Service-oriented architecture for device lifecycle support in industrial automation

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores Especialidade: Robótica e Manufactura Integrada

Lightweight robust behavior industrial agent methodology

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Musealização da Levada de Tomar: subsídios para a conservação do património industrial da moagem A Portuguesa

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em (designação da área científica do mestrado)

InnovationCity Ruhr: a prime example for social and technological innovation

The project “InnovationCity Ruhr” deals with the reconstruction of the city of Bottrop with regard to energy saving measures. The aim is to make the city more environmental friendly in order to create a model for other industrial cities. Until the conclusion of the project in the year 2020, it is planned to change the surface of Bottrop in several positive ways. This paper focuses on the description of the project to give the reader an example of what exactly is done within the scope of InnovationCity Ruhr. Besides that, the link to the subject of sociology shall be given in order to show that the project is a prime example for social innovation.

Argamassa industrial para a reabilitação de rebocos antigos

Argamassas 2014 - I Simpósio de Argamassas e Soluções Térmicas de Revestimento, 5-6 Junho, ITeCons, Universidade de Coimbra

Património industrial e turismo cultural: contributo para a criação de um itinerário turístico no Centro Histórico de Lisboa

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Práticas Culturais para os Municípios

Eco-wall modular solutions for buildings

This paper discusses the development of modular solutions for eco low-cost houses based on a pre-fabricated modular wall system environmentally sustainable, socioeconomically competitive and geared towards developing African nations with a housing deficit. The key point to the research of a modular wall solution is a structural layer complemented with local and materials made by non-specialized workforce. This wall also meets also hydrothermal acoustic and mechanical properties. Thus,the solution also offers good safety and interior comfort conditions to its users while maintaining the flexibility to expand the size of the house. Parameters as dimensions, materials and constructive processes of the existing housing stock were studied. Features such as the family size, typology, different uses, common materials, existing regulations, minimal living conditions, safety and comfort have also been considered to achieve the most efficient solution.

Dinâmicas de revitalização de frentes Ribeirinhas no período Pós-Industrial: o Arco Ribeirinho Sul do Estuário do Tejo

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Geografia e Planeamento Regional

Characterization and surface reconstruction of objects in tomographic images of composite materials

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

Aplicação da metodologia TRIZ e da manutenção autónoma em atividades de manutenção industrial

A manutenção tem ganho cada vez maior importância entre as atividades das empresas industriais. O aumento constante das exigências do mercado motiva os responsáveis pela manutenção a procurarem novas metodologias e técnicas, que permitam melhorar a gestão da manutenção em todas as suas vertentes. A metodologia TRIZ (Teoria de Resolução Inventiva de Problemas) promove a inovação sistemática e a procura de novas soluções para os problemas existentes. Sendo a inovação um conceito da atualidade e bem presente nas empresas que queiram marcar as suas posições no mercado, o uso da metodologia TRIZ é uma boa forma de as empresas se diferenciarem, encontrando novas soluções inovadoras e mais criativas. Este aumento da criatividade poderá proporcionar vantagens em relação à concorrência. Uma das principais caraterísticas da manutenção autónoma é a inclusão de diferentes áreas funcionais das empresas nas atividades da manutenção. Uma das grandes vantagens da manutenção autónoma é a partilha das responsabilidades e conhecimentos entre os técnicos de manutenção e os operadores dos equipamentos. Os operados dos equipamentos ganham com isso a capacidade de realizar algumas operações elementares de manutenção, ajudando na deteção precoce de anomalias, podendo com isto reduzir as paragens e falhas de equipamentos, prolongar a vida útil dos mesmos, tendo por vezes influência direta na qualidade do produto final produzido e na imagem da empresa. O estudo desenvolvido no âmbito da presente dissertação centrou-se nas possibilidades e oportunidades da utilização conjunta da metodologia TRIZ e da manutenção autónoma, em busca de novas formas de solucionar problemas da manutenção. Sendo a combinação destas técnicas ainda pouco explorada, o presente estudo visa abrir novos caminhos em relação à utilização da metodologia TRIZ nos problemas da manutenção. No âmbito desta dissertação foram explorados vários conceitos e ferramentas da metodologia TRIZ para resolver três casos práticos de manutenção industrial.

Options and Requirements for a potential market entry into Portugal with renewable energy technologies that are applicable for heating and cooling of buildings

NSBE-UNL

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Levantamento, identificação e classificação de dados para a gestão da manutenção numa empresa industrial

O presente trabalho refere-se à análise de conceitos gerais de manutenção e sua gestão, aplicados a uma indústria de produção de fibra têxtil sintética. Contempla uma primeira fase de organização e segmentação de um registo histórico de dados, para a identificação de equipamentos críticos e o seu impacto a nível capital na instalação industrial, e uma outra fase de caracterização de tipos de avaria comuns para a definição de um plano de acções. Neste contexto o trabalho visa o estudo de um equipamento essencial ao processo produtivo, pois a ocorrência de uma avaria/falha traduz-se na paragem da máquina e consequentemente perda na produção. Partindo dos dados organizados sobre avarias comuns identificam-se as causas raiz, com recurso a diagramas de causa e efeito. Acrescenta-se uma análise dos investimentos necessários para cumprir algumas das acções do plano. A estrutura de dados realizada permite à empresa dispor de uma nova ferramenta de apoio à gestão da manutenção, com vista a uma melhor preparação de trabalhos futuros e consequente aumento da produtividade.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.