea della qualità dimensionale di pezzi torniti attraverso la profilometria ottica telecentrica. Il campione da ispezionare è stato posto tra l'illuminatore e l'obiettivo per ottenere la proiezione dell'ombra del campione. Le misure sono state eseguite mediante analisi grafica dell'immagine. Abbiamo discusso le disposizioni meccaniche mirate a ottimizzare le immagini acquisite e i problemi che eventuali disallineamenti meccanici dei componenti potrebbero introdurre nella qualità delle immagini. Per le misure microscopiche abbiamo progettato un sistema di misurazione della rugosità superficiale basato sulla visione retroilluminata, con l'obiettivo di determinare le condizioni ottimali di imaging utilizzando la modulation transfer function e l'uso di una electrically tunable lens. Un campione tornito (un cilindro) è posto di fronte a una telecamera ed è retroilluminato da una sorgente di luce collimata; tale configurazione ottica fornisce l'immagine del bordo del campione. Per testare la sensibilità del sistema di misura è stata utilizzata una serie di campioni di acciaio torniti con diverse rugosità superficiali. Per il secondo obiettivo, le tecniche di valutazione dell'incertezza di misura utilizzate in questo lavoro sono state un'analisi dell'incertezza statistica di tipo A e un'analisi Gage R&R. Nel caso del profilometro telecentrico, l'analisi è stata eseguita in confronto con altri dispositivi presenti sul mercato con un'analisi di tipo A e una Gage R&R. L'incertezza di misura del profilometro si è rivelata sufficiente per ottenere risultati nell'intervallo di tolleranza richiesto. Per il sistema di visione retroilluminato, il confronto dei risultati è stato effettuato con altri strumenti allo stato dell'arte, con un'analisi di Tipo A. Il confronto ha mostrato che le prestazioni dello strumento retroilluminato dipendono dai valori di rugosità superficiale considerati; mentre a valori maggiori di rugosità l'offset aumenta, per valori inferiori di rugosità i risultati sono compatibili con quelli dello strumento di riferimento (a stilo). Infine, sono state valutate la ripetibilità e la riproducibilità di un profilometro a triangolazione di linea laser, attraverso uno studio Gage R&R. Ogni punto di misura è stato ispezionato da tre operatori e l'insieme dei dati è stato elaborato con un'analisi dell'incertezza di Tipo A. Successivamente, uno studio Gage R&R ha contribuito a indagare la ripetibilità, la riproducibilità e la variabilità del sistema. Questa analisi ha dimostrato un'incertezza accettabile.The purpose of this industrial PhD project financed through a scholarship from the Regione Marche was to develop research with potential impact on an industrial sector, to promote the involvement of local factories and companies in research and innovation performed jointly with the university and to produce research in line with the needs of the industrial environment, not only at regional level. Hence, through collaborating with a local turning factory (Zannini SpA) and a small high-tech company focused on introducing mechatronic innovation in the turning sector (Z4Tec srl), and also thanks to an international collaboration with the University of Antwerp, we designed and developed new instruments for in-line quality control, based on non-contact technologies, specifically electro-optical technologies. While also bringing attention to the importance of taking uncertainty into consideration, since it is pivotal in data-based decision making which are at the base of a Zero Defect Manufacturing strategy. This means that poor quality of measurements can prejudice the quality of the data. In particular, this work presents two measurement instruments that were designed and developed for the purpose of in-line quality control and the uncertainty of each of the two instruments was evaluated and analyzed in comparison with instruments already present on the market. In the last part of this work, the uncertainty of a hand-held laser-line triangulation profilometer is estimated. Hence, the research conducted in this thesis can be organized in two main objectives: the development of new vision-based dimensional measurement systems to be implemented in production line and the uncertainty analysis of these measurement instruments. For the first objective we focused on two types of dimensional measurements imposed by the manufacturing industry: macroscopic (measuring dimensions in mm) and microscopic (measuring roughness in µm). For macroscopic measurements the target was the in-production dimensional quality control of turned parts through telecentric optical profilometry. The sample to be inspected was placed between illuminator and objective in order to obtain the projection of the shadow of the sample over a white background. Dimensional measurements were then performed by means of image processing over the image obtained. We discussed the mechanical arrangements targeted to optimize images acquired as well as the main issues that eventual mechanical misalignments of components might introduce in the quality of images. For microscopic measurements we designed a backlit vision-based surface roughness measurement system with a focus on smart behaviors such as determining the optimal imaging conditions using the modulation transfer function and the use of an electrically tunable lens. A turned sample (a cylinder) is placed in front of a camera and it is backlit by a collimated source of light; such optical configuration provides the image of the edge of the sample. A set of turned steel samples with different surface roughness was used to test the sensitivity of the measurement system. For the second objective, the measurement uncertainty evaluation techniques used in this work were a Type A statistical uncertainty analysis and a Gage R&R analysis. In the case of the telecentric profilometer, the analysis was performed in comparison with other on-the-market devices with a Type A analysis and a Gage R&R analysis. The measurement uncertainty of the profilometer proved to be sufficient to obtain results within the tolerance interval required. For the backlit vision system, the comparison of the results was made with other state-of-the-art instruments, with a Type A analysis. The comparison showed that the performance of the backlit instrument depends on the values of surface roughness considered; while at larger values of roughness the offset increases, the results are compatible with the ones of the reference instrument (stylus-based) at lower values of roughness. Lastly, the repeatability and reproducibility of a laser-line triangulation profilometer were assessed, through a Gage R&R study. Each measuring point was inspected by three different operators and the data set has been, at first, processed by a Type A uncertainty analysis. Then, a Gage R&R study helped investigate repeatability, reproducibility and the system variability. This analysis showed that the presented laser-line triangulation system has an acceptable uncertainty

Using Color in Machine Vision Systems for Wood Processing

Color information, already shown to be valuable in distinguishing wood surface features, should prove especially useful for future applications of machine vision in the wood products industry. This review provides investigators interested in such applications with the information necessary for understanding the benefits-and associated difficulties-of using color. Various standard color-measurement systems ("color spaces") are discussed. No one system has been completely successful, at least partly because simple physical measurements are difficult to correlate with a human observer's complex perception of color. Color video camera systems, designed with human viewers in mind, have the potential for machine vision applications, but certain system "features" (white balance, gamma or contour correction) could cause problems. Future applications, including detecting and classifying hard-to-identify defects and matching colors of wood components, will require careful choice of lighting geometry and source, camera system, and color space for the purpose at hand

Compressed sensing current mapping spatial characterization of photovoltaic devices

In this work a new measurement technique for current mapping of photovoltaic (PV) devices is developed, utilising the compressed sensing (CS) sampling theory. Conventional current mapping measurements of PV devices are realised using the light beam induced current (LBIC) measurement method. For its realization, a light beam scans a PV device and the induced current is measured for every point, generating the final current map of the device. Disadvantages of the LBIC method are the low measurement speed, the complicated and usually expensive measurement layouts and the impractical application of the method on PV modules. With the development of CS current mapping in this work, the above issues can be mitigated. Instead of applying a raster scan, a series of illumination patterns are projected onto the PV sample, acquiring fewer measurements than the pixels of the final current map. The final reconstruction of the current map is achieved by means of an optimisation algorithm. Spatially resolved electrical simulations of CS current mapping demonstrate that theoretically the proposed method is feasible. In addition, it is shown that current maps can be acquired with even 40% of the measurements a standard LBIC system would require, saving a significant amount of measurement time. The performance of CS current mapping is the same, regardless of the features a sample may contain and measurements can be applied to any type of photovoltaic device. The ability of the method to provide current maps of PV modules is demonstrated. The performance of several reconstruction algorithms is also investigated. An optical measurement setup for CS current mapping of small area PV devices was built at the National Physical Laboratory (NPL), based on a digital micromirror device (DMD). Accurate current maps can be produced with only 40% of the measurements a conventional point by point scan would need, confirming simulation results. The measurement setup is compact, straightforward to realise and uses a small number of optical elements. It can measure a small area of 1cm by 1cm, making it ideal for current mapping of small research samples. A significant signal amplification is achieved, since the patterns illuminate half of the sample. This diminishes the use of lock-in techniques, reducing the cost for current mapping of PV devices. Current maps of an optical resolution up to 27μm are acquired, without the use of any demagnification elements of the projected pattern that the DMD generates. v A scale up of this new current mapping method is demonstrated using Digital Light Processing (DLP) technology, which is based on DMD chips. A commercial DLP projector is utilised for building a proof of concept CS current mapping measurement system at the Centre of Renewable Energy Systems Technology (CREST). Current maps of individual PV cells in encapsulated modules can be acquired, something that is extremely difficult to achieve with conventional LBIC systems. Direct current mapping of a PV module with by-pass diodes is successfully applied for the first time. Specific shading strategies are developed for this purpose in order to isolate the cell under test. Due to the application of compressive sampling, current maps are acquired even if the signal-to-noise-ratio levels are so low that a point by point scan is not possible. Through the above implementations of CS current mapping of this work, the proposed technique is studied and evaluated. The results demonstrate that this novel method can offer a realistic alternative approach for current mapping of PV cells and modules that can be cost effective and straightforward to implement. In addition, this work introduces the application of the CS theory and DLP technology to PV metrology in general

Aesthetics and Gloss of Ground Surfaces: A Review on Measurement and Generation

Visual appearance of an object significantly influences a consumer's choice and largely controls the market economy. The perceived quality of products is governed by surface's optical properties (reflection, refraction, etc.), geometrical properties (roughness, waviness, etc.), and chemical properties (oxide layer formation, thermal variation, etc.). Surface shininess attracts researchers from many different disciplines, in particular manufacturing, metrology, psychology, physiology, and computer science. Unfortunately, there are still huge knowledge gaps on characterizing and appraising shiny surfaces in a reproducible way. This paper introduces the main definitions and physics of shininess and gloss, methods of gloss sensing, and relates these definitions and methods to surface generation by grinding. Automated gloss measurement is difficult in particular for free-form surfaces, and optical quality is still often evaluated by human workers. Gloss models are often based on the bidirectional reflection distribution function (BRDF) of the surface, but the models are commonly not connected with the manufacturing process. This study proposes to consider the geometrical features (defects, waviness, lay, and roughness) of metal surfaces as well as the physical and chemical features (grain structure and microlayers) to understand surface appearance and manufacturing in a holistic way. Preliminary tests show that 2D roughness measurements are not connected well with measured gloss units (GUs) and subjective, perceived quality. More fundamental research on the generation and measurement of surface appearance is needed and would benefit many industries

Automatic surface defect quantification in 3D

Three-dimensional (3D) non-contact optical methods for surface inspection are of significant interest to many industrial sectors. Many aspects of manufacturing processes have become fully automated resulting in high production volumes. However, this is not necessarily the case for surface defect inspection. Existing human visual analysis of surface defects is qualitative and subject to varying interpretation. Automated 3D non-contact analysis should provide a robust and systematic quantitative approach. However, different 3D optical measurement technologies use different physical principles, interact with surfaces and defects in diverse ways, leading to variation in measurement data. Instrument s native software processing of the data may be non-traceable in nature, leading to significant uncertainty about data quantisation. Sub-millimetric level surface defect artefacts have been created using Rockwell and Vickers hardness testing equipment on various substrates. Four different non-contact surface measurement instruments (Alicona InfiniteFocus G4, Zygo NewView 5000, GFM MikroCAD Lite and Heliotis H3) have been utilized to measure different defect artefacts. The four different 3D optical instruments are evaluated by calibrated step-height created using slipgauges and reference defect artefacts. The experimental results are compared to select the most suitable instrument capable of measuring surface defects in robust manner. This research has identified a need for an automatic tool to quantify surface defect and thus a mathematical solution has been implemented for automatic defect detection and quantification (depth, area and volume) in 3D. A simulated defect softgauge with a known geometry has been developed in order to verify the implemented algorithm and provide mathematical traceability. The implemented algorithm has been identified as a traceable, highly repeatable, and high speed solution to quantify surface defect in 3D. Various industrial components with suspicious features and solder joints on PCB are measured and quantified in order to demonstrate applicability