No description available.

No description available.

No description available.

Manufacturing systems are usually nonlinear, nonstationary, highly corrupted with outliers, and oftentimes constrained by physical laws. Modeling and approximation of their underly- ing response surface functions are extremely challenging. Bayesian optimization is a great statistical tool, based on Bayes rule, used to optimize and model these expensive-to-evaluate functions. Bayesian optimization comprises of two important components namely, a sur- rogate model often the Gaussian process and an acquisition function often the expected improvement. The Gaussian process, known for its outstanding modeling and uncertainty quantification capabilities, is used to represent the underlying response surface function, while the expected improvement is used to select the next point to be evaluated by trading- off exploitation and exploration. Although Bayesian optimization has been extensively used in optimizing unknown and expensive-to-evaluate functions and in hyperparameter tuning of deep learning models, mod- eling highly outlier-corrupted, nonstationary, and stress-induced response surface functions hinder the use of conventional Bayesian optimization models in manufacturing systems. To overcome these limitations, we propose a series of systematic methodologies to improve Bayesian optimization for engineering design and quality control of manufacturing systems. Specifically, the contributions of this dissertation can be summarized as follows. 1. A novel asymmetric robust kernel function, called AEN-RBF, is proposed to model highly outlier-corrupted functions. Two new hyperparameters are introduced to im- prove the flexibility and robustness of the Gaussian process model. 2. A nonstationary surrogate model that utilizes deep multi-layer Gaussian processes, called MGP-CBO, is developed to improve the modeling of complex anisotropic con- strained nonstationary functions. 3. A Stress-Aware Optimal Actuator Placement framework is designed to model and op- timize stress-induced nonlinear constrained functions. Through extensive evaluations, the proposed methodologies have shown outstanding and significant improvements when compared to state-of-the-art models. Although these pro- posed methodologies have been applied to certain manufacturing systems, they can be easily adapted to other broad ranges of problems. / Doctor of Philosophy / Modeling advanced manufacturing systems, such as engineering design and quality moni- toring and control, is extremely challenging. The underlying response surface functions of these manufacturing systems are often nonlinear, nonstationary, and expensive-to-evaluate. Bayesian optimization, a statistical modeling approach based on Bayes rule, is used to rep- resent and model those complex (i.e., black-box) objective functions. A Bayesian optimiza- tion model consists of a surrogate model, often the Gaussian process, and an acquisition function, often the expected improvement. Conventional Bayesian optimization models do not accurately represent non-stationary and outlier-corrupted functions. To overcome these limitations, we propose a new asymmetric robust kernel function to improve the model- ing capabilities of the Gaussian process model in process quality control through improved defect detection and classification. We also propose a non-stationary surrogate model to improve the performance of Bayesian optimization in aerospace process design problems. Finally, we develop a new optimization framework that models and optimizes stress-induced constrained aerospace manufacturing systems correctly. Our extensive experiments show significant improvements of these three proposed models when compared to state-of-the-art methodologies.

M.S.

In order for an industrial inspection system to be of utility in manufacturing it must be fast, accurate, and flexible [Chin 1986]. Current machine vision systems are very specialized and inflexible in nature. A reason for the inflexibility of current machine vision systems is the need for real-time processing of image data. Such a need has forced both the use of very specialized image processing hardware as well as the use of rather simple, very specialized computer vision algorithms to do the analysis. On the other hand, most, if not all, of today’s computer vision methods are not general purpose in nature. In the absence of truly robust general purpose methods, developing satisfactory machine vision solutions will continue to involve experimenting with machine vision hardware and software components. Given the current state of machine vision technology, it would seem that the best method for creating flexible machine vision systems is, perhaps, to define a subclass of inspection problems where all the problems within the subclass have a number of common features about them. Such a subclass must be of interest to a number of manufacturers. It must also be “reasonable” to solve, given the current state of the art. Once the subclass has been selected, the next logical step would seem to be to create a device that makes performing all the needed experiments on the various problems within the class easy to perform. Based on the above line of reasoning, this work has four major objectives. The first objective is to define a meaningful subclass of inspection problems that are a) of interest to a number of manufacturers, and b) represent inspection tasks that seem “reasonable” within the current state-of-the-art of computer vision. The subclass of inspection problems selected for this work is the longitudinal planar web inspection problem under the two-dimensional imaging restriction. The second objective of this work is to create a vehicle that will allow the types of experimentation usually associated with the development of machine vision systems to be facilitated. This vehicle created is called a “machine vision prototyper.” The third objective of this work is to use the machine vision prototyper system to attack a particular planar web applications problem. The application considered is the problem of locating and identifying surface defects in surfaced hardwood lumber in a species independent manner. The fourth objective of this research is to indicate how the prototyper system can be used to attack a second planar web application problem. This application problem is the inspection of hardwood parts coming out of a molder. The utility of the machine vision prototyper system as an experimental tool is demonstrated on two of the three possible types of longitudinal planar web inspection problems. The results include the development of a machine vision system for a hardwood surfaced lumber surface feature detection problem, and a discussion of how the prototyper can be used to attack the problem of inspecting hardwood parts coming out of a molder. / Ph. D.

A performance analysis of three different Minimax control charts is performed with respect to their Chi-Square control chart counterparts under several different conditions. A unique control chart must be constructed for each process described by a unique combination of quality characteristic mean vector and associated covariance matrix. The three different charts under consideration differ in the number of quality characteristic variables of concern. In each case, without loss of generality the in-control quality characteristic mean vector is assumed to have zero entries and the associated covariance matrix is assumed to have non-negative entries. The performance of the Chi-Square and Minimax charts are compared under different values of the sample size, the probability of a Type I error, and selected shifts in the quality characteristic mean vector. Minimax and Chi-Square charts that are compared share identical in-control average run lengths (ARL) making the out-of-control ARL the appropriate performance measure. A combined Tausworthe pseudorandom number generator is used to generate the out-of-control mean vectors. Issues regarding multivariate uniform pseudorandom number generation are addressed. / Master of Science

Total Quality Management (TQM) has become a popular term in quality improvement management. Many organizations, however, frequently implement quality tools that are not well coordinated with the established quality principles or the managerial decisions and actions. This research focuses on studying three major quality management components: quality philosophies, interventions, and tools. The primary desired outcome of this research is to improve the understanding of TQM implementation. The means to accomplish this desired outcome included reviewing quality improvement philosophies of Deming, Juran, Feigenbaum, Crosby, and Ishikawa, and conducting multiple case studies. The eight organizations vary in their organizational type (service or manufacturing), years of experience in their TQM efforts, and their sizes (number of employees). The case studies involved interviewing the quality managers and described how they define and implement TQM. A quality improvement taxonomy, a two-dimensional matrix, is a product developed as a result of this study. The first dimension of the taxonomy describes the quality interventions--the organizational planned changes for improving quality, which are categorized by six quality checkpoints: management of upstream systems, incoming quality assurance, in-process quality management, outgoing quality assurance, proactive assurance of customer satisfaction, and the overall quality management process. The second dimension lists seventeen supporting quality management tools. They include tools such as the Input/Output Analysis, Quality Function Deployment, Competitive Benchmarking, and Statistical Process Control. Organizations can use this quality improvement taxonomy to communicate the TQM concept and to improve coordination of quality management tools with the overall TQM implementation decisions and actions. / Master of Science

The purpose of this research was to investigate how the quality control manager perceived complaints received by textile companies from their business customers. The population included all textile firms that weave fabric for outerwear (apparel). A packet consisting of cover letter, questionnaire (developed by the researcher), and stamped self-addressed envelope was mailed to each quality control manager in the population. Fifty-four usable questionnaires (28 percent) were returned. The Chi-squared test for independence revealed that at the .05 level, no relationship existed between the number of employee-hours spent handling business customer complaints and the establishment of written guidelines for complaint resolution within the quality control department; nor between the office that handled complaints from business customers and end-use consumers, and the office from which quality control received business customer complaints. The Chi-squared test also found that no relationship existed between the ratings for intended end use for fabric that weavers produced and the type of business customers from whom the quality control manager received complaints; and between the time spent handling different types of business customer complaints received by the quality control managers and the source of these complaints. The quality control and sales offices frequently collaborated on complaints to ensure that their business customers received satisfactory resolutions within the established time. The most frequent complaints received were spots/stains/streaks/dye resistant area, or faulty weaving that most likely came from the consumer product manufacturer, converter, or dyer/finisher and consumed almost 50 percent of the time spent handling complaints. / M.S.

Tesis por compendio / La industria alimentaria, concretamente el sector poscosecha, necesita innovar en sus procesos productivos, optimizando los mismos para rentabilizar sus actividades, garantizando productos de calidad capaces de satisfacer las necesidades de los consumidores. La presente tesis doctoral se centra en evaluar el potencial de la espectroscopia VIS-NIR para la caracterización e inspección de la calidad de la fruta tanto fuera de línea como a tiempo real en procesos automatizados. En un primer lugar, la viabilidad de la técnica se estudió a nivel de laboratorio en estado estático (off-line), con el fin de conocer y optimizar las condiciones de medición. Posteriormente, se evaluó la calidad interna y externa de diferentes tipos de frutas como son caqui, nectarina y mango. En una segunda etapa, se llevó a cabo una automatización de los procesos de inspección mediante el desarrollo de nuevos prototipos in-line. Para este propósito, y con el objetivo de completar y corroborar los resultados obtenidos de manera estática, se estudió la integración de dos sondas VIS-NIR en una garra robótica capaz de manipular mangos. Finalmente, se estudió la integración de una sonda VIS-NIR a una cinta transportadora. Los resultados obtenidos a nivel estático han demostrado que la espectroscopia VIS-NIR es un método no destructivo muy prometedor para predecir la astringencia en caqui. Así mismo, ha demostrado ser una adecuada herramienta para clasificar al 100% entre variedades de nectarinas como "Big Top" y "Diamond Ray" con una apariencia externa e interna muy similar, pero con diferentes propiedades organolépticas. De manera similar, fue posible clasificar al 100% variedades como "Big Top" y "Magique" de apariencia externa y composición similar pero distinto color de pulpa., y además se desarrolló un índice de calidad interna (IQI) para evaluar la calidad de las nectarinas. Por lo que respecta a los trabajos off-line realizados con mangos de la variedad "Osteen", fue posible predecir su calidad interna mediante los índices de madurez (RPI) y de calidad (IQI) con un gran rendimiento. A su vez, los ensayos experimentales efectuados con estos mismos mangos bajo la manipulación no destructiva de una garra robótica, demostraron que los mejores modelos eran capaces de predecir tanto la firmeza mecánica, el contenido en sólidos solubles, la luminosidad de la pulpa, así como el índice RPI de las muestras en base a la información obtenida por los acelerómetros instalados en los dedos de la garra robótica. En cuanto a los ensayos realizados de manera in-line, el primer prototipo desarrollado se basó en la integración de dos sondas VIS-NIR en una garra robótica dispuesta con dos acelerómetros. El sistema desarrollado permitió alcanzar una buena estimación de la calidad del mango a través del índice RPI fusionando la información tanto de los espectros VIS-NIR como del impacto no destructivo de los acelerómetros. De este modo quedó demostrado que era posible obtener una predicción similar trabajando de forma in-line como trabajando de manera off-line para la predicción del mismo índice de calidad en mangos. El segundo prototipo in-line desarrollado se basa en la integración de una sonda VIS-NIR en una cinta transportadora para la identificación de distintas variedades y orígenes de manzanas. El prototipo desarrollado permitió registrar resultados de clasificación tan buenos como los efectuados de manera off-line con, por ejemplo, nectarina. De este modo, se puede concluir que la espectroscopia VIS-NIR permite monitorear la calidad y clasificar fruta poscosecha tanto en modo off-line como in-line. Los nuevos prototipos desarrollados aportan claras ventajas respecto a los procesos tradicionales realizados a mano, como son la reducción del tiempo de inspección, la disminución de la cantidad de residuos generados y la posibilidad de inspeccionar toda la producción, obteniendo así un análisis más estandariz / The food industry, concretely the post-harvest sector, needs to innovate in their production processes, optimizing them to make their activities profitable, guaranteeing quality products capable of satisfying the needs of consumers. The present doctoral thesis focuses on evaluating the potential of visible and near infrared spectroscopy (VIS-NIR) for the characterization and inspection of fruit quality both off-line and in real time in automated processes. Firstly, the viability of the technique was studied at the laboratory level in a static mode (off-line), in order to know and optimise the measurement conditions. Subsequently, the internal and external quality of different types of fruits such as persimmon, nectarine and mango were evaluated. Secondly, an automation of the inspection processes was carried out through the development of new in-line prototypes. For this purpose, and with the aim of completing and corroborating the results obtained in a static mode, the integration of two VIS-NIR probes in a robotic gripper capable of manipulating mangoes was studied. Finally, the integration of a VIS-NIR probe to a conveyor belt was studied as an in-line monitoring tool on the inspection process of different apple varieties. The results obtained in static mode have shown that VIS-NIR spectroscopy is a very promising non-destructive method to predict the astringency in persimmon. Likewise, it has demonstrated to be an adequate tool to classify 100% between nectarine varieties such as 'Big Top' and 'Diamond Ray' with very similar external and internal appearance, but with different organoleptic properties. Similarly, it was possible to classify 100% varieties such as 'Big Top' and 'Magique' with external appearance and similar composition but different pulp colour. An internal quality index (IQI) was developed to evaluate the quality of nectarines, which can be predicted through VIS-NIR spectroscopy. Regarding the off-line work carried out with mangoes of 'Osteen' variety, it was possible to predict its internal quality through the indexes of maturity (RPI) and quality (IQI) with a high performance. Moreover, the experimental tests carried out with these same mangoes under the non-destructive manipulation of a robotic gripper, showed that the best models were able to predict both the mechanical firmness, the soluble solids content, the brightness of the pulp, as well as the RPI index of the samples based on the information obtained by the accelerometers installed on the fingers of the robotic gripper. Regarding the tests carried out in an in-line mode, the first developed prototype was based on the integration of two VIS-NIR probes in a robotic gripper fitted with two accelerometers. The developed system allowed reaching a good estimation of mango quality through the RPI index. In this way, it was demonstrated that it was possible to obtain a similar prediction working in-line as off-line mode for the prediction of the same quality index in mangoes. The second developed in-line prototype is based on the integration of a VIS-NIR probe in a conveyor belt for the identification of different varieties and origins of apples, achieving a success rate of 98% with the system. The developed prototype allowed to register classification results as good as those carried out off-line with, for example, nectarine. In this way, it can be concluded that VIS-NIR spectroscopy allows monitoring the quality and classifying post-harvest fruit in both off-line and in-line mode, being a tool that allows improving and guaranteeing the correct quality and food safety. The new developed prototypes provide clear advantages over the traditional processes performed by hand, such as the reduction of inspection time, the reduction of the amount of waste generated by destructive quality analysis and the possibility of inspecting full production, obtaining a more standardised analysis of the quality of the products. / La indústria alimentària, concretament el sector postcollita, necessita innovar en els seus processos productius, optimitzant els mateixos per a rendibilitzar les seues activitats, garantint productes de qualitat capaços de satisfer les necessitats dels consumidors. La present tesi doctoral es centra en avaluar el potencial de l'espectroscòpia visible i infraroig pròxim (VIS-NIR) per a la caracterització i la inspecció de la qualitat de la fruita tant fora de línia com a temps real en processos automatitzats. En un primer lloc, la viabilitat de la tècnica es va estudiar a nivell de laboratori en estat estàtic (off-line), a fi de conéixer i optimitzar les condicions de mesurament. Posteriorment, es va avaluar la qualitat interna i externa de diferents tipus de fruites com són caqui, nectarina i mango. En una segona etapa, es va dur a terme una automatització dels processos d'inspecció per mitjà del desenvolupament de nous prototips in-line. Per aquest propòsit, i amb l'objectiu de completar i corroborar els resultats obtinguts de manera estàtica, es va estudiar la integració de dos sondes VIS-NIR en una garra robòtica capaç de manipular. Finalment, es va estudiar la integració d'una sonda VIS-NIR a una cinta transportadora. Els resultats obtinguts a nivell estàtic han demostrat que l'espectroscòpia VIS-NIR és un mètode no destructiu molt prometedor per a predir l'astringència en caqui. Així mateix, ha demostrat ser una adequada ferramenta per a classificar al 100% entre varietats de nectarines com "Big Top" i "Diamond Ray" amb una aparença externa i interna molt semblant, però amb diferents propietats organolèptiques. De manera semblant, va ser possible classificar al 100% varietats com "Big Top" i "Magique" d'aparença externa i composició semblant però distint color de polpa. Es va desenvolupar un índex de qualitat interna (IQI) per avaluar la qualitat de les nectarines. Pel que fa als treballs off-line realitzats amb mangos de la varietat "Osteen" va ser possible predir la seua qualitat interna mitjançant els índexs de maduresa (RPI) i de qualitat (IQI) amb un gran rendiment. Al mateix temps, els assajos experimentals efectuats amb estos mateixos mangos baix la manipulació no destructiva d'una garra robòtica, van demostrar que els millors models eren capaços de predir tant la fermesa mecánica, el contingut en sòlids solubles, la lluminositat de la polpa, així com l'índex RPI de les mostres basant-se en l'informació obtinguda pels acceleròmetres instal¿lats en els dits de la garra robòtica. En quant als assajos realitzats de manera in-line, el primer prototip desenvolupat es va basar en la integració de dos sondes VIS-NIR en una garra robòtica disposada amb dos acceleròmetres. El sistema desenvolupat va permetre aconseguir una bona estimació de la qualitat del mango a través de l'índex RPI fusionant l'informació tant dels espectres VIS-NIR com de l'impacte no destructiu dels acceleròmetres. D'esta manera va quedar demostrat que era possible obtindre una predicció semblant treballant de forma in-line com off-line per a la predicció del mateix índex de qualitat en mangos. El segon prototip in-line desenvolupat es va basar en la integració d'una sonda VIS-NIR en una cinta transportadora per a l'identificació de distintes varietats i orígens de pomes. El prototip desenvolupat va permetre registrar resultats de classificació tan bons com els efectuats de manera off-line. D'aquesta manera, es pot concloure que l'espectroscòpia VIS-NIR permet monitorar la qualitat i classificar fruita postcollita tant en mode off-line com in-line. Els nous prototips desenvolupats aporten clars avantatges respecte als processos tradicionals realitzats a mà, com són la reducció del temps d'inspecció, la disminució de la quantitat de residus generats pels anàlisis destructives de qualitat i la possibilitat d'inspeccionar tota la producció, obtenint així un anàlisi més estandarditz / Cortés López, V. (2018). Innovations in non-destructive techniques for fruit quality control applied to manipulation and inspection lines [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/110969 / Compendio