Conference Agenda

Efficient diagnosis of problems in automotive electronic injection systems in Honduras is limited due to general lack of specialized tools in the country. A multifunctional, efficient and accurate tester for CKP, CMP sensors and ETC and IAC actuators was designed to improve automotive diagnosis and repair. Through an explanatory approach, using six vehicles carefully selected to represent a variety of models and operating conditions. Ad a result, thr automotive sensor and actuator test bench allowed to realized reliable diagnostics by comparing waveforms obtained and manufactures provided data. This process demonstrated the test bench's ability to identify component failures and provide reliable diagnosis of the presented anomalies.

The continuous increase in energy demand highlights the need for its forecasting to ensure energy supply. Various methods have been used to predict this demand; however, this study proposes an approach based on a multiple linear regression model to perform energy demand forecasting. Demand energy is considered the dependent variable, while the independent variables include socioeconomic factors such as population, gross domestic product (GDP), energy production and temperature. To validate the accuracy of the model, statistical indicators such as the coefficient of determination (R²) and percentage error metrics, including the mean absolute deviation (MAD) and the mean absolute percentage error (MAPE), are applied. The proposed method is applied to the energy demand of the Peruvian national case, using historical data collected from 1995 to 2021. The results show an error of 1.7% between the historical demand used for model training (70% of the data, corresponding to 1995–2013) and the forecasted demand for the validation period (30% of the historical data, corresponding to 2014–2021), indicating a good level of accuracy in the estimates. Based on these results, long-term forecasting is performed, projecting electric demand from 2022 to 2038. The proposed methodology is useful for energy demand forecasting studies carried out by operators of national electrical power systems, such as COES in the case of Peru.

It seeks to numerically model the calculation of replenishment of supplies in an electrical energy distribution company in northern Peru to reduce the monetary value of its inventories, with its quantitative approach and quasi-experimental design. For this purpose, the restrictions of a suitable model for replenishment were defined by interviewing logistics managers from the last 10 years, then the operational applicability of each of the current calculation models was evaluated, from which a replenishment model that is multi-product and multi-period, appropriate to the conditions of the company, was proposed. Then, the model designed in replenishment was applied experimentally for 9 months to a convenience sample of 10 SKUs due to company restrictions and a comparative analysis of results was carried out. The research concludes that the proposed model can be applied in a single periodic review to multiple SKUs with different types of demand, delivery times, unit price and proximity of source, managing to reduce the valued stock on average by 69.93%, verifying its effectiveness and its applicability in similar organizations.

The project shows the design of an electricity generation system using clean energy from wave power, which arises from the country’s need to diversify the renewable energy portfolio of the master electricity that plan. The design includes a compressed air generation system through sixty mechanical arms with modified pistons and buoys, harnessing wave energy. And, on the other hand, it incorporates a hydraulic system powered by the compressed air from the first system, which, through five pneumatic pumps and four hydropneumatics tanks, supplies water at 15 bar to a 25 kW turbogenerator. This design was developed through calculations, simulations and 3D modeling, taking into account wave crest and period data from “La Chocolatera” in Salinas-Santa Elena, Ecuador. It is concluded that the design can generate electricity 24 hours a day throughout the year, without depending on wave conditions or other climatic factors. Therefore, despite the total cost of $537,384.00 which is high for a 25 kW production compared to other clean energy sources, it fulfills the expectations for the diversification of the country’s clean energy sources

This research aims to evaluate the influence of flow rate on electricity generation using a hydraulic generator by analyzing its behavior at different water level heights over a specific time interval. The study seeks to establish the relationship between flow rate reduction and voltage variation. A quantitative approach was used, employing an experimental design where flow rate measurements were taken at four different time intervals and various water heights. Data collection was conducted through observation techniques, recorded in tables designed by the research team, and using instruments such as a camera and a stopwatch. The results show that changes in water height directly affect the flow rate through the hydraulic system, impacting energy generation. In conclusion, hydraulic generators can be an efficient alternative for electricity generation in areas near rivers or canals with a constant water flow, especially in communities without access to conventional power grids.

The energy sector faces major challenges due to the increasing demand for efficiency and service quality, which represents a significant barrier for small and medium-sized enterprises (SMEs) seeking to maintain their competitiveness in the market. This study explores the application of Lean Service and 8D methodologies in an SME of the electrical sector to improve its operational processes, where it currently faces high inefficiency rates, delays in service, and low customer satisfaction.

The Lean Service methodology aims to reduce waste and optimize workflow through tools such as Kanban, which visually organizes tasks, and Heijunka, which stabilizes production; both contribute to increased efficiency. On the other hand, the 8D approach provides a structured framework to solve operational problems by identifying and eliminating root causes, preventing recurrence, and fostering continuous improvement.

The results show significant improvements in key indicators, such as reduced service time, backlog reduction, and a considerable increase in customer satisfaction. These findings suggest that the combined use of Lean Service and 8D enables a sustainable and effective operational transformation in similar companies. The methodology used, based on theoretical and practical evidence, offers a replicable model for other SMEs in the sector, which is essential for fostering their sustainability and growth in a highly competitive environment.