Edson Farias de Oliveira

The use of additive manufacturing for printing mechanical parts makes it possible to create mechanisms with a higher degree of complexity, due to the resources of filament deposits in three dimensions that this technology makes available, something that if compared to conventional machining systems is limited. The objective of this work is to develop a methodology that uses additive manufacturing for the development of functional testing devices, commonly used in the electrical testing of Notebook motherboards, inside the mechanical core of the development laboratory of a company from the Industrial Pole of Manaus (PIM). In which it was necessary to perform analysis and survey of requirements of the testing steps as well as the machining process, used for making functional devices. Resulting in new functional testing devices, which were implemented in the production line, enabling this methodology to be validated and replicated for other types of electronic board models.

The main objective of thermoelectric power plants is to meet the power demand with the lowest fuel cost and emission levels of pollutant and greenhouse gas emissions, considering the operational restrictions of the power plant. Optimization techniques have been widely used to solve engineering problems as in this case with the objective of minimizing the cost and the pollution damages. Heuristic and metaheuristic algorithms have been extensively studied and used to successfully solve this multi-objective problem. This chapter, several optimization techniques (simulated annealing, ant lion, dragonfly, NSGA II, and differential evolution) are analyzed and their application to economic-emission load dispatch (EELD) is also discussed. In addition, a comparison of all approaches and its results are offered through a case study.

Industrial production has evolved significantly over the last decade. For this reason, it is necessary to obtain mathematical and computational tools that enable power systems engineers to make decisions that reduce harmonic distortions in accordance with international standards. This paper presents a total harmonic distortion (THD) assessment based on full knowledge discovery in databases (KDD) using power quality (PQ) standards and computational intelligence tools. The materials and methods of THD assessment consist of load and layout analysis; choice and installation of PQ analyzers; and the application of the full KDD process, including collection, selection, cleaning, integration, transformation and reduction, mining, interpretation and evaluation of the data. This research methodology was used in an electrical and electronic industry; the results obtained have characteristics that can be used as a reference for other types of analyses. The results indicate that these methods can be applied to several industrial applications such as (1) the description of the complete KDD process for THD assessment of the point of common coupling (PCC); (2) simultaneous collection using five PQ analyzers at several points in the electrical network; and (3) the use of a decision tree classifier.