Navegando por Autor "CASTRO, Anderson de Oliveira"

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Methodology Proposal for Multicriteria Optimization Using NSGA-II in Industrial Applications
(INSTITUTO DE TECNOLOGIA, 2023) CASTRO, Anderson de Oliveira; BEZERRA, Ubiratan Holanda; LEITE, Jandecy Cabral; AZEVEDO, Manoel Socorro Santos.; Professor Dr. Bernardo Borges Pompeu Neto
The paper proposes a methodology for multicriteria optimization using the NSGA-II genetic algorithm in industrial applications, specifically in the assembly process of electronic components in surface mount technology (SMT) machines. The study addresses problems such as feeder arrangement and head routing, aiming to reduce the total cycle time. The methodology integrates known approaches and applies multi-objective optimization to enhance machine performance, with results validated in a real industrial environment.
Otimização do Processo de Montagem de Componentes Eletrônicos de Superfície Utilizando Ferramenta Multicritério
(Universidade Federal do Pará, 2015) CASTRO, Anderson de Oliveira; BEZERRA, Ubiratan Holanda
The optimization problems of industrial process attracted many researches since the early 90's of the last century. The production volume increase, market competition increase and technological advances pushed the industries to seek for low cost and quick implementation solutions. One of the processes that became the core reason for increasing the sales volumes was the surface mount technology composed by printing, automated chip mounting and reflow oven which replaced the through hole technology. This research formulated a new point of view for optimization of modular chip mounters based on the already known feeder assignment problem and assembly head motion problem applying the global optimization using the non sorting dominance genetic algorithm the NSGAII in regard of the total cycle time reduction. The modeling of the fitness functions was presented and the multi criteria optimization tool was described using the machine functions and constraints. The same method could be applied to describe other type of machines to support future research.
Planning Passive Filters using NSGA II for Industry Applications
(INSTITUTO DE TECNOLOGIA, 2014) LEITE, Jandecy Cabral; SILVA, Waterloo Ferreira da; CASTRO, Anderson de Oliveira; NOGUEIRA, Rildo de Mendonça; AZEVEDO, Manoel Socorro Santos; Prof. Dra. ADRIANA RIBEIRO CARNEIRO FOLADOR
This paper presents a multi-objective optimization approach for planning passive harmonic filters in industrial systems using the NSGA-II genetic algorithm. The method maximizes reactive power compensation benefits, minimizes harmonic distortion in the PCC current and bus voltages, and complies with power quality standards. The algorithm determines the filters' location, configuration, and parameters, demonstrating effectiveness in a practical example.