965 resultados para Machine-tool industry.
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Thesis presented at the Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, to obtain a Master degree in Conservation and Restoration,Specialization in Textiles
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ISO 14001 is an International Standard of worldwide acceptance based on the concept that better environmental performance can be achieved when environmental aspects are systematically identified and managed giving a major contribution to Sustainability, through pollution prevention, improved environmental performance and complying with applicable laws. This paper aims to discuss the Sustainability approach through the use of Environmental Management Standards (EMS), the results achieved by organizations that implement and certify those EMS and a special focus on the current process of ISO 14001:2015 revision and the logic behind it.
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Mestrado em Engenharia Civil – Ramo Estruturas
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Dissertation presented to obtain a Master degree in Biotechnology at the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Performance appraisal increasingly assumes a more important role in any organizational environment. In the trucking industry, drivers are the company's image and for this reason it is important to develop and increase their performance and commitment to the company's goals. This paper aims to create a performance appraisal model for trucking drivers, based on a multi-criteria decision aid methodology. The PROMETHEE and MMASSI methodologies were adapted using the criteria used for performance appraisal by the trucking company studied. The appraisal involved all the truck drivers, their supervisors and the company's Managing Director. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used. The results are to be used as a decision-making tool to allocate drivers to the domestic haul service.
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The problem addressed here originates in the industry of flat glass cutting and wood panel sawing, where smaller items are cut from larger items accordingly to predefined cutting patterns. In this type of industry the smaller pieces that are cut from the patterns are piled around the machine in stacks according to the size of the pieces, which are moved to the warehouse only when all items of the same size have been cut. If the cutting machine can process only one pattern at a time, and the workspace is limited, it is desirable to set the sequence in which the cutting patterns are processed in a way to minimize the maximum number of open stacks around the machine. This problem is known in literature as the minimization of open stacks (MOSP). To find the best sequence of the cutting patterns, we propose an integer programming model, based on interval graphs, that searches for an appropriate edge completion of the given graph of the problem, while defining a suitable coloring of its vertices.
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A Gestão da Segurança do Processo consiste na implementação de procedimentos para controlar os perigos resultantes de fabrico, manuseamento e utilização de substâncias perigosas e da utilização de sistemas sob pressão em instalações industriais, pelo que se torna numa ferramenta de Gestão muito importante na indústria. Pela pesquisa realizada, a Gestão da Segurança do Processo é um tema pouco desenvolvido no nosso país, embora esteja diretamente relacionada com a Diretivas Seveso. Como colaborador da Central de Ciclo Combinado da Tapada do Outeiro, propus-me a avaliar a Gestão da Segurança do Processo na Central. A Direção da Central apoiou o tema, reservando a confidencialidade do trabalho final devido a assuntos sensíveis do negócio. Como resultado final do Projeto temos a avaliação da Gestão da Segurança do Processo na Central de Ciclo Combinado da Tapada do Outeiro, permitindo à gestão da Central identificar oportunidades para melhorar a efetividade do cumprimento deste objetivo.
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This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.
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Environmental Training in Engineering Education (ENTREE 2001) - integrated green policies: progress for progress, p. 329-339 (Florence, 14-17 November 2001; proceedings published as book)
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This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.
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This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.
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Journal of Environmental Management, nº 82 p. 410–432
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Starting from theoretical perspectives on globalisation, the following article analyses how current working conditions are affected by globalisation processes. For this purpose, recent developments in the German clothing sector are traced back to the power of economic globalisation processes. Characterising the German clothing sector as pioneer in economic globalisation, we use empirical findings to illustrate how current processes of globalisation influence the work place: At organisational level, corporate strategies aim at rationalisation, standardisation and flexibilisation of work in order to response to the economic pressure of global markets. At individual level these strategies, in turn, speed up working processes and intensify working processes for the employees. Although these developments form strong trends, we conclude that the local embeddedness of companies is still of high importance with regard to organisational and individual consequences of globalisation.
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Gradually smart grids and smart meters are closer to the home consumers. Several countries has developed studies focused in the impacts arising from the introduction of these technologies and one of the main advantages are related to energy efficiency, observed through the awareness of the population on behalf of a more efficient consumption. These benefits are felt directly by consumers through the savings on electricity bills and also by the concessionaires through the minimization of losses in transmission and distribution, system stability, smaller loading during peak hours, among others. In this article two projects that demonstrate the potential energy savings through smart meters and smart grids are presented. The first performed in Korea, focusing on the installation of smart meters and the impact of use of user interfaces. The second performed in Portugal, focusing on the control of loads in a residence with distributed generation.
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This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.