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.

Feed form and energy concentration of the diet affect growth performance and digestive tract traits of brown-egg laying pullets from hatching to 17 weeks of age

The influence of feed form and energy concentration of the diet on growth performance and the development of the gastrointestinal tract (GIT) was studied in brown-egg laying pullets. Diets formed a 2 x 5 factorial with 2 feed forms (mash vs. crumbles) and 5 levels of energy differing in 50 kcal AMEn/kg. For the entire study (0 to 17 wk of age) feeding crumbles increased ADFI (52.9 vs. 49.7 g; P < 0.001) and ADG (12.7 vs. 11.6 g; P < 0.001) and improved feed conversion ratio (FCR; 4.18 vs. 4.27; P < 0.001). An increase in the energy content of the diet decreased ADFI linearly (P < 0.001) and improved FCR quadratically (P < 0.01) but energy intake (kcal AMEn/d) was not affected. BW uniformity was higher (P < 0.05) in pullets fed crumbles than in those fed mash but was not affected (P > 0.05) by energy content of the diet. At 5, 10, and 17 wk of age, the relative weight (RW, % BW) of the GIT and the gizzard, and gizzard digesta content were lower (P < 0.05 to P < 0.001) and gizzard pH was higher (P < 0.05 to P < 0.001) in pullets fed crumbles than in pullets fed mash. Energy concentration of the diet did not affect any of the GIT variables studied. In summary, feeding crumbles improved pullet performance and reduced the RW of the GIT and gizzard, and increased gizzard pH at all ages. An increase in the energy content of the diet improved FCR from 0 to 17 wk of age. The use of crumbles and the increase in the AMEn content of the diet might be used adventageously when the objetive is to increase the BW of the pullets. However, crumbles affected the development and weight of the organs of the GIT, which might have negative effects on feed intake and egg production at the beginning of the egg laying cycle.

Experimental study of the thermal-energy performance of an insulated vegetal facade under summer conditions in a continental mediterranean climate

The use of vegetal systems in facades affects the reduction of the buildings' energy demand, the attenuation of the urban heat island (UHI) and the filtration of pollutants present in the air. Even so, up to now the knowledge about the effect of this type of systems on the thermal performance of insulated facades is limited. This article presents the results of an experimental study carried out in a vegetal facade located in a continental Mediterranean climate zone. The objective is to study the effect of a vegetal finishing, formed by plants and substrate, on the thermal-energy performance of an insulated facade under summer conditions. To this effect, the thermal data obtained from two full-scale experimental mock-ups of the same dimensions and composition of the enclosure and only different in the south facade's enclosure where one incorporates a vegetation layer are compared and analysed. The results show that, in spite of the high thermal resistance of the enclosure, the effect of the vegetation is very positive, particularly in the warmer hours of the day. Therefore, vegetal facades can be used as a passive cooling strategy, reducing the consumption of energy for refrigeration and improving the comfort conditions of the users. (C) 2014 Elsevier Ltd. All rights reserved.

Effect of level of fiber of the rearing phase diets on egg production, digestive tract traits, and body measurements of brown egg-laying hens fed diets differing in energy concentration

This research studied the effects of additional fiber in the rearing phase diets on egg production, gastrointestinal tract (GIT) traits, and body measurements of brown egg-laying hens fed diets varying in energy concentration from 17 to 46 wk of age. The experiment was completely randomized with 10 treatments arranged as a 5 × 2 factorial with 5 rearing phase diets and 2 laying phase diets. During the rearing phase, treatments consisted of a control diet based on cereals and soybean meal and 4 additional diets with a combination of 2 fiber sources (cereal straw and sugar beet pulp, SBP) at 2 levels (2 and 4%). During the laying phase, diets differed in energy content (2,650 vs. 2,750 kcal AMEn/kg) but had the same amino acid content per unit of energy. The rearing diet did not affect any production trait except egg production that was lower in birds fed SBP than in birds fed straw (91.6 and 94.1%, respectively; P < 0.05). Laying hens fed the high energy diet had lower feed intake (P < 0.001), better feed conversion (P < 0.01), and greater BW gain (P < 0.05) than hens fed the low energy diet but egg production and egg weight were not affected. At 46 wk of age, none of the GIT traits was affected by previous dietary treatment. At this age, hen BW was positively related with body length (r = 0.500; P < 0.01), tarsus length (r = 0.758; P < 0.001), and body mass index (r = 0.762; P < 0.001) but no effects of type of diet on these traits were detected. In summary, the inclusion of up to 4% of a fiber source in the rearing diets did not affect GIT development of the hens but SBP reduced egg production. An increase in the energy content of the laying phase diet reduced ADFI and improved feed efficiency but did not affect any of the other traits studied.

The temporal evolution of the energy flux across scales in homogeneous turbulence

A temporal study of energy transfer across length scales is performed in 3D numerical simulations of homogeneous shear flow and isotropic turbulence. The average time taken by perturbations in the energy flux to travel between scales is measured and shown to be additive. Our data suggests that the propagation of disturbances in the energy flux is independent of the forcing and that it defines a ‘velocity’ that determines the energy flux itself. These results support that the cascade is, on average, a scale-local process where energy is continuously transmitted from one scale to the next in order of decreasing size.