Autonomic computing for scheduling in manufacturing systems

We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.

Cooperative intelligent system for manufacturing scheduling

Hybridization of intelligent systems is a promising research field of computational intelligence focusing on combinations of multiple approaches to develop the next generation of intelligent systems. In this paper we will model a Manufacturing System by means of Multi-Agent Systems and Meta-Heuristics technologies, where each agent may represent a processing entity (machine). The objective of the system is to deal with the complex problem of Dynamic Scheduling in Manufacturing Systems.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

Planeamento espacial marinho das áreas marinhas protegidas: o caso de estudo da ára protegida de gestão de recursos: Caloura - ilhéu de Vila Franca do Campo

Tese de Doutoramento, Ciências do Mar (Ecologia Marinha), 26 de Novembro de 2013, Universidade dos Açores.

Conservation of limpet populations: a heavily exploited resource in Azores, NE-Atlantic

10th International Temperate Reefs Symposium, The University of Western Australia, 12-17 de janeiro.

Towards systematic conservation planning in the Azores

Several field methodologies, analytical measures and theoretical patterns have been explored for conservation planning for arthropods in native forests of the Azores archipelago. Here, the outcomes are assembled to make recommendations on practical strategies to assess arthropod diversity and to select and manage protected native forests in the Azores. Suggestions are made on how to apply similar plans for conservation of other plant and animal groups in these forests. Potential threats to the Azorean native forest are described and measures to minimize them are proposed. Future studies are also suggested that would improve the present knowledge of arthropod diversity and distribution in Azorean native forests and could assist in the identification of suitable conservation strategies.

Sistema múltiplo de apoio à decisão para a programação de sistemas do tipo Job-Shop

Mestrado em Engenharia Electrotécnica e de Computadores

Mapping multi-species habitat use for marine conservation planning

Tese de Doutoramento, Ciências do Mar (Biologia Marinha)

Comparison of different breast planning techniques and algorithms for radiation therapy treatment

This work aims at investigating the impact of treating breast cancer using different radiation therapy (RT) techniques – forwardly-planned intensity-modulated, f-IMRT, inversely-planned IMRT and dynamic conformal arc (DCART) RT – and their effects on the whole-breast irradiation and in the undesirable irradiation of the surrounding healthy tissues. Two algorithms of iPlan BrainLAB treatment planning system were compared: Pencil Beam Convolution (PBC) and commercial Monte Carlo (iMC). Seven left-sided breast patients submitted to breast-conserving surgery were enrolled in the study. For each patient, four RT techniques – f-IMRT, IMRT using 2-fields and 5-fields (IMRT2 and IMRT5, respectively) and DCART – were applied. The dose distributions in the planned target volume (PTV) and the dose to the organs at risk (OAR) were compared analyzing dose–volume histograms; further statistical analysis was performed using IBM SPSS v20 software. For PBC, all techniques provided adequate coverage of the PTV. However, statistically significant dose differences were observed between the techniques, in the PTV, OAR and also in the pattern of dose distribution spreading into normal tissues. IMRT5 and DCART spread low doses into greater volumes of normal tissue, right breast, right lung and heart than tangential techniques. However, IMRT5 plans improved distributions for the PTV, exhibiting better conformity and homogeneity in target and reduced high dose percentages in ipsilateral OAR. DCART did not present advantages over any of the techniques investigated. Differences were also found comparing the calculation algorithms: PBC estimated higher doses for the PTV, ipsilateral lung and heart than the iMC algorithm predicted.

Um caso multimédia na formação inicial: contributos para o conhecimento sobre o ensino exploratório da Matemática

Este artigo tem como foco o uso de casos multimédia na formação inicial de professores e procura analisar o seu contributo para o desenvolvimento do conhecimento didático de futuras professoras acerca do ensino exploratório da Matemática, bem como apreciar as suas perspetivas sobre as mais-valias do caso multimédia utilizado como recurso formativo. Analisam-se questionários e relatórios de treze alunas do Mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo da Universidade de Évora, que trabalharam sobre um caso multimédia que retrata a prática de ensino de uma professora de 1º ciclo. O caso inclui recursos diversificados, sendo os vídeos de sala de aula complementados com o plano da aula, as resoluções da tarefa pelos alunos, as reflexões da professora sobre a sua prática, um quadro de referência sobre o ensino exploratório da Matemática e artigos teóricos sobre ensino de natureza exploratória da Matemática. As alunas em formação apreciaram conhecer e explorar o caso multimédia, ressaltando a possibilidade de através dele conhecerem uma nova prática real de ensino da Matemática; sublinharam a importância de ouvirem as reflexões da professora para dotar de sentido a respetiva prática, revelando as intenções das suas ações; aprenderam também conhecimentos relevantes para pôr em prática o ensino exploratório, nomeadamente relativos ao conhecimento do processo instrucional, tanto no diz respeito à planificação, como à condução da aula.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

Jogos Sérios para Lean Manufacturing: “Jogo: Método 5S”

A crise económica global que se faz sentir leva a que surja uma necessidade de aumentar a competitividade das empresas, através da melhoria de performance dos seus colaboradores. Nesse sentido, Lean Manufacturing é uma área que merece a atenção das empresas e dos seus colaboradores, uma vez que os seus principais objectivos são o aumento da produtividade, a redução dos desperdícios e a optimização dos recursos disponíveis. Uma ferramenta do Lean que merece especial destaque é o Método 5S, que permite aumentar a produtividade através do aumento da organização do posto de trabalho. Uma vez que usar postos de trabalho a mais, de modo a que os colaboradores pratiquem e aprendam a aplicar as regras do 5S, fica dispendioso em tempo de trabalho e custos acrescidos pela paragem da linha produção, surge a necessidade de criação de um Jogo Sério que ajude na aprendizagem destes temas. Um breve estudo do mercado revelou que esta necessidade não está a ser devidamente respondida. Existem algumas entidades que se dedicam ao ensino e partilha deste tipo de conhecimentos, sendo poucas as que têm ferramentas digitais disponíveis. Esta dissertação propõe um Jogo Sério que pretende dar resposta a esta necessidade, permitindo pôr em prática o Método 5S, servindo ainda como ferramenta motivadora, para que o colaborador aprofunde o seu conhecimento na matéria. Esta abordagem prática encoraja o jogador a aprender por tentativa e erro. Informações mostradas ao longo do jogo permitem uma aprendizagem sem haver uma sobrecarga cognitiva. A avaliação do jogo, realizada por um grupo de alunos que frequentam o Mestrado em Engenharia Mecânica, demonstrou que a nossa abordagem é eficiente e resulta na aprendizagem dos conceitos 5S.

Planning and implementing a new assessment strategy using an e-learning platform

One of the most difficult issues of e-Learning is the students’ assessment. Being this an outstanding task regarding theoretical topics, it becomes even more challenging when the topics under evaluation are practical. ISCAP’s Information Systems Department is composed of about twenty teachers who have been for several years using an e-learning environment (at the moment Moodle 2.3) combined with traditional assessment. They are now planning and implementing a new e-learning assessment strategy. This effort was undertaken in order to evaluate a practical topic (the use of spreadsheets to solve management problems) common to shared courses of several undergraduate degree programs. The same team group is already experienced in the assessment of theoretical information systems topics using the b-learning platform. Therefore, this project works as an extension to previous experiences being the team aware of the additional difficulties due to the practical nature of the topics. This paper describes this project and presents two cycles of the action research methodology, used to conduct the research. The first cycle goal was to produce a database of questions. When it was implemented in order to be used with a pilot group of students, several problems were identified. Subsequently, the second cycle consisted in solving the identified problems preparing the database and all the players to a broader scope implementation. For each cycle, all the phases, its drawbacks and achievements are described. This paper suits all those who are or are planning to be in the process of shifting their assessment strategy from a traditional to one supported by an e-learning platform.

Melhoria do processo produtivo na indústria do mobiliário

Com o aumento da concorrência, a crise económica que atravessamos e com a conquista de novos mercados no horizonte, surge a necessidade de responder a essas situações com uma melhor prestação do sistema produtivo no sentido de reduzir tempos de produção e de baixar os custos dos mesmos, podendo assim dar uma resposta mais rápida e competitiva às expectativas dos clientes. Esta dissertação tem como objectivo analisar todo o sistema produtivo da empresa, desenvolvendo um estudo adequado ao sistema actual de fabrico de mobiliário, propondo melhorias que proporcionem uma melhor organização e uma redução dos custos de fabrico. Fez-se também um levantamento do sistema de planeamento existente, detectando pontos de melhoria que, para além de um maior controlo e organização, permitem, em alguns aspectos, a melhoria do sistema produtivo. Foi apresentada uma proposta de um processo de reengenharia aplicado ao sistema produtivo, tendo em vista implementar as medidas de melhoria, indo ao encontro das situações identificadas, tornando assim o sistema produtivo mais eficiente.

Comparison of inverse planning systems based on biological or physical factors: Pinnacle®, Corvus® and Monaco®

Radiotherapy (RT) is one of the most important approaches in the treatment of cancer and its performance can be improved in three different ways: through the optimization of the dose distribution, by the use of different irradiation techniques or through the study of radiobiological initiatives. The first is purely physical because is related to the physical dose distributiuon. The others are purely radiobiological because they increase the differential effect between the tumour and the health tissues. The Treatment Planning Systems (TPS) are used in RT to create dose distributions with the purpose to maximize the tumoral control and minimize the complications in the healthy tissues. The inverse planning uses dose optimization techniques that satisfy the criteria specified by the user, regarding the target and the organs at risk (OAR’s). The dose optimization is possible through the analysis of dose-volume histograms (DVH) and with the use of computed tomography, magnetic resonance and other digital image techniques.