Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Integrated learning of computer applications for production engineering

A high productivity rate in Engineering is related to an efficient management of the flow of the large quantities of information and associated decision making activities that are consubstantial to the Engineering processes both in design and production contexts. Dealing with such problems from an integrated point of view and mimicking real scenarios is not given much attention in Engineering degrees. In the context of Engineering Education, there are a number of courses designed for developing specific competencies, as required by the academic curricula, but not that many in which integration competencies are the main target. In this paper, a course devoted to that aim is discussed. The course is taught in a Marine Engineering degree but the philosophy could be used in any Engineering field. All the lessons are given in a computer room in which every student can use each all the treated software applications. The first part of the course is dedicated to Project Management: the students acquire skills in defining, using Ms-PROJECT, the work breakdown structure (WBS), and the organization breakdown structure (OBS) in Engineering projects, through a series of examples of increasing complexity, ending up with the case of vessel construction. The second part of the course is dedicated to the use of a database manager, Ms-ACCESS, for managing production related information. A series of increasing complexity examples is treated ending up with the management of the pipe database of a real vessel. This database consists of a few thousand of pipes, for which a production timing frame is defined, which connects this part of the course with the first one. Finally, the third part of the course is devoted to the work with FORAN, an Engineering Production package of widespread use in the shipbuilding industry. With this package, the frames and plates where all the outfitting will be carried out are defined through cooperative work by the studens, working simultaneously in the same 3D model. In the paper, specific details about the learning process are given. Surveys have been posed to the students in order to get feed-back from their experience as well as to assess their satisfaction with the learning process. Results from these surveys are discussed in the paper

Aquaponics: integrating fish feeding rates and ion waste production for strawberry hydroponics

Aquaponics is the science of integrating intensive fish aquaculture with plant production in recirculating water systems. Although ion waste production by fish cannot satisfy all plant requirements, less is known about the relationship between total feed provided for fish and the production of milliequivalents (mEq) of different macronutrients for plants, especially for nutrient flow hydroponics used for strawberry production in Spain. That knowledge is essential to consider the amount of macronutrients available in aquaculture systems so that farmers can estimate how much nutrient needs to be supplemented in the waste water from fish, to produce viable plant growth. In the present experiment, tilapia (Oreochromis niloticus L.) were grown in a small-scale recirculating system at two different densities while growth and feed consumption were noted every week for five weeks. At the same time points, water samples were taken to measure pH, EC25, HCO3 – , Cl – , NH4 + , NO2 – , NO3 – , H2PO4 – , SO4 2– , Na + , K+ , Ca 2+ and Mg 2+ build up. The total increase in mEq of each ion per kg of feed provided to the fish was highest for NO3 - , followed, in decreasing order, by Ca 2+ , H2PO4 – , K+ , Mg 2+ and SO4 2– . The total amount of feed required per mEq ranged from 1.61- 13.1 kg for the four most abundant ions (NO3 – , Ca 2+ , H2PO4 – and K+ ) at a density of 2 kg fish m–3 , suggesting that it would be rather easy to maintain small populations of fish to reduce the cost of hydroponic solution supplementation for strawberries.

A simplified Probabilistic Safety Assesment of a Steam-Methane Reforming Hydrogen Production Plant coupled to a High-Temperature Gas Cooled Nuclear Reactor

A Probabilistic Safety Assessment (PSA) is being developed for a steam-methane reforming hydrogen production plant linked to a High-Temperature Gas Cooled Nuclear Reactor (HTGR). This work is based on the Japan Atomic Energy Research Institute’s (JAERI) High Temperature Test Reactor (HTTR) prototype in Japan. This study has two major objectives: calculate the risk to onsite and offsite individuals, and calculate the frequency of different types of damage to the complex. A simplified HAZOP study was performed to identify initiating events, based on existing studies. The initiating events presented here are methane pipe break, helium pipe break, and PPWC heat exchanger pipe break. Generic data was used for the fault tree analysis and the initiating event frequency. Saphire was used for the PSA analysis. The results show that the average frequency of an accident at this complex is 2.5E-06, which is divided into the various end states. The dominant sequences result in graphite oxidation which does not pose a health risk to the population. The dominant sequences that could affect the population are those that result in a methane explosion and occur 6.6E-8/year, while the other sequences are much less frequent. The health risk presents itself if there are people in the vicinity who could be affected by the explosion. This analysis also demonstrates that an accident in one of the plants has little effect on the other. This is true given the design base distance between the plants, the fact that the reactor is underground, as well as other safety characteristics of the HTGR. Sensitivity studies are being performed in order to determine where additional and improved data is needed.

Optimización de la programación(scheduling) en Talleres de Mecanizado

Los problemas de programación de tareas son muy importantes en el mundo actual. Se puede decir que se presentan en todos los fundamentos de la industria moderna, de ahí la importancia de que estos sean óptimos, de forma que se puedan ahorrar recursos que estén asociados al problema. La programación adecuada de trabajos en procesos de manufactura, constituye un importante problema que se plantea dentro de la producción en muchas empresas. El orden en que estos son procesados, no resulta indiferente, sino que determinará algún parámetro de interés, cuyos valores convendrá optimizar en la medida de lo posible. Así podrá verse afectado el coste total de ejecución de los trabajos, el tiempo necesario para concluirlos o el stock de productos en curso que será generado. Esto conduce de forma directa al problema de determinar cuál será el orden más adecuado para llevar a cabo los trabajos con vista a optimizar algunos de los anteriores parámetros u otros similares. Debido a las limitaciones de las técnicas de optimización convencionales, en la presente tesis se presenta una metaheurística basada en un Algoritmo Genético Simple (Simple Genetic Algorithm, SGA), para resolver problemas de programación de tipo flujo general (Job Shop Scheduling, JSS) y flujo regular (Flow Shop Scheduling, FSS), que están presentes en un taller con tecnología de mecanizado con el objetivo de optimizar varias medidas de desempeño en un plan de trabajo. La aportación principal de esta tesis, es un modelo matemático para medir el consumo de energía, como criterio para la optimización, de las máquinas que intervienen en la ejecución de un plan de trabajo. Se propone además, un método para mejorar el rendimiento en la búsqueda de las soluciones encontradas, por parte del Algoritmo Genético Simple, basado en el aprovechamiento del tiempo ocioso. ABSTRACT The scheduling problems are very important in today's world. It can be said to be present in all the basics of modern industry, hence the importance that these are optimal, so that they can save resources that are associated with the problem. The appropriate programming jobs in manufacturing processes is an important problem that arises in production in many companies. The order in which they are processed, it is immaterial, but shall determine a parameter of interest, whose values agree optimize the possible. This may be affected the total cost of execution of work, the time needed to complete them or the stock of work in progress that will be generated. This leads directly to the problem of determining what the most appropriate order to carry out the work in order to maximize some of the above parameters or other similar. Due to the limitations of conventional optimization techniques, in this work present a metaheuristic based on a Simple Genetic Algorithm (Simple Genetic Algorithm, SGA) to solve programming problems overall flow rate (Job Shop Scheduling, JSS) and regular flow (Flow Shop Scheduling, FSS), which are present in a workshop with machining technology in order to optimize various performance measures in a plan. The main contribution of this thesis is a mathematical model to measure the energy consumption as a criterion for the optimization of the machines involved in the implementation of a work plan. It also proposes a method to improve performance in finding the solutions, by the simple genetic algorithm, based on the use of idle time.

Modelo multifactorial para optimización de la productividad en el proceso de generación de energía eléctrica : aplicación al caso de las centrales hidroeléctricas venezolanas

Las organizaciones son sistemas o unidades sociales, compuestas por personas que interactúan entre sí, para lograr objetivos comunes. Uno de sus objetivos es la productividad. La productividad es un constructo multidimensional en la que influyen aspectos tecnológicos, económicos, organizacionales y humanos. Diversos estudios apoyan la influencia de la motivación de las personas, de las habilidades y destrezas de los individuos, de su talento para desempeñar el trabajo, así como también del ambiente de trabajo presente en la organización, en la productividad. Por esta razón, el objetivo general de la investigación, es analizar la influencia entre los factores humanos y la productividad. Se hará énfasis en la persona como factor productivo clave, para responder a las interrogantes de la investigación, referidas a cuáles son las variables humanas que inciden en la productividad, a la posibilidad de plantear un modelo de productividad que considere el impacto del factor humano y la posibilidad de encontrar un método para la medición de la productividad que contemple la percepción del factor humano. Para resolver estas interrogantes, en esta investigación se busca establecer las relaciones entre las variables humanas y la productividad, vistas desde la perspectiva de tres unidades de análisis diferentes: individuo, grupo y organización, para la formulación de un modelo de productividad humana y el diseño de un instrumento para su medida. Una de las principales fuente de investigación para la elección de las variables humanas, la formulación del modelo, y el método de medición de la productividad, fue la revisión de la literatura disponible sobre la productividad y el factor humano en las organizaciones, lo que facilitó el trazado del marco teórico y conceptual. Otra de las fuentes para la selección fue la opinión de expertos y de especialistas directamente involucrados en el sector eléctrico venezolano, lo cual facilitó la obtención de un modelo, cuyas variables reflejasen la realidad del ámbito en estudio. Para aportar una interpretación explicativa del fenómeno, se planteó el modelo de los Factores Humanos vs Productividad (MFHP), el cual se analizó desde la perspectiva del análisis causal y fue conformado por tres variables latentes exógenas denominadas: factores individuales, factores grupales y factores organizacionales, que estaban relacionadas con una variable latente endógena denominada productividad. El MFHP se formuló mediante la metodología de los modelos de ecuaciones estructurales (SEM). Las relaciones inicialmente propuestas entre las variables latentes fueron corroboradas por los ajustes globales del modelo, se constataron las relaciones entre las variables latentes planteadas y sus indicadores asociados, lo que facilitó el enunciado de 26 hipótesis, de las cuales se comprobaron 24. El modelo fue validado mediante la estrategia de modelos rivales, utilizada para comparar varios modelos SEM, y seleccionar el de mejor ajuste, con sustento teórico. La aceptación del modelo se realizó mediante la evaluación conjunta de los índices de bondad de ajuste globales. Asimismo, para la elaboración del instrumento de medida de la productividad (IMPH), se realizó un análisis factorial exploratorio previo a la aplicación del análisis factorial confirmatorio, aplicando SEM. La revisión de los conceptos de productividad, la incidencia del factor humano, y sus métodos de medición, condujeron al planteamiento de métodos subjetivos que incorporaron la percepción de los principales actores del proceso productivo, tanto para la selección de las variables, como para la formulación de un modelo de productividad y el diseño de un instrumento de medición de la productividad. La contribución metodológica de este trabajo de investigación, ha sido el empleo de los SEM para relacionar variables que tienen que ver con el comportamiento humano en la organización y la productividad, lo cual abre nuevas posibilidades a la investigación en este ámbito. Organizations are social systems or units composed of people who interact with each other to achieve common goals. One objective is productivity, which is a multidimensional construct influenced by technological, economic, organizational and human aspects. Several studies support the influence on productivity of personal motivation, of the skills and abilities of individuals, of their talent for the job, as well as of the work environment present in the organization. Therefore, the overall objective of this research is to analyze the influence between human factors and productivity. The emphasis is on the individual as a productive factor which is key in order to answer the research questions concerning the human variables that affect productivity and to address the ability to propose a productivity model that considers the impact of the human factor and the possibility of finding a method for the measurement of productivity that includes the perception of the human factor. To consider these questions, this research seeks to establish the relationships between human and productivity variables, as seen from the perspective of three different units of analysis: the individual, the group and the organization, in order to formulate a model of human productivity and to design an instrument for its measurement. A major source of research for choosing the human variables, model formulation, and method of measuring productivity, was the review of the available literature on productivity and the human factor in organizations which facilitated the design of the theoretical and conceptual framework. Another source for the selection was the opinion of experts and specialists directly involved in the Venezuelan electricity sector which facilitated obtaining a model whose variables reflect the reality of the area under study. To provide an interpretation explaining the phenomenon, the model of the Human Factors vs. Productivity Model (HFPM) was proposed. This model has been analyzed from the perspective of causal analysis and was composed of three latent exogenous variables denominated: individual, group and organizational factors which are related to a latent variable denominated endogenous productivity. The HFPM was formulated using the methodology of Structural Equation Modeling (SEM). The initially proposed relationships between latent variables were confirmed by the global fits of the model, the relationships between the latent variables and their associated indicators enable the statement of 26 hypotheses, of which 24 were confirmed. The model was validated using the strategy of rival models, used for comparing various SEM models and to select the one that provides the best fit, with theoretical support. The acceptance of the model was performed through the joint evaluation of the adequacy of global fit indices. Additionally, for the development of an instrument to measure productivity, an exploratory factor analysis was performed prior to the application of a confirmatory factor analysis, using SEM. The review of the concepts of productivity, the impact of the human factor, and the measurement methods led to a subjective methods approach that incorporated the perception of the main actors of the production process, both for the selection of variables and for the formulation of a productivity model and the design of an instrument to measure productivity. The methodological contribution of this research has been the use of SEM to relate variables that have to do with human behavior in the organization and with productivity, opening new possibilities for research in this area.

Analysing written production competence descriptors for academic and professional purposes and their calibration to the CEFR

The Common European Framework of Reference for Languages (CEFR) "describes in a comprehensive way what language learners have to learn to do in order to use a language for communication and what knowledge and skills they have to develop so as to be able to act effectively" (Council of Europe, 2001: 1). This paper reports on the findings of two studies whose purpose was to assess written production competence descriptors meant for their inclusion into the Academic and Professional English Language Portfolio KELP) for students of engineering and architecture. The main objective of these studies was to establish whether the language competence descriptors were a satisfactory valid tool in their language programmes from the point of view of clarity, relevance and reliability, as perceived by the students and fellow English for Academic Purposes (RAP) / English for Science and Technology (EST) instructors. The studies shed light on how to improve unsatisfactory descriptors. Results show that the final descriptor lists were on the whole well calibrated and fairly well written: the great majority was considered valid for both teachers and students involved.

Indoor characterization at production sccale: 200 kWp of CPV solar simulator measurements

In order to complement ISFOC’s characterization capabilities, a Helios 3198 CPV Solar Simulator was installed in summer 2010. This Solar Simulator, based on a parabolic mirror and a high-intensity, small area Xenon flash lamp was developed by the Instituto de Energía Solar in Madrid [1] and is manufactured and distributed by Soldaduras Avanzadas [2]. This simulator is used not only for R&D purposes, but as a quality control tool for incoming modules that are to be installed in ISFOC’s CPV plants. In this paper we will discuss the results of recent measurements of close to 5000 modules, the entire production of modules corresponding to a small CPV power plant (200 kWp). We scrutinize the resultant data for signs of drift in the measurements, and analyze the light quality before and after, to check for changes in spectrum or spatial uniformity.)

On the complexity of radiation models for PV energy production calculation

Several authors have analysed the changes of the probability density function of the solar radiation with different time resolutions. Some others have approached to study the significance of these changes when produced energy calculations are attempted. We have undertaken different transformations to four Spanish databases in order to clarify the interrelationship between radiation models and produced energy estimations. Our contribution is straightforward: the complexity of a solar radiation model needed for yearly energy calculations, is very low. Twelve values of monthly mean of solar radiation are enough to estimate energy with errors below 3%. Time resolutions better than hourly samples do not improve significantly the result of energy estimations.

Crack origin and detection in thin cristallyne solar cells in a production line

In order to reduce cost and make up for the rising price of silicon, silicon wafers are sliced thinner and wider,eading to weaker wafers and increased breakage rates during fabrication process. In this work we have analysed different cracks origins and their effect on wafer’s mechanical strength. To enhance wafer’s strength some etching methods have been tested. Also, we have analysed wafers from different points of an entire standard production process. Mechanical strength of the wafers has been obtained via the four line bending test and detection of cracks has been tested with Resonance Ultrasonic Vibration (RUV) system, developed by the University of South Florida.

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Research and production of a multi-view streaming page

The electronic and mechanical media such as film, television, photography, offset, are just examples of how fast and important the technological development had become in society. Nevertheless the outcoming technologies and the continuous development had provided newer and better possibilities every time for having advanced services. Nowadays multi-view video has been developed with different tools and applications, having as main goal to be more innovative and bring within technical offerings in a friendly for all users in general, in terms of managing and accessibility (just internet connection is needed). The intention of all technologies is to generate an innovation in order to gain more users and start being popular, therefore is important to realize an implementation in this case. In such terms realizing about the outreach that Multi View Video, an importance to become more global in this days, an application that supports this aim such as the possibility of language selection within the use of a same scenario has been realized. Finally is important to point out that thanks to the Multi View Video's continuous progress in technology a more intercultural market will be reachable, making of it a shared society growth on the world's global development. � ��� ���� ������� ��� �� ��� ��� �������� ��� ���� ��� ��� ������ ���������� � ���� � �� ���� ���� � ���� �� � � ���� � � ��� ��� �� ��� �� � ��� ��� ��������� �� � ����� ��������� ��� � ��� � ���� ���� ����� ����������� ��� ��� �� � ������������� �� �������� �������� ������� ������� �� ����� �������� ��� � � �� ���� �������� ���� ����� �������� �������� �� ������ ���� �� � ����������� ������������� � � ��!��� � � � �� ������� ��� ��������"������ � �� ���������� �������� ��� �� ������ � ����� ����� ��� ��� �� � �� �� ���� �� ��� �� ���� � � � �� ��� ������ �� �� ��� �� �� ��� �� � �� ��� #�� ��� ������� � ��� �� � �� ������$������� � ��� ��� # ������� � ����� ����� �� ���� �% ���% �������� ��� ����� ����������� �� ������� �� � �� ������ ��� ���� �� ��� �� � ����� �� � �� � �� ����� ��� ��� ���� � � �� ��� ��������� ����� ��� � � �� ���������������������� ����������� ��� #����& ������ �� ��� �� � ���� � ��� � �� � ���'�� �� ��� ��� � % ��� % ���(�� ��� ������ � �� ���� �� ���������� ���� �� � � ��� � ����� '� �� ��� ��� ���������� ��' ������ ������ ������ � ��� �� ����� ����� ��(������������������� ��� � �

Integrated learning of production engineering software applications in a shipbuilding context

Acourse focused on the acquisition of integration competencies in ship production engineering, organized in collaboration with selected industry partners, is presented in this paper. The first part of the course is dedicated to Project Management: the students acquire skills in defining, using MS-PROJECT, the work breakdown structure (WBS), and the organization breakdown structure (OBS) in Engineering projects, through a series of examples of increasing complexity with the final one being the construction planning of a vessel. The second part of the course is dedicated to the use of a database manager, MS-ACCESS, in managing production related information.Aseries of increasing complexity examples is treated, the final one being the management of the piping database of a real vessel. This database consists of several thousand pipes, for which a production timing frame is defined connecting this part of the course with the first one. Finally, the third part of the course is devoted to working withFORAN,an Engineering Production application developed bySENERand widely used in the shipbuilding industry. With this application, the structural elements where all the outfittings will be located are defined through cooperative work by the students, working simultaneously in the same 3D model. In this paper, specific details about the learning process are given. Surveys have been posed to the students in order to get feedback from their experience as well as to assess their satisfaction with the learning process, compared to more traditional ones. Results from these surveys are discussed in the paper.

Descriptive study of production factors affecting performance traits in growing-finishing pgis in Spain.

The objective of this study was to build up a data set including productive performance and production factors data of growing-finishing (GF) pigs in Spain in order to perform a representative and reliable description of the traits of Spanish growing-finishing pig industry. Data from 764 batches from 452 farms belonging to nine companies (1,157,212 pigs) were collected between 2008 and 2010 through a survey including five parts: general, facilities, feeding, health status and performance. Most studied farms had only GF pigs on their facilities (94.7%), produced ‘industrial’ pigs (86.7%), had entire male and female (59.5%) and Pietrain-sired pigs (70.0%), housed between 13-20 pigs per pen (87.2%), had  50% of slatted floor (70%), single-space dry feeder (54.0%), nipple drinker (88.7%) and automatic ventilation systems (71.2%). A 75.0% of the farms used three feeding phases using mainly pelleted diets (91.0%), 61.3% performed three or more antibiotic treatments and 36.5% obtained water from the public supply. Continuous variables studied had the following average values: number of pigs placed per batch, 1,515 pigs; initial and final body weight, 19.0 and 108 kg; length of GF period, 136 days; culling rate, 1.4%; barn occupation, 99.7%; feed intake per pig and fattening cycle, 244 kg; daily gain, 0.657 kg; feed conversion ratio, 2.77 kg kg-1 and mortality rate, 4.3%. Data reflecting the practical situation of the Spanish growing and finishing pig production and it may contribute to develop new strategies in order to improve the productive and economic efficiency of GF pig units.

New tool to assess the force production in the swallow

8 men artistic gymnasts were evaluated with a new test protocol in order to assess isometric strength in an specific hold position on still rings. The proposed test protocol measures the force applied the gymnast on the rings from an initial lying prone position on a force platform while he is trying to achieve the Swallow (or Hirondelle) position. The vertical force (FZ) from the forcetime curve registered (100 Hz) was used and it showed a descent from the initial body weight level caused by the gymnast force on the rings and, later, a maximal isometric force period. Fundamental and derivate variables to extract from the evolution of Fz were defined. Results showed significant statistical differences between gymnasts that could perform the Swallow (P) from those that could not (NP) (pmenor que0.05). Performer gymnasts were characterized by a higher percentage of body weight descent and higher strength in relation to body mass (pmenor que0.05). The practical application of this tool could be to provide coaches with information about how close the gymnast is to perform the Swallow.