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An electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way. Failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this reason, there is a need for failure prediction to reestablish power in the shortest possible time. Considering an evaluation of the number of failures over time, this paper proposes performing failure prediction during the first year of the pandemic in Brazil (2020) to verify the feasibility of using time series forecasting models for fault prediction. The long short-term memory (LSTM) model will be evaluated to obtain a forecast result that an electric power utility can use to organize maintenance teams. The wavelet transform has shown itself to be promising in improving the predictive ability of LSTM, making the wavelet LSTM model suitable for the study at hand. The assessments show that the proposed approach has better results regarding the error in prediction and has robustness when statistical analysis is performed.

The electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way, failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this reason, there is a need for failure prediction to reestablish power in the shortest possible time. Considering an evaluation of the number of failures over time, this paper proposes to perform a failure prediction during the first year of the pandemic in Brazil (2020) to verify the feasibility of using time series forecasting models for fault prediction. The Long Short-Term Memory (LSTM) model will be evaluated to obtain a forecast result that can be used by the electric power utility to organize the maintenance teams. The Wavelet transform shows to be promising in improving the predictive ability of the LSTM, making the Wavelet LSTM model suitable for the study at hand. The results show that the proposed approach has better results regarding the evaluation of the error in prediction and has robustness when a statistical analysis is performed.

This research thematic is the Economic Viability Study, in order to implement a cogeneration system, in a logging company, located in the Santa Catarina highland plateau region. Thus, reducing its production cost, since much of it is due electricity purchase. Data collection of both production, consumption and expenses with electricity purchase and billing were carried out together with the company. Descriptive method was used, with case study. For the economic analysis, both net present value (NPV), internal rate of return (IRR) and payback period were used. With this information and crossing the data, the economic viability for this project became evident, as it can be visualized throughout of this article.

This article aims to identify the challenges that women engineers face in their field of work. The main theoretical references are: Silva (1992), Hirata; Kergoat (2007), Carvalho; Casagrande (2011); Carvalho (2008); Casagrande et al. (2004); Lombardi (2006a, 2006b); Cabral; Bazzo (2005); Lime; Souza (2011); among others. It is a qualitative-quantitative research and data were collected through questionnaires. The 69 women who graduated from 2011 to 2018 were invited to participate in the survey. Of these 33 answered the instrument. The data show that women engineers experience gender discrimination, sexism, racism and sexual and moral harassment in their work field. Finally, these women, in 2019, reported cases of gender inequality experienced in the labor market. In this perspective, the study points out the following strategies to fight gender discrimination in the production engineering course: - include publications by renowned engineers in the teaching plans; - discuss with students and professors of the course about gender equity in the labor market.