8 resultados para Production Management
em Instituto Politécnico do Porto, Portugal
Resumo:
Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspects of swarm intelligence based optimization techniques such Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) algorithms for scheduling optimization.
Resumo:
Atualmente o sistema produtivo do tipo job shop é muito comum nas PMEs (Pequenas e Médias Empresas). Estas empresas trabalham por encomenda. Produzem grande variedade de modelos, e em pequenas quantidades. Os prazos de entrega são um fator de elevada importância, pois os clientes exigem um produto de qualidade no tempo certo. O presente trabalho, pretende criar uma ferramenta de programação da produção para a secção da costura, usando dados reais da empresa, que tem uma implantação do tipo job shop com máquinas multi-operação (Multi-Purpose -Machines Job Shop). No final, são reunidas as principais conclusões e perspetivados futuros desenvolvimentos. Os resultados obtidos comprovam que o algoritmo desenvolvido, com base no algoritmo de Giffler & Thompson, consegue obter com grande precisão e de forma rápida o escalonamento / balanceamento da secção da costura. Com a ferramenta criada, a empresa otimiza a programação da secção da costura e fornece informação importante á gestão da produção, possibilitando uma melhoria do planeamento da empresa.
Resumo:
Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.
Resumo:
Pesticides are among the most widely used chemicals in the world. Because of the widespread use of agricultural chemicals in food production, people are exposed to low levels of pesticide residues through their diets. Scientists do not yet have a total understanding of the health effects of these pesticide residues. This work aims to determine differences in terms of pesticide residue content in Portuguese strawberries grown using different agriculture practices. The Quick, Easy, Cheap, Effective, Rugged, and Safe sample preparation method was conducted and shown to have good performance for multiclass pesticides extraction in strawberries. The screening of 25 pesticides residue was performed by gas chromatography–tandem mass spectrometry. In quantitative validation, acceptable performances were achieved with recoveries of 70–120 and <12 % residual standard deviation for 25 pesticides. Good linearity was obtained for all the target compounds, with highly satisfactory repeatability. The limits of detection were in the range of 0.1–28 μg/kg. The method was applied to analyze strawberry samples from organic and integrated pest management (IPM) practices harvested in 2009–2010. The results showed the presence of fludioxonil, bifenthrin, mepanipyrim, tolylfluanid, cyprodinil, tetraconazole, and malathion when using IPM below the maximum residue levels.
Resumo:
In this study, the added value resultant from the incorporation of pultrusion production waste into polymer based concretes was assessed. For this purpose, different types of thermoset composite scrap material, proceeding from GFRP pultrusion manufacturing process, were mechanical shredded and milled into a fibrous-powdered material. Resultant GFRP recyclates, with two different size gradings, were added to polyester based mortars as fine aggregate and filler replacements, at various load contents between 4% up to 12% in weight of total mass. Flexural and compressive loading capacities were evaluated and found better than those of unmodified polymer mortars. Obtained results highlight the high potential of recycled GFRP pultrusion waste materials as efficient and sustainable admixtures for concrete and mortar-polymer composites, constituting an emergent waste management solution.
Resumo:
To date, glass fibre reinforced polymer (GFRP) waste recycling is very limited and restricted by thermoset nature of binder matrix and lack of economically viable enduse applications for the recyclates. In this study, efforts were made in order to recycle grinded GFRP waste proceeding from pultrusion production scrap, into new and sustainable composite materials. For this purpose, GFRP waste recyclates, a mix of powdered and fibrous materials, were incorporated into polyester based mortars as fine aggregate and filler replacements, at different load contents (between 4% up to 12% of total mass) and particle size distributions. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified polymer mortars. Test results revealed that GFRP waste filled polymer mortars present improved flexural and compressive behaviour over unmodified polyester based mortars, thus indicating the feasibility of GFRP waste reuse in concrete-polymer composites.
Resumo:
This paper presents a framework for a robotic production line simulation learning environment using Autonomous Ground Vehicles (AGV). An eLearning platform is used as interface with the simulator. The objective is to introduce students to the production robotics area using a familiar tool, an eLearning platform, and a framework that simulates a production line using AGVs. This framework allows students to learn about robotics but also about several areas of industrial management engineering without requiring an extensive prior knowledge on the robotics area. The robotic production line simulation learning environment simulates a production environment using AGVs to transport materials to and from the production line. The simulator allows students to validate the AGV dynamics and provides information about the whole materials supplying system which includes: supply times, route optimization and inventory management. The students are required to address several topics such as: sensors, actuators, controllers and an high level management and optimization software. This simulator was developed with a known open source tool from robotics community: Player/Stage. This tool was extended with several add-ons so that students can be able to interact with a complex simulation environment. These add-ons include an abstraction communication layer that performs events provided by the database server which is programmed by the students. An eLearning platform is used as interface between the students and the simulator. The students can visualize the effects of their instructions/programming in the simulator that they can access via the eLearning platform. The proposed framework aims to allow students from different backgrounds to fully experience robotics in practice by suppressing the huge gap between theory and practice that exists in robotics. Using an eLearning platform eliminates installation problems that can occur from different computers software distribution and makes the simulator accessible by all students at school and at home.
Resumo:
This article presents a framework to an Industrial Engineering and Management Science course from School of Management and Industrial Studies using Autonomous Ground Vehicles (AGV) to supply materials to a production line as an experimental setup for the students to acquire knowledge in the production robotics area. The students must be capable to understand and put into good use several concepts that will be of utmost importance in their professional life such as critical decisions regarding the study, development and implementation of a production line. The main focus is a production line using AGVs, where the students are required to address several topics such as: sensors actuators, controllers and an high level management and optimization software. The presented framework brings to the robotics teaching community methodologies that allow students from different backgrounds, that normally don’t experiment with the robotics concepts in practice due to the big gap between theory and practice, to go straight to ”making” robotics. Our aim was to suppress the minimum start point level thus allowing any student to fully experience robotics with little background knowledge.