The observatory of intelligence and territorial development, tool for innovation in processes of territorial planning in municipalities of the province of Jujuy

El municipio es considerado como un espacio donde sus habitantes comparten no sólo el territorio sino también los problemas y los recursos existentes. La institución municipal -como gobierno local- es el ámbito en el cual se toman decisiones sobre el territorio, que implican a sus habitantes. En cuanto a los actores, estos pueden ser funcionarios, empleados y la comunidad (individual y organizada en ongs), todos aportan sus conocimientos y valores, pero tienen diferentes intereses y diferentes tiempos. Vinculada a las decisiones, encontramos que la forma en que se gestiona la información territorial, es determinante si se pretende apuntar hacia acciones con impacto positivo, y sustentables en lo ambiental y en el tiempo. Este trabajo toma tres municipios: San Salvador de Jujuy, capital de la provincia localizada en los Valles Templados; San Pedro de Jujuy, principal municipio de la región de las Yungas y Tilcara en la Quebrada de Humahuaca. El aporte de la Inteligencia Territorial, a través del observatorio OIDTe, permite analizar los modos de gestión de la información, especialmente mediante el uso de las tecnologías de la información y comunicación (pagina web municipal, equipamiento informático en las oficinas, estrategias de comunicación y vinculación con la población) y mediante la organización de las estructuras administrativas (organigrama) por las cuales circula la información municipal. Además, con la participación enriquecedora de equipos multidisciplinarios en las diferentes etapas. Se busca, a partir de un diagnóstico, generar estrategias para la introducción de innovaciones con los propios actores municipales, a partir de las situaciones y modos culturales propios de cada lugar, incorporando los marcos conceptuales de la Inteligencia Territorial. En este sentido el OIDTe al promover el entendimiento entre los actores, institucionales y la sociedad, facilita la coordinación de diferentes intereses propiciando la toma de decisiones por acuerdos. Asimismo, el método Portulano, puede orientar la introducción de innovaciones en la coordinación de la información cartográfica, para que las diferentes oficinas puedan complementar sus aportes y la comunicación hacia fuera de la institución. En la fase de diagnóstico, se aplicaron entrevistas a informantes claves, se realizó un workshop con técnicos de planta permanente y funcionarios de áreas que manejan información territorial, y de planificación. También por la importancia de la capacidad instalada de recursos humanos, se analizó el nivel de instrucción y la capacitación con que cuenta el personal de planta permanente de cada área

The observatory of intelligence and territorial development, tool for innovation in processes of territorial planning in municipalities of the province of Jujuy

El municipio es considerado como un espacio donde sus habitantes comparten no sólo el territorio sino también los problemas y los recursos existentes. La institución municipal -como gobierno local- es el ámbito en el cual se toman decisiones sobre el territorio, que implican a sus habitantes. En cuanto a los actores, estos pueden ser funcionarios, empleados y la comunidad (individual y organizada en ongs), todos aportan sus conocimientos y valores, pero tienen diferentes intereses y diferentes tiempos. Vinculada a las decisiones, encontramos que la forma en que se gestiona la información territorial, es determinante si se pretende apuntar hacia acciones con impacto positivo, y sustentables en lo ambiental y en el tiempo. Este trabajo toma tres municipios: San Salvador de Jujuy, capital de la provincia localizada en los Valles Templados; San Pedro de Jujuy, principal municipio de la región de las Yungas y Tilcara en la Quebrada de Humahuaca. El aporte de la Inteligencia Territorial, a través del observatorio OIDTe, permite analizar los modos de gestión de la información, especialmente mediante el uso de las tecnologías de la información y comunicación (pagina web municipal, equipamiento informático en las oficinas, estrategias de comunicación y vinculación con la población) y mediante la organización de las estructuras administrativas (organigrama) por las cuales circula la información municipal. Además, con la participación enriquecedora de equipos multidisciplinarios en las diferentes etapas. Se busca, a partir de un diagnóstico, generar estrategias para la introducción de innovaciones con los propios actores municipales, a partir de las situaciones y modos culturales propios de cada lugar, incorporando los marcos conceptuales de la Inteligencia Territorial. En este sentido el OIDTe al promover el entendimiento entre los actores, institucionales y la sociedad, facilita la coordinación de diferentes intereses propiciando la toma de decisiones por acuerdos. Asimismo, el método Portulano, puede orientar la introducción de innovaciones en la coordinación de la información cartográfica, para que las diferentes oficinas puedan complementar sus aportes y la comunicación hacia fuera de la institución. En la fase de diagnóstico, se aplicaron entrevistas a informantes claves, se realizó un workshop con técnicos de planta permanente y funcionarios de áreas que manejan información territorial, y de planificación. También por la importancia de la capacidad instalada de recursos humanos, se analizó el nivel de instrucción y la capacitación con que cuenta el personal de planta permanente de cada área

Sm-Nd, Rb-Sr, and He isotopic composition and hydrocarbon gases in rocks and minerals from the Markov Deep, Mid-Atlantic Ridge rift valley

The paper presents characteristics of the Nd and Sr isotopic systems of ultrabasic rocks, gabbroids, plagiogranites, and their minerals as well as data on helium and hydrocarbons in fluid inclusions of the same samples. Materials presented in this publication were obtained by studying samples dredged from the MAR crest zone at 5°-6°N (U/Pb zircon dating, geochemical and petrological-mineralogical studies). It was demonstrated that variations in the isotopic composition of He entrapped in rocks and minerals were controlled by variable degrees of mixing of juvenile He, which is typical of basaltic glass for MAR (DM source), and atmospheric He. Increase in the atmospheric He fraction in plutonic rocks and, to a lesser degree, in their minerals reflects involvement of seawater or hydrated material of the oceanic crust in magmatic and postmagmatic processes. This conclusion finds further support in positive correlation between the fraction of mantle He (R ratio) and 87Sr/86Sr ratio. High-temperature hydration of ultrabasic rocks (amphibolization) was associated with increase in the fraction of mantle He, while their low-temperature hydration (serpentinization) was accompanied by drastic decrease in this fraction and significant increase in 87Sr/86Sr ratio. Insignificant variations in 143Nd/144Nd (close to 0.5130) and 87Sr/86Sr (0.7035) in most of gabbroids and plagiogranites as well as the fraction of mantle He in these rocks, amphibolites, and their ore minerals indicate that the melts were derived from the depleted mantle. Similar e-Nd values of gabbroids, plagiogranites, and fresh harzburgites (6.77-8.39) suggest that these rocks were genetically related to a single mantle source. e-Nd value of serpentinized lherzolites (2.62) likely reflects relations of these relatively weakly depleted mantle residues to another source. Aforementioned characteristics of the rocks generally reflect various degrees of mixing of depleted mantle components with crustal components (seawater) during metamorphic and hydrothermal processes that accompanied formation of the oceanic crust.

State-business relations in the smaller gulf monarchies -- the role of business actors in the decision-making process

The Arab monarchies of the Gulf have been undergoing striking socio-economic changes caused by the ending of the rent-based welfare state model on which they had largely relied since the 1950s. In this perspective, this paper aims at examining the comparative role of local business communities in affecting the orientations and the outcomes of the policies implemented during the period of high oil prices in the 2000s. This paper pays a special attention to the impact of the Arab Spring on the state-business relations in two of the smaller Gulf monarchies (Bahrain and Oman).

ERP Software Selection Processes: A Case Study in the Metal Transformation Sector

When a firm decides to implement ERP softwares, the resulting consequences can pervade all levels, includ- ing organization, process, control and available information. Therefore, the first decision to be made is which ERP solution must be adopted from a wide range of offers and vendors. To this end, this paper describes a methodology based on multi-criteria factors that directly affects the process to help managers make this de- cision. This methodology has been applied to a medium-size company in the Spanish metal transformation sector which is interested in updating its IT capabilities in order to obtain greater control of and better infor- mation about business, thus achieving a competitive advantage. The paper proposes a decision matrix which takes into account all critical factors in ERP selection.

A New Fast Motion Estimation and Mode Decision algorithm for H.264 Depth Maps encoding in Free Viewpoint TV

In this paper, we consider a scenario where 3D scenes are modeled through a View+Depth representation. This representation is to be used at the rendering side to generate synthetic views for free viewpoint video. The encoding of both type of data (view and depth) is carried out using two H.264/AVC encoders. In this scenario we address the reduction of the encoding complexity of depth data. Firstly, an analysis of the Mode Decision and Motion Estimation processes has been conducted for both view and depth sequences, in order to capture the correlation between them. Taking advantage of this correlation, we propose a fast mode decision and motion estimation algorithm for the depth encoding. Results show that the proposed algorithm reduces the computational burden with a negligible loss in terms of quality of the rendered synthetic views. Quality measurements have been conducted using the Video Quality Metric.

Hydrologic models for emergency decision support using Bayesian networks

In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited number sensors) and partial knowledge about the structure and behavior of the river basin. This is a case of reasoning about a complex dynamic system with uncertainty and real-time constraints where bayesian networks can be used to provide an effective support. In this paper we describe a solution with spatio-temporal bayesian networks to be used in a context of emergencies produced by river floods. In the paper we describe first a set of types of causal relations for hydrologic processes with spatial and temporal references to represent the dynamics of the river basin. Then we describe how this was included in a computer system called SAIDA to provide assistance to operators in charge of control in a river basin. Finally the paper shows experimental results about the performance of the model.

Outsourcing and acquisition models comparison related to IT supplier selection decision analysis

This paper presents a comparison of acquisition models related to decision analysis of IT supplier selection. The main standards are: Capability Maturity Model Integration for Acquisition (CMMI-ACQ), ISO / IEC 12207 Information Technology / Software Life Cycle Processes, IEEE 1062 Recommended Practice for Software Acquisition, the IT Infrastructure Library (ITIL) and the Project Management Body of Knowledge (PMBOK) guide. The objective of this paper is to compare the previous models to find the advantages and disadvantages of them for the future development of a decision model for IT supplier selection.

Data Processing Modeling in Decision Support Systems.

Due to the advancement of both, information technology in general, and databases in particular; data storage devices are becoming cheaper and data processing speed is increasing. As result of this, organizations tend to store large volumes of data holding great potential information. Decision Support Systems, DSS try to use the stored data to obtain valuable information for organizations. In this paper, we use both data models and use cases to represent the functionality of data processing in DSS following Software Engineering processes. We propose a methodology to develop DSS in the Analysis phase, respective of data processing modeling. We have used, as a starting point, a data model adapted to the semantics involved in multidimensional databases or data warehouses, DW. Also, we have taken an algorithm that provides us with all the possible ways to automatically cross check multidimensional model data. Using the aforementioned, we propose diagrams and descriptions of use cases, which can be considered as patterns representing the DSS functionality, in regard to DW data processing, DW on which DSS are based. We highlight the reusability and automation benefits that this can be achieved, and we think this study can serve as a guide in the development of DSS.

Commonalities between networking in multiplayer computer games and negotiation processes in a future multi-layered Air Traffic Management (ATM) system

First, this paper describes a future layered Air Traffic Management (ATM) system centred in the execution phase of flights. The layered ATM model is based on the work currently performed by SESAR [1] and takes into account the availability of accurate and updated flight information ?seen by all? across the European airspace. This shared information of each flight will be referred as Reference Business Trajectory (RBT). In the layered ATM system, exchanges of information will involve several actors (human or automatic), which will have varying time horizons, areas of responsibility and tasks. Second, the paper will identify the need to define the negotiation processes required to agree revisions to the RBT in the layered ATM system. Third, the final objective of the paper is to bring to the attention of researchers and engineers the communalities between multi-player games and Collaborative Decision Making processes (CDM) in a layered ATM system

Systematic Approach for the selection of monitoring technologies in CO2 geological storage projects. Application of multicriteria decision making

Geologic storage of carbon dioxide (CO2) has been proposed as a viable means for reducing anthropogenic CO2 emissions. Once injection begins, a program for measurement, monitoring, and verification (MMV) of CO2 distribution is required in order to: a) research key features, effects and processes needed for risk assessment; b) manage the injection process; c) delineate and identify leakage risk and surface escape; d) provide early warnings of failure near the reservoir; and f) verify storage for accounting and crediting. The selection of the methodology of monitoring (characterization of site and control and verification in the post-injection phase) is influenced by economic and technological variables. Multiple Criteria Decision Making (MCDM) refers to a methodology developed for making decisions in the presence of multiple criteria. MCDM as a discipline has only a relatively short history of 40 years, and it has been closely related to advancements on computer technology. Evaluation methods and multicriteria decisions include the selection of a set of feasible alternatives, the simultaneous optimization of several objective functions, and a decision-making process and evaluation procedures that must be rational and consistent. The application of a mathematical model of decision-making will help to find the best solution, establishing the mechanisms to facilitate the management of information generated by number of disciplines of knowledge. Those problems in which decision alternatives are finite are called Discrete Multicriteria Decision problems. Such problems are most common in reality and this case scenario will be applied in solving the problem of site selection for storing CO2. Discrete MCDM is used to assess and decide on issues that by nature or design support a finite number of alternative solutions. Recently, Multicriteria Decision Analysis has been applied to hierarchy policy incentives for CCS, to assess the role of CCS, and to select potential areas which could be suitable to store. For those reasons, MCDM have been considered in the monitoring phase of CO2 storage, in order to select suitable technologies which could be techno-economical viable. In this paper, we identify techniques of gas measurements in subsurface which are currently applying in the phase of characterization (pre-injection); MCDM will help decision-makers to hierarchy the most suitable technique which fit the purpose to monitor the specific physic-chemical parameter.

A decision model for it supplier selection

En los últimos años la externalización de TI ha ganado mucha importancia en el mercado y, por ejemplo, el mercado externalización de servicios de TI sigue creciendo cada año. Ahora más que nunca, las organizaciones son cada vez más los compradores de las capacidades necesarias mediante la obtención de productos y servicios de los proveedores, desarrollando cada vez menos estas capacidades dentro de la empresa. La selección de proveedores de TI es un problema de decisión complejo. Los gerentes que enfrentan una decisión sobre la selección de proveedores de TI tienen dificultades en la elaboración de lo que hay que pensar, además en sus discursos. También de acuerdo con un estudio del SEI (Software Engineering Institute) [40], del 20 al 25 por ciento de los grandes proyectos de adquisición de TI fracasan en dos años y el 50 por ciento fracasan dentro de cinco años. La mala gestión, la mala definición de requisitos, la falta de evaluaciones exhaustivas, que pueden ser utilizadas para llegar a los mejores candidatos para la contratación externa, la selección de proveedores y los procesos de contratación inadecuados, la insuficiencia de procedimientos de selección tecnológicos, y los cambios de requisitos no controlados son factores que contribuyen al fracaso del proyecto. La mayoría de los fracasos podrían evitarse si el cliente aprendiese a comprender los problemas de decisión, hacer un mejor análisis de decisiones, y el buen juicio. El objetivo principal de este trabajo es el desarrollo de un modelo de decisión para la selección de proveedores de TI que tratará de reducir la cantidad de fracasos observados en las relaciones entre el cliente y el proveedor. La mayor parte de estos fracasos son causados por una mala selección, por parte del cliente, del proveedor. Además de estos problemas mostrados anteriormente, la motivación para crear este trabajo es la inexistencia de cualquier modelo de decisión basado en un multi modelo (mezcla de modelos adquisición y métodos de decisión) para el problema de la selección de proveedores de TI. En el caso de estudio, nueve empresas españolas fueron analizadas de acuerdo con el modelo de decisión para la selección de proveedores de TI desarrollado en este trabajo. Dos softwares se utilizaron en este estudio de caso: Expert Choice, y D-Sight. ABSTRACT In the past few years IT outsourcing has gained a lot of importance in the market and, for example, the IT services outsourcing market is still growing every year. Now more than ever, organizations are increasingly becoming acquirers of needed capabilities by obtaining products and services from suppliers and developing less and less of these capabilities in-house. IT supplier selection is a complex and opaque decision problem. Managers facing a decision about IT supplier selection have difficulty in framing what needs to be thought about further in their discourses. Also according to a study from SEI (Software Engineering Institute) [40], 20 to 25 percent of large information technology (IT) acquisition projects fail within two years and 50 percent fail within five years. Mismanagement, poor requirements definition, lack of comprehensive evaluations, which can be used to come up with the best candidates for outsourcing, inadequate supplier selection and contracting processes, insufficient technology selection procedures, and uncontrolled requirements changes are factors that contribute to project failure. The majority of project failures could be avoided if the acquirer learns how to understand the decision problems, make better decision analysis, and good judgment. The main objective of this work is the development of a decision model for IT supplier selection that will try to decrease the amount of failures seen in the relationships between the client-supplier. Most of these failures are caused by a not well selection of the supplier. Besides these problems showed above, the motivation to create this work is the inexistence of any decision model based on multi model (mixture of acquisition models and decision methods) for the problem of IT supplier selection. In the case study, nine different Spanish companies were analyzed based on the IT supplier selection decision model developed in this work. Two software products were used in this case study, Expert Choice and D-Sight.

Participatory modelling to support decision making in water management under uncertainty: Two comparative case studies in the Guadiana river basin, Spain.

A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

TITIM GIS-tool: A GIS-based decision support system for measuring the territorial impact of transport infrastructures

To achieve sustainability in the area of transport we need to view the decision-making process as a whole and consider all the most important socio-economic and environmental aspects involved. Improvements in transport infrastructures have a positive impact on regional development and significant repercussions on the economy, as well as affecting a large number of ecological processes. This article presents a DSS to assess the territorial effects of new linear transport infrastructures based on the use of GIS. The TITIM ? Transport Infrastructure Territorial Impact Measurement ? GIS tool allows these effects to be calculated by evaluating the improvement in accessibility, loss of landscape connectivity, and the impact on other local territorial variables such as landscape quality, biodiversity and land-use quality. The TITIM GIS tool assesses these variables automatically, simply by entering the required inputs, and thus avoiding the manual reiteration and execution of these multiple processes. TITIM allows researchers to use their own GIS databases as inputs, in contrast with other tools that use official or predefined maps. The TITIM GIS-tool is tested by application to six HSR projects in the Spanish Strategic Transport and Infrastructure Plan 2005?2020 (PEIT). The tool creates all 65 possible combinations of these projects, which will be the real test scenarios. For each one, the tool calculates the accessibility improvement, the landscape connectivity loss, and the impact on the landscape, biodiversity and land-use quality. The results reveal which of the HSR projects causes the greatest benefit to the transport system, any potential synergies that exist, and help define a priority for implementing the infrastructures in the plan

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.