The need for cost-effective usability evaluation has led to the development of methodologies to support the usability practitioner in finding usability problems during formative evaluation. Even though various methods exist for performing usability evaluation, practitioners seldom have the information needed to decide which method is appropriate for their specific purpose. In addition, most methods do not have an integrated relationship with a theoretical foundation for applying the method in a reliable and efficient manner. Practitioners often have to apply their own judgment and techniques, leading to inconsistencies in how the method is applied in the field. Usability practitioners need validated information to determine if a given usability evaluation method is effective and why it should be used instead of some other method. Such a desire motivates the need for formal, empirical comparison studies to evaluate and compare usability evaluation methods. In reality, the current data for comparing usability evaluation methods suffers from a lack of consistent measures, standards, and criteria for identifying effective methods. The work described here addresses three important research activities. First, the User Action Framework was developed to help organize usability concepts and issues into a knowledge base that supports usability methods and tools. From the User Action Framework, a mapping was made to the Usability Problem Inspector; a tool to help practitioners conduct a highly focused inspection of an interface design. Second, the reliability of the User Action Framework was evaluated to determine if usability practitioners could use the framework in a consistent manner when classifying a set of usability problems. Third, a comprehensive comparison study was conducted to determine if the Usability Problem Inspector, based on the User Action Framework, could produce results just as effective as two other inspection methods (i.e., the heuristic evaluation and the cognitive walkthrough). The comparison study used a new comparison approach with standards, measures, and criteria to prove the effectiveness of methods. Results from the User Action Framework reliability study showed higher agreement scores at all classification levels than was found in previous work with a similar classification tool. In addition, agreement using the User Action Framework was stronger than the results obtained from the same experts using the heuristic evaluation. From the inspection method comparison study, results showed the Usability Problem Inspector to be more effective than the heuristic evaluation and consistent with effectiveness scores from the cognitive walkthrough. / Ph. D.

The task of railroad inspection is a tedious one. It requires a lot of skilled experts and long hours of frequent on-field inspection. Automated ground equipment systems that have been developed to address this problem have the drawback of blocking the rail service during inspection process. As an alternative, using aerial imagery from a UAV, Computer Vision and Machine Learning based techniques were developed in this thesis to analyze two kinds of defects on the rail tracks. The defects targeted were missing spikes on tie plates and cracks on ties. In order to perform this inspection, the rail region was identified in the image and then the tie plate and tie regions on the track were detected. These steps were performed using morphological operations, filtering and intensity analysis. Once the tie plate was localized, the regions of interest on the plate were used to train a machine learning model to recognize missing spikes. Classification using SVM resulted in an accuracy of around 96% and varied greatly based on the tie plate illumination and ROI alignment for Lampasas and Chickasha subdivision datasets. Also, many other different classifiers were used for training and testing and an ensemble method with majority vote scheme was also explored for classification. The second category of learning model used was a multi-layered neural network. The major drawback of this method was, it required a lot of images for training. However, it performed better than feature based classifiers with availability of larger training dataset. As a second kind of defect, tie conditions were analyzed. From the localized tie region, the tie cracks were detected using thresholding and morphological operations. A machine learning classifier was developed to predict the condition of a tie based on training examples of images with extracted features. The multi-class classification accuracy obtained was around 83% and there were no misclassifications seen between two extreme classes of tie condition on the test data. / Master of Science

This thesis presents an inspection method based on RGB-D profiling for the rail industry. The proposed approach uses inexpensive RGB-D cameras to generate color and geometrical information of the observations, and stitches each consecutive scan from the sensor to form a map, provided that the two scans contain the information from the same observation. Using a technique known as pairwise registration, the errors between these consecutive scans are minimized using error minimization algorithms such as Iterative Closest Point and Normal Distributions Transform. Once the error between each consecutive scan is minimized, the scans are then converted into a global co-ordinate frame work to form a global map of all the added scans. The proposed approach could be used as a map-based identification technique by comparing the past global map to newly acquired scans while also reducing computation time effectively. The effectiveness of this approach is demonstrated by developing a system that uses multiple RGB-D cameras to detect railway defects such as spikes. The applicability of the proposed approach to other applications is then evaluated by profiling long lengths of road. / Master of Science

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

Residential deck and balcony failures are preventable if the decks and balconies are maintained and inspected regularly. Inspection of in-service decks or balconies is not common and often is unregulated or building codes do not appear to be widely enforced. With every failure, the need for a comprehensive inspection manual for residential wood decks and balconies becomes more apparent. Research was conducted on inspection techniques, common deck and balcony construction methods, maintenance issues, decay detection and the evolution of the building code regulations on decks and balconies. Eight decks were inspected to find the extent of structural inadequacies and non-conformance with building codes. Using the information gathered from the research and inspections, a Manual for the Inspection of Residential Wood Decks and Balconies was written for professional inspectors and building officials. The manual includes recommended methods to prepare for inspection to preparation of final reports. It contains an appendix with information on the "pick test" for detecting early decay, information on adequate deck attachment, and a sample report for a complete deck inspection. / Master of Science

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25258号 / 工博第5217号 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 杉浦 邦征, 教授 八木 知己, 教授 KIM Chul-Woo / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

Construction and maintenance can have huge implications on the long-term functioning of GSI facilities. GSI facilities investigated were bioretention, permeable pavement, sand filters, infiltration trenches, and vegetated swales. This study first highlights the most important construction and maintenance items based on relevant studies and state stormwater manuals. Fairfax County, VA was used as a case study to evaluate the County's current stormwater program and illuminate common maintenance issues found for each GSI type. Data analysis of 3141 inspection records illustrated particular deficiencies for each GSI type and that there are differences between public and private facilities, most likely depending on site conditions and frequency of routine maintenance. Sediment accumulation was found to be the most common maintenance issue (27.8% of inspections), supporting the importance of adequate pretreatment and good housekeeping when implementing GSI. The Northern Virginia Soil and Water Conservation District (NVSWCD) performed a study surveying 63 public bioretention facilities in which they measured ponding depth, filter media depth, ponding area, and infiltration rates. The NVSWCD concluded that deficiencies found in facilities could mostly be attributed to inadequacies during construction. By comparing current post-construction inspections performed by the County to the NVSWCD data, it was found that these County inspections are failing to detect these inadequacies in bioretention facilities from improper construction. It is recommended that MS4s thoroughly record and track construction and post-construction inspection items to improve the longevity of its facilities and better inform future decision making regarding GSI. / Master of Science / Studies have shown that the proper construction and maintenance of green stormwater infrastructure (GSI) is a critical factor concerning its long-term performance; however, little research has been conducted on the necessary protocols and frequency to ensure its longevity. Many MS4s and stormwater managers are implementing these facilities without providing the adequate institutional framework to ensure the proper construction and maintenance. This study concentrates on illuminating the construction and maintenance factors critical for the performance of GSI. Facility types investigated were bioretention, permeable pavement, sand filters, infiltration trenches, and vegetated swales. The effects of local site-conditions and level of routine maintenance on frequency of facility deficiencies was quantified using 3141 records of maintenance and inspection data from Fairfax County, VA. Sediment and debris accumulation were found to be the most common deficiency highlighting the importance of good housekeeping and pretreatment devices. The Northern Virginia Soil and Water Conservation District (NVSWCD) performed a comprehensive review of 63 bioretention facilities in which they inspected elements considered critical to pollutant removal performance including ponding depth, filter media depth, and infiltration rates. By comparing the findings from the NVSWCD to current post-construction inspections performed by the County, it was found that current inspection protocols are missing important design components of bioretention facilities. This study also highlights the importance of thorough and thoughtful databases to track and record inspection and maintenance data surrounding GSI. The proper construction and maintenance of GSI is ultimately dependent on a multitude of factors including site-conditions, facility design specifications, and institutional support.

Dans le contexte économique et compétitif actuel, ce qui permet aux entreprises de se distinguer c'est leur réactivité à fournir des produits de plus en plus complexes sen répondant à des besoins toujours plus diversifiés. Pour faire face à cette exigence de réactivité et malgré ces contraintes, les approches d'ingénierie intégrée sont apparues pour une meilleure gestion du cycle de vie des produits. Dans ce contexte la prise en compte des variabilités et leurs interdépendances a été démontrée comme étant indispensable à l'amélioration des performances (coût, risque, qualité, …). Ce travail de thèse est consacré à l'élaboration d'un plan d'inspection optimal pour : la maîtrise de ces variabilités et leurs effets sur le comportement du produit, l'usage et les fonctionnalités de celui-ci. Pour cela un cadre méthodologique pour la co-conception des activités de contrôles de conformités et celles de suivi de fabrication a été formalisé. Ce cadre permet une prise de décision opérationnelle grâce à l'utilisation des outils opérationnels et assure la satisfaction des objectifs stratégiques (réduction des coûts, amélioration de la qualité, augmentation de la productivité, …). Suite à une synthèse approfondie de la littérature relative à la planification la qualité et de l'amélioration (conjointe) de la performance, les outils AMDEC, KC flowdown, et Activity Based Costing (ABC) ont été retenus. Cependant ces outils présentent certains manques à combler et ont fait donc l'objet de certaines modifications (adaptations) pour convenir au mieux aux besoins du cadre méthodologique proposé. L'intégration d'AMDEC et de KC flowdown a abouti à un nouvel outil nommé ACDE (Analyse de la Causalité, des Défaillances, et leurs Effets). Ainsi l'adaptation d'ABC à l'estimation de coût de la qualité par « Quality-Driven ABC » a été proposée. L'application de ces derniers a été proposée dans le cadre de la planification d'inspection « au juste nécessaire ». / In the current economic and competitive environment, what distinguish the companies is their reactivity to provide increasingly complex products with increasingly diverse needs. To achieve this reactivity despite constraints, integrated engineering approachs have been emerged to better manage and organize the product life cycle. In this context, it is essential to take into account the characteristics' variations and their interdependencies to improve the performance (cost, risk, quality ...). This thesis was devoted to the generation of an optimal inspection plan including process variations monitoring and product variations control. A methodological framework for the co-conception of product control and process monitoring activities has been formalized and validated. This framework allows operational decision-making by the intervention of operational tools and ensures the satisfaction of strategic objectives (cost reduction, improved quality, increased productivity ...). FMEA, KC flowdown, and Activity Based Costing (ABC) were selected following a comprehensive literature review on quality planning and performance improvement. However, these tools present some lack to fill up and therefore are subjected to certain adaptations in order to best fit the needs of the proposed methodological framework. Integration of FMEA and KC flowdown resulted in a new tool called ACDE. As well the adaptation of ABC to estimate the cost of quality by "Quality-Driven ABC" was proposed. The application of these latter has been proposed to limit the inspection planning to “bare essentials activities.

Most existing structural health monitoring (SHM) techniques are based on measured acceleration data. Such practice, however, is highly expensive to operate, mainly due to cumbersome, time-consuming and expensive installation of sensors and their data acquisition systems. As an emerging noncontact method, the vision-based displacement sensor systems have attracted significant research interests and offered a promising alternative to the conventional sensors for SHM. However, most existing vision-based sensors require physical access to the structure to install a predesigned target panel, which has a higher contrast and thus is easier to track. Besides, most studies are carried out in controlled laboratory environments. The accuracy and robustness of vision sensors in the outdoor field conditions have not been fully investigated. It is also noted that current researches are mainly focusing on the measurement performance evaluation of vision sensors, without discussing the use of the measured displacement data for SHM. This dissertation develops a high-precision vision sensor system for remote and real-time measurement of multipoint structural displacements by tracking natural targets on structural surfaces. Two sets of software packages are developed respectively based on two advanced template matching algorithms (i.e., the upsampled cross correlation and the orientation code matching) incorporated with different subpixel techniques. Comprehensive experiments, including laboratory shaking table tests and field bridge tests, are carried out to evaluate its performance. Satisfactory agreements are observed between the displacements measured by the proposed vision sensor and those measured by high-performance reference displacement sensors. Moreover, this study examines the robustness of the vision sensor against ill environmental conditions such as dim light, background image disturbance and partial template occlusion. This dissertation further explores the potentials of the vision sensor for fast and inexpensive SHM applications, by demonstrating the usefulness of the displacement data for experimental modal analysis, finite element (FE) model updating, damage detection, etc. For a three-story frame structure, the modal analysis shows that the obtained natural frequencies and mode shapes from displacement measurements by using one camera match well with those by using four accelerometers. In fact, the vision sensor can achieve smoother mode shapes which would make damage localization more accurate, while the resolution of mode shapes from accelerometers is limited by the sensor number. This has been demonstrated from the damage detection result of beam structures based on the mode shape curvature (MSC) index. To address the needs for monitoring aging railway and highway bridges, coupled train-track-bridge and vehicle-bridge FE models are firstly developed to study the dynamic interactions between bridges and moving trains/vehicles. Subsequently, a time-domain model updating approach for railway bridges is proposed based on the in-situ measurement of the bridges’ dynamic displacement histories by the proposed vision sensor. This dissertation further proposes a bridge damage detection procedure that utilizes vehicle-induced displacement response and the MSC index without requiring prior knowledge about the traffic excitation.

Manufacturing industries are facing major challenges in terms of improving product quality and increasing throughput while sustaining production costs to acceptable levels. Product-oriented processes, both legacy and new, are poorly monitored and controlled on the basis of distributed loop controllers that are aiming to maintain critical process variables within acceptable bounds. Thus, poor quality product results when such processes are subjected to large disturbances - operational failures, environmental changes, and changes in loading conditions. In this research, product quality modeling and control based on a vision inspection methodology is proposed to improve product quality and increase productivity. The main contributions of this research are twofold. First, this research introduces a product quality modeling methodology that combines both physical-based modeling and data-driven modeling. The quality model is the link between information coming from the inspection of product features and the specification of process control strategies. It is essential to control and optimize the process. Physical-based modeling is used to model the product temperature profile, and data-driven modeling is used to train the mapping from the product temperature profile to each quality metric. The break down of the sub models increase the flexibility of model development and reduce the effort to change the model when the quality metrics change. The second contribution is the development of a novel approach to control product quality based on vision inspection, which is developed as part of a hybrid, hierarchical architecture. The high-level control module involves scheduling of multiple plant processes, diagnostics of the failure condition in the process, and the supervision of the whole process. The mid-level control module, which is the focus of the work presented here, takes advantage of baking product quality indicators and oven parameter measurements to optimize zone temperature and conveyor speed set points so that the best product quality is achieved even in the presence of disturbances. The low-level control module consists of basic control loops. Each of them controls parameters of each operation in the process separately. They are generally simple and easy to implement.