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Recent research discussed the development of image processing tools as a part of the quality control framework in manufacturing environments. This research could be divided into two image-based fault detection approaches: 1) MVS; and 2) MVS and control charts. Despite the intensive research in both groups, there is a disconnect between research and the actual needs on the shop-floor. This disconnect is mainly attributed to the following: • The literature for the first category has mainly focused on improving fault detection accuracy through the use of special setups without considering its impact on the manufacturing process. Therefore, many of these methods have not been utilized by industry, and these tools lack the capability of using images already present on the shop floor. • The studies presented on the second category have been mainly developed in isolation. In addition, most of these studies have focused more on introducing the concept of utilizing control charts on image data rather than tackling specific industry problems. • In this thesis, these limitations are investigated and are disseminated to the research community through two different journal papers. In the first paper, it was shown that a face-recognition tool could be successfully used to detect faults in real-time in stamped processes, where the changes in image lighting conditions and part location were allowed to emulate actual manufacturing environments. On the other hand, the second paper reviewed the literature on image-based control charts and suggested recommendations for future research. / Master of Science

Statistical process monitoring and hierarchical Bayesian modeling are two ways to learn more about processes of interest. In this work, we consider two main components: risk-adjusted monitoring and Bayesian hierarchical models for spatial data. Usually, if prior information about a process is known, it is important to incorporate this into the monitoring scheme. For example, when monitoring 30-day mortality rates after surgery, the pre-operative risk of patients based on health characteristics is often an indicator of how likely the surgery is to succeed. In these cases, risk-adjusted monitoring techniques are used. In this work, the practical limitations of the traditional implementation of risk-adjusted monitoring methods are discussed and an improved implementation is proposed. A method to perform spatial risk-adjustment based on exact locations of concurrent observations to account for spatial dependence is also described. Furthermore, the development of objective priors for fully Bayesian hierarchical models for areal data is explored for Gaussian responses. Collectively, these statistical methods serve as analytic tools to better monitor and model spatial processes. / Ph. D.

Yes / Polymer extrusion is an energy intensive production process and process energy e ciency has become a key concern in the current industry with the pressure of reducing the global carbon footprint. Here, knowledge of the pattern of energy usage and losses of each component in the plant is highly useful in the process energy optimization. Moreover, it is essential to maintain the melt quality while improving the energy e ciency in polymer processing. In this work, an investigation was made on the total energy consumption, drive motor energy consumption, power factor and the melt temperature profile across the die melt flow (as an indication of the melt thermal quality) of an industrial scale extruder with three di erent screw geometries, three polymer types and wide range of processing conditions (altogether 135 di erent processing situations were observed). This aims to widen the knowledge on process energy and thermal behaviors while exploring possible correlation/s between energy demand and melt quality (in terms of melt temperature fluctuations across the melt flow). The results showed that the level and fluctuations of the extruder’s power factor is particularly dependent upon the material being processed. Moreover, it seems that there is a relation between the level of energy demand of the heaters and the level of melt temperature fluctuations. While the extruder specific energy consumption decreases with increasing screw speed, specific energy consumption of the drive motor may have either increasing or decreasing behavior. Overall, this study provides new insights in a wide range on process energy demand and melt thermal quality in polymer extrusion. Moreover, further research is recommended to establish strong correlation/s between process energy consumption and melt thermal quality which should help to enhance process control and hence the product quality in single screw polymer extrusion.

Yes / Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditions is a key to reducing operating costs. Usually, extruders consume energy through the drive motor, barrel heaters, cooling fans, cooling water pumps, gear pumps, etc. Typically the drive motor is the largest energy consuming device in an extruder while barrel/die heaters are responsible for the second largest energy demand. This study is focused on investigating the total energy demand of an extrusion plant under various processing conditions while identifying ways to optimise the energy efficiency. Initially, a review was carried out on the monitoring and modelling of the energy consumption in polymer extrusion. Also, the power factor, energy demand and losses of a typical extrusion plant were discussed in detail. The mass throughput, total energy consumption and power factor of an extruder were experimentally observed over different processing conditions and the total extruder energy demand was modelled empirically and also using a commercially available extrusion simulation software. The experimental results show that extruder energy demand is heavily coupled between the machine, material and process parameters. The total power predicted by the simulation software exhibits a lagging offset compared with the experimental measurements. Empirical models are in good agreement with the experimental measurements and hence these can be used in studying process energy behaviour in detail and to identify ways to optimise the process energy efficiency.

Yes / Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel. / This work was funded through an inter-disciplinary research programme (Grant No. EP/G059330/1) by the EPSRC-UK. The technical assistance provided by Ken Howell, Roy Dixon and John Wyborn is greatly appreciated.

[EN] An accurate fault diagnosis of both, faults sensors and real process faults have become more and more important for process monitoring (minimize downtime, increase safety of plant operation and reduce the manufacturing cost). Quick and correct fault diagnosis is required in order to put back on track our processes or products before safety or quality can be compromised. In the study and comparison of the fault diagnosis methodologies, this thesis distinguishes between two different scenarios, methods for multivariate statistical quality control (MSQC) and methods for latent-based multivariate statistical process control: (Lb-MSPC). In the first part of the thesis the state of the art on fault diagnosis and identification (FDI) is introduced. The second part of the thesis is devoted to the fault diagnosis in multivariate statistical quality control (MSQC). The rationale of the most extended methods for fault diagnosis in supervised scenarios, the requirements for their implementation, their strong points and their drawbacks and relationships are discussed. The performance of the methods is compared using different performance indices in two different process data sets and simulations. New variants and methods to improve the diagnosis performance in MSQC are also proposed. The third part of the thesis is devoted to the fault diagnosis in latent-based multivariate statistical process control (Lb-MSPC). The rationale of the most extended methods for fault diagnosis in supervised Lb-MSPC is described and one of our proposals, the Fingerprints contribution plots (FCP) is introduced. Finally the thesis presents and compare the performance results of these diagnosis methods in Lb-MSPC. The diagnosis results in two process data sets are compared using a new strategy based in the use of the overall sensitivity and specificity / [ES] La realización de un diagnóstico preciso de los fallos, tanto si se trata de fallos de sensores como si se trata de fallos de procesos, ha llegado a ser algo de vital importancia en la monitorización de procesos (reduce las paradas de planta, incrementa la seguridad de la operación en planta y reduce los costes de producción). Se requieren diagnósticos rápidos y correctos si se quiere poder recuperar los procesos o productos antes de que la seguridad o la calidad de los mismos se pueda ver comprometida. En el estudio de las diferentes metodologías para el diagnóstico de fallos esta tesis distingue dos escenarios diferentes, métodos para el control de estadístico multivariante de la calidad (MSQC) y métodos para el control estadístico de procesos basados en el uso de variables latentes (Lb-MSPC). En la primera parte de esta tesis se introduce el estado del arte sobre el diagnóstico e identificación de fallos (FDI). La segunda parte de la tesis está centrada en el estudio del diagnóstico de fallos en control estadístico multivariante de la calidad. Se describen los fundamentos de los métodos más extendidos para el diagnóstico en escenarios supervisados, sus requerimientos para su implementación sus puntos fuertes y débiles y sus posibles relaciones. Los resultados de diagnóstico de los métodos es comparado usando diferentes índices sobre los datos procedentes de dos procesos reales y de diferentes simulaciones. En la tesis se proponen nuevas variantes que tratan de mejorar los resultados obtenidos en MSQC. La tercera parte de la tesis está dedicada al diagnóstico de fallos en control estadístico multivariante de procesos basados en el uso de modelos de variables latentes (Lb-MSPC). Se describe los fundamentos de los métodos mas extendidos en el diagnóstico de fallos en Lb-MSPC supervisado y se introduce una de nuestras propuestas, el fingerprint contribution plot (FCP). Finalmente la tesis presenta y compara los resultados de diagnóstico de los métodos propuestos en Lb-MSPC. Los resultados son comparados sobre los datos de dos procesos usando una nueva estrategia basada en el uso de la sensitividad y especificidad promedia. / [CA] La realització d'un diagnòstic precís de les fallades, tant si es tracta de fallades de sensors com si es tracta de fallades de processos, ha arribat a ser de vital importància en la monitorització de processos (reduïx les parades de planta, incrementa la seguretat de l'operació en planta i reduïx els costos de producció) . Es requerixen diagnòstics ràpids i correctes si es vol poder recuperar els processos o productes abans de que la seguretat o la qualitat dels mateixos es puga veure compromesa. En l'estudi de les diferents metodologies per al diagnòstic de fallades esta tesi distingix dos escenaris diferents, mètodes per al control estadístic multivariant de la qualitat (MSQC) i l mètodes per al control estadístic de processos basats en l'ús de variables latents (Lb-MSPC). En la primera part d'esta tesi s'introduïx l'estat de l'art sobre el diagnòstic i identificació de fallades (FDI). La segona part de la tesi està centrada en l'estudi del diagnòstic de fallades en control estadístic multivariant de la qualitat. Es descriuen els fonaments dels mètodes més estesos per al diagnòstic en escenaris supervisats, els seus requeriments per a la seua implementació els seus punts forts i febles i les seues possibles relacions. Els resultats de diagnòstic dels mètodes és comparat utilitzant diferents índexs sobre les dades procedents de dos processos reals i de diferents simulacions. En la tesi es proposen noves variants que tracten de millorar els resultats obtinguts en MSQC. La tercera part de la tesi està dedicada al diagnòstic de fallades en control estadístic multivariant de processos basat en l'ús de models de variables latents (Lb-MSPC). Es descriu els fonaments dels mètodes més estesos en el diagnòstic de fallades en MSPC supervisat i s'introdueix una nova proposta, el fingerprint contribution plot (FCP). Finalment la tesi presenta i compara els resultats de diagnòstic dels mètodes proposats en MSPC. Els resultats són comparats sobre les dades de dos processos utilitzant una nova estratègia basada en l'ús de la sensibilitat i especificitat mitjana. / Vidal Puig, S. (2016). FAULT DIAGNOSIS TOOLS IN MULTIVARIATE STATISTICAL PROCESS AND QUALITY CONTROL [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61292

Yes / Polymer extrusion is an important but an energy intensive method of processing polymeric materials. The rapid increase in demand of polymeric products has forced manufactures to rethink their processing efficiencies to manufacture good quality products with low-unit-cost. Here, analyzing the operational conditions has become a key strategy to achieve both energy and thermal efficiencies simultaneously. This study aims to explore the effects of polymers' rheology on the energy consumption and melt thermal quality (ie, a thermally homogeneous melt flow in both radial and axil directions) of extruders. Six commodity grades of polymers (LDPE, LLDPE, PP, PET, PS, and PMMA) were processed at different conditions in two types of continuous screw extruders. Total power, motor power, and melt temperature profiles were analyzed in an industrial scale single-screw extruder. Moreover, the active power (AP), mass throughput, torque, and power factor were measured in a laboratory scale twin-screw extruder. The results confirmed that the specific energy consumption for both single and twin screw extruders tends to decrease with the processing speed. However, this action deteriorates the thermal stability of the melt regardless the nature of the polymer. Rheological characterization results showed that the viscosity of LDPE and PS exhibited a normal shear thinning behavior. However, PMMA presented a shear thickening behavior at moderate-to-high shear rates, indicating the possible formation of entanglements. Overall, the findings of this work confirm that the materials' rheology has an appreciable correlation with the energy consumption in polymer extrusion and also most of the findings are in agreement with the previously reported investigations. Therefore, further research should be useful for identifying possible correlations between key process parameters and hence to further understand the processing behavior for wide range of machines, polymers, and operating conditions.

Yes / Industry-standard quality management systems such as Six Sigma and emerging Industry 4.0 compliant production processes demonstrate the importance of in-line condition monitoring of manufacturing methods for achieving the highest levels of product quality. Measurement data collected as the process is running can inform the operator about unexpected changes in machine operation or raw materials that could negatively impact production; and offer an opportunity for a process control intervention to stabilise production. However, micro-manufacturing production lines can pose a challenging environment for deploying such systems, since processing events can occur extremely rapidly and in harsh environments. Moreover, the small scale of micro-nano featured components can make sensor installation even more problematic. Recently, ultrasonic micromoulding has drawn attention in niche markets due to its unique advantages for processing thermoplastics as a new micro-manufacturing technology. The process differs from conventional moulding significantly by eliminating the need for a plasticising screw and using direct application of ultrasonic energy to melt the polymer. This offers numerous benefits such as decrease in energy usage, moulding at lower pressures, easier cleaning, and reduced material residence times, the latter which could be beneficial for pharma-grade polymers or polymers with active ingredients. However, very little work has been reported attempting to monitor the process using in-line measurements. This work aims to evaluate the characteristics of the ultrasonic micromoulding process for microinjection moulding of a microneedle array using a range of sensor technologies including: data recorded by the machine controller; a high-speed thermal camera and a cavity pressure transducer. The data has captured the highly dynamic process environment with a high degree of accuracy. The relationship between the process data and dimensional quality of the ultrasonically micromoulded products has been quantified and subsequently implemented as a cost-effective in-line quality assurance method. / Horizon 2020, the EU Framework Programme for Research and Innovation (Project ID: 674801). This research has also received funding and support from two other Horizon 2020 projects: HIMALAIA (Grant agreement No. 766871) and Laser4Fun (GA no. 675063)