Process planning is a task comprising a broad range of activities to design and develop an appropriate manufacturing process for producing a part. Interpretation of the part design, selection of manufacturing processes, definition of operations, operation sequences, machining datums, geometrical dimensions and tolerances are some common activities associated with the task. Process planning is also “the link between product design and manufacturing” with the supplementary commission to support design of competitive products. Process planning is of a complex and dynamic nature, often managed by a skilled person with few, or no, explicit methods to solve the task. The work is heuristic and the result is depending on personal experiences and decisions. Since decades, there have been plenty of attempts to develop systems for computer-aided process planning (CAPP). CAPP is still awaiting its breakthrough and one reason is the gap between the functionality of the CAPP systems and the industrial process planning practice. This thesis has an all-embracing aim of finding methods that cover essential activities for process planning, including abilities to predict the outcome of a proposed manufacturing process. This is realised by gathering supporting methods suitable to manage both qualitative and quantitative characterisation and analyses of a manufacturing process. The production research community has requested systematisation and deeper understanding of industrial process planning. This thesis contributes with a flow chart describing the process planning process (PPP), in consequence of the methodological studies. The flow chart includes process planning activities and information flows between these activities. The research has been performed in an industrial environment for high volume manufacturing of gear parts. Though gear manufacturing has many distinctive features, the methods and results presented in this thesis are generally applicable to precision manufacturing of many kinds of mechanical parts. / <p>QC 20140522</p>

The relative efficacy of training procedures emphasizing accuracy versus those which add a rate criterion is a topic of debate. The desired learning outcome is fluent responding, assessed by measures of retention, endurance, stability, and application. The current study examined the effects of these two procedures on fluency outcomes using a matching-to-sample paradigm to train participants to match English to Japanese characters. An explicit FR-3 observing response was added to an accuracy-only condition to assess the extent to which it may facilitate learning. Total time spent responding in practice drills in accuracy-only conditions was yoked to total time spent in drills achieving rate aims in accuracy+rate (AR) conditions. One participant clearly demonstrated superior fluency outcomes after AR training while another displayed superior endurance and stability outcomes after such training. The remaining two participants did not demonstrate significantly different fluency outcomes across conditions.

Photons have proven to be an effective test-bed for the fundamental concepts and elements of quantum-enhanced technologies. As systems become increasingly complex, however, practical considerations make the traditional approach of bulk optics and free-space propagation progressively more difficult. The major obstacles are the physical space necessary to realise and operate such a complex system, its stability, and maintaining low losses. In order to address these issues, quantum optical technologies can take a cue from their classical counterparts and look towards an integrated architecture to provide miniaturisation, greatly enhanced stability, less alignment, and low loss interfaces between different system components. In this thesis the feasibility of chip-based waveguides as a platform for metrology and information processing will be explored. In Part I, the necessary criteria for a metrology system to out-perform its classical counterpart will be investigated. It will be found that loss is a major barrier to this aim and, critically, that it is unlikely to have been achieved to date by any experiment which consumes resources of a fixed photon number. The issue of loss will be addressed by developing a scalable heralded source of a class of entangled photonic states which are both robust to losses and practically feasible to prepare. A novel tomographic technique will be developed to characterize these states and it will be explicitly demonstrated how it is possible to beat some bounds on classical performance without being able to out-perform a comparable classical system. Finally, a proof of principle demonstration of a waveguide-based interferometer with an integrated phase-shifter will be undertaken. It will be shown that the device preserves quantum interference, making it suitable for use in quantum-enhanced metrology applications. In Part II, integrated optics in the context of information processing will be discussed. First, a novel characterization technique will be developed which enables the behaviour of complex circuits to be predicted. The technique is independent of loss in the device being characterized. A method of simulating these circuits will be outlined that takes advantage of the computational speed-up available from parallelisation and sparse matrix operations. A key increase in complexity for integrated photonic systems will be demonstrated by showing quantum interference of three photons from two separate sources in eight spatial modes. The resulting interference has a visibility which beats all possible classical interference visibilities for similar circuits. Finally, a fully integrated waveguide-coupled photon-number-resolving detector will be developed and demonstrated. This proof of concept demonstration will show good resolution of different photon number events. The device will be modelled and routes to high efficiency operation will be explored.

Die Landwirtschaft ist bereits digital – seit vielen Jahren prägen Informatik und Elektronik den landwirtschaftlichen Alltag. Digitale Anwendungen helfen beim Pflanzenschutz und der Wettervorhersage. Für die Präzisionslandwirtschaft sind Landmaschinen mit intelligenten Technologien bestückt. So kommunizieren sie untereinander. Automatisierte Arbeitsprozesse sind auf dem Feld und im Hof angekommen. Wie lässt sich Ökonomie und Ökologie nachhaltig verbinden und gut mit dem Faktor „Mensch“ integrieren? Die Frage, wer über Daten verfügt und sie interpretieren kann, wird zum Wettbewerbsfaktor in der Landwirtschaft – ist aber auch fachlich, juristisch und ethisch von Interesse. Diesen Themen widmet sich unter Schirmherrschaft des Bundeslandwirtschaftsministeriums (BMEL) die erste Konferenz zur Digitalisierung in der Landwirtschaft. Dabei geht es neben Begriffsfindung (z.B. Digitalisierung, Transformation, Big Data, Farming 4.0, Precision Farming), um das Aufzeigen der Potenziale und Risiken sowie den Erfahrungsaustausch über praxisnahe Lösungsansätze für die in der Wertschöpfungskette Beteiligten. Die Veranstaltung wird im Rahmen eines Programmkomitees durch DLG, KTBL, Leibniz Institut für Agrartechnik Potsdam, Bornim, Hochschule Osnabrück, Gesellschaft für Informatik in der Landtechnik und das Institut für Naturstofftechnik der TU Dresden unterstützt. Die Veranstaltung findet parallel zum IEEE 5G Summit statt (https://5glab.de/5gsummit/). Dies erlaubt erste Blicke auf die Anwendungsdemonstrationen der nächsten Mobilfunkgeneration und den direkten Kontakt mit den Teilnehmern des Summits während der Abendveranstaltung.

This study examined the effects of fluency-based instruction on the identification of six component-composite relations for early reading skills. Five participants (ages 5-8) who struggled with reading participated. A multiple probe design was used to assess the effects of frequency building on prerequisite skills on the emergence of composite reading skills. The results show that the prerequisite skills taught did not have an effect on the composite skill probes but did have an effect on the assessment scores. The data expand the research pertaining to Precision Teaching, fluency-based instruction, and component-composite relations. These data suggest that additional skills may be needed to be taught in order to effects on the composite skills. In addition, these authors identify the need for the identification of the component skills necessary to teach rapid autonomic naming.

Les techniques polarimétriques et interférométriques SAR (PolInSAR) en bande P (250Mhz - 500Mhz), offrent une solution à échelle mondiale pour l'étude des paramètres de la biomasse végétale. L'objectif de ce travail de doctorat est de proposer une analyse de la précision d'estimation que l'on peut espérer obtenir à l'aide de ces techniques pour certains paramètres tels que la hauteur de la végétation et du sol, en s'appuyant sur une des modélisation de la végétation les plus utilisées (modèle RVoG). Nous avons tout d'abord déterminé la Borne de Cramér-Rao (BCR) qui permet de fournir une borne inférieure à la variance d'estimation lorsque cette dernière est sans biais. Cette étude montre qu'il peut exister une grande diversité de situations, avec dans les cas favorables un écart type d'estimation de l'ordre du mètre pour une taille d'échantillon de 100 pixels. Il a pu ainsi être montré que la technique d'estimation la plus utilisée conduit à des variances proches de la BCR dans un grand nombre de situations. Cette étude a également permis d'analyser les performances quand on réduit l'information polarimétrique (Polarimétrie Compacte). Nous avons ensuite analysé l'influence de quelques écarts au modèle RvoG (fluctuations de la hauteur du sol et de la végétation, et décorrélation temporelle). La décorrélation temporelle semble être la perturbation la plus critique car elle peut fortement biaiser l'estimation. Finalement nous avons illustré, sur des forêts tropicales et tempérées, certains de ces résultats théoriques à l'aide de données acquises par les systèmes radar RAMSES et SETHI de l'ONERA en bande P. / Polarimetric and Interferometric SAR techniques (PolInSAR) offer a global solution for vegetal biomass parameters monitoring. In the scope of this thesis, we propose to analyze the estimation precision that can be achieved with those techniques for some parameters such as ground and vegetation height, based on one of the most widely used PolInSAR vegetation model (RVoG model). We have first determined the Cramer-Rao bound (CRB), which gives a lower bound on the estimation variance, for unbiased estimation. This study shows a high diversity of situations, with in the best cases a precision of around 1 meter for a sample size of 100 pixels. It was shown that the most commonly used estimation method leads to estimation variances close to the CRB in a lot of situations. This study also allowed us to analyze the performance loss when polarimetric information is reduced (Compact Polarimetry). Then, we analyzed the influence of some deviations from the RVoG model (ground and vegetation height fluctuations, and also temporal decorrelation). Temporal decorrelation seems to be the most concerning issue as it can lead to high estimation bias. These theoritical results have been illustrated on tropical and tempered forests using P band data acquired by RAMSES and SETHI, the ONERA radar systems.

The need for high speed and cost efficient inspection in manufacturing lineshas led to a vast usage of camera-based vision systems. The performance ofthese systems is sufficient to determine shape and size, but hardly to an accuracylevel comparable with traditional metrology tools. To achieve highprecision shape/position/defect measurements, the camera techniques haveto be combined with high performance image metrology techniques whichare developed and adapted to the manufactured components. The focus ofthis thesis is the application of enhanced image analysis as a tool for highprecision metrology. Dedicated algorithms have been developed, tested andevaluated in three practical cases ranging from micro manufacturing at submicronprecision to meter sized aerospace components with precision requirementsin the 10 μm range.The latter measurement challenge was solved by low cost standard consumerproducts, i.e. digital cameras in a stereo configuration and structured lightfrom a gobo-projector. Combined with high-precision image analysis and anew approach in camera calibration and 3D reconstruction for precise 3Dshape measurement of meter sized surfaces, the achievement was fulfilledand verified by two conventional measurement systems; a high precisioncoordinate measurement machine and a laser scanner.The sub-micron challenge was the implementation of image metrology forverification of micro manufacturing installations within a joint Europeaninfrastructure network, EUMINAfab. The results were an unpleasant surprisefor some of the participating laboratories, but became a big step forwardto improve the dimensional accuracy of the investigated laser micromachining, micro milling and micro-printing systems, since the accuracy ofthese techniques are very difficult to assess.The third high precision metrology challenge was the measurement of longrange,low-amplitude topographic structures on specular (shiny) aerodynamicsurfaces. In this case Fringe Reflection Technique (FRT) was appliedand image analysis algorithms were used to evaluate the fringe deformationas a measure of the surface slopes to obtain high resolution data. The resultwas compared with an interferometric analysis showing height deviation inthe range of tens of micrometers over a lateral extension of several cm. / <p>QC 20170523</p> / LOCOMACHS / EUMINAfab / Cleansky

Master of Agribusiness / Department of Agricultural Economics / Vincent Amanor-Boadu / Farming is an important industry in the United States. The custom harvesting industry plays a major role in feeding the world. Schemper Harvesting is a family-owned and operated custom harvesting service that employs 20-25 seasonal workers and understanding how to manage a custom harvesting business professionally and efficiently is the key for its success. Today, there is data available through JDLink on John Deere combine performance beginning in year 2012. The purpose of this study is to examine the usefulness of this JDLink data to assess the efficiency of each of Schemper Harvesting’s seven combines, including machine efficiency and different combine operators. The goal is to determine how the data can improve Schemper Harvesting’s overall performance. Statistical methods were used to analyze Schemper Harvesting’s performance. The analysis indicated that fuel is a major expense and there are ways Schemper Harvesting can conserve fuel. This information may prove valuable in being able to operate a combine more efficiently and save money on expenses. Overall, the objective is to improve Schemper Harvesting’s performance, which results in higher profit without sacrificing quality. Precision technology is an added expense to the business. Being able to justify this expense with profit is the answer. Fuel, labor and machinery are the biggest inputs in the custom harvesting business. These costs related to production agriculture have increased the demand for precision agriculture to increase efficiency and profitability. In order to compensate for the investment in technology, it has been demonstrated that it pays for itself. Making correct use of precision technology adds to productivity. With experience, operators improve increasing their overall efficiency. Incentive plans can be utilized through this data. With the availability of data, the costs and benefits of precision technology can be further evaluated. Five of the seven combines are operated by family members and the other two by non-family employees. This study shows that the performance of the non-family employees was below that of family members. The initial assessment for this difference may be attributed to experience because all the family members have been operating combines for most of their lives. This implies that employing people with excellent performance experience records and/or a need to train non-family employees to help them understand the performance expectations at Schemper Harvesting. The results indicate that tracking operational output performance indicators, such as acreage and volume harvest should be completed so that they may be assessed in concert with the technical indicators such as time and fuel use. The study provides the potential benefits of using John Deere’s JDLink data service providing telematics information for its customers with the latest precision agriculture technologies.

Master of Agribusiness / Department of Agricultural Economics / Kevin Dhuyvetter / This thesis was commissioned by Cooperative Producers, Inc. (CPI) of Hastings, Nebraska in order to better understand the preferences and uses of precision agriculture by customers within the company’s trade territory. With the rapid increase of precision agriculture (hardware, software, services, etc.) it is necessary to get a better understanding of what drives growers to adopt and implement precision agriculture practices. A paper survey was sent out in CPI’s monthly statements to patrons that also included instructions to be able to fill out an online survey if that was preferred. From that offering there were a total of 114 responses providing data from which several technology adoption models were estimated. Based on prior experience with precision agriculture and the development of services offered to growers, it is hypothesized that there are three primary variables influencing a grower’s decision to adopt precision agriculture. If the operation is managed by a younger grower (<40 years old), farms with a larger number of acres, and if a high percent of the operation’s acres are irrigated they will be more likely to adopt precision agriculture practices. The survey results generally revealed that younger farmers, larger farm size, and a higher percentage of irrigated acres did not increase the likelihood of utilizing precision agriculture. The questions asked in the survey were designed to provide information for the development of a tool that salespeople offering precision agriculture services could use to determine if a potential customer with be inclined to adopt and utilize precision agriculture. While some of the results were contrary to expectations they do offer insight into what type of customer adopts precision agriculture and a direction for CPI to move in order to maximize market penetration.

The GMT-Consortium Large Earth Finder (G-CLEF) will be a cross-dispersed, optical band echelle spectrograph to be delivered as the first light scientific instrument for the Giant Magellan Telescope (GMT) in 2022. G-CLEF is vacuumenclosed and fiber-fed to enable precision radial velocity (PRV) measurements, especially for the detection and characterization of low-mass exoplanets orbiting solar-type stars. The passband of G-CLEF is broad, extending from 3500 angstrom to . This passband provides good sensitivity at blue wavelengths for stellar abundance studies and deep red response for observations of high-redshift phenomena. The design of G-CLEF incorporates several novel technical innovations. We give an overview of the innovative features of the current design. G-CLEF will be the first PRV spectrograph to have a composite optical bench so as to exploit that material's extremely low coefficient of thermal expansion, high in-plane thermal conductivity and high stiffness-to-mass ratio. The spectrograph camera subsystem is divided into a red and a blue channel, split by a dichroic, so there are two independent refractive spectrograph cameras. The control system software is being developed in model-driven software context that has been adopted globally by the GMT. G-CLEF has been conceived and designed within a strict systems engineering framework. As a part of this process, we have developed a analytical toolset to assess the predicted performance of G-CLEF as it has evolved through design phases.