Conference Agenda

The implementation of the Environmental Management Plan (EMP) at the Trujillo tannery has been instrumental in addressing environmental issues, especially exposure to chemicals and the flesh tanning process, which account for 80% of incidents involving hazardous substances. An 85% reduction in costs for exposure to chemicals (from S/. 8000 to S/. 1200) and 76% in meat tanning (from S/. 6200 to S/. 1500) is projected, thus improving the company's financial situation and creating a safer environment for workers. The financial analysis reveals a positive Net Present Value (NPV) of S/. 80,530.04 and an Internal Rate of Return (IRR) of 36.45%, which implies that each sol invested generates a return of S/. 1.53. In conclusion, WFP not only addresses operational and regulatory issues, but also promotes sustainable practices, protecting the environment and public health.

The flexographic printing industry plays a crucial role in packaging, yet many companies in emerging markets struggle with low Overall Equipment Effectiveness (OEE), primarily due to long setup times, unplanned downtimes, and process inconsistencies. Previous studies have addressed these issues through isolated applications of Total Productive Maintenance (TPM), Single-Minute Exchange of Dies (SMED), and 5S. However, limited research has integrated these tools into a unified model tailored to the sector’s challenges. This study developed a structured Lean-TPM model combining 5S, SMED, and TPM to enhance OEE in a Peruvian flexographic printing SME. The model was validated through pilot implementations and simulation using Arena software. Results showed an OEE increase from 59.91% to 70.84%, setup time reduction by 29.05%, and defect rate decrease by 28.26%. These improvements demonstrate the model’s effectiveness in optimizing performance while ensuring financial sustainability. This research provides a replicable framework for similar industries. Future studies should explore artificial intelligence applications to further enhance predictive maintenance and operational efficiency in dynamic manufacturing environments.

This paper addresses the environmental management of an infrastructure construction project for an alcoholic beverage factory, focusing on identifying and mitigating the environmental impacts generated during its execution. Three main root causes were diagnosed: particulate matter emissions, solid waste generation and excessive noise, whose effects generate environmental risks and additional operating costs.

As a solution, a Prevention, Remediation, and Mitigation Plan was designed to implement specific measures, such as emissions control, proper waste management, and regulation of noisy activities, together with an Environmental Contingency Plan to respond to emergencies. The P.A.M.A. Matrix tool made it possible to structure these actions and evaluate their impact on the environment.

The financial analysis of the project showed its viability, with a TMAR of 1.88%, an NPV of S/. 14,761, an IRR of 43% and a B/C of 2.19, which indicates that for each sol invested, S/. 2.19 of profit is generated. These results demonstrate the effectiveness of the proposal, both environmentally and economically, ensuring the sustainability of the project, regulatory compliance and protection of the natural environment.

The objective of the present study was to characterize the implementations of Machine Learning algorithms in predictive maintenance within the framework of Industry 4.0, with emphasis on its applicability and adaptation to the Latin American context, calculating on empirical evidence documented between 2018 and 2024, it was carried out through a narrative-analytical approach, complemented with a quantitative analysis of performance metrics, this combination allowed identifying best practices and critical success factors, as well as making objective comparisons between approaches and solutions, offering a comprehensive vision of the trends in predictive maintenance, where a gradual and adaptive approach is required, using traditional algorithms to balance complexity and viability in contexts with limited resources, observing a trend towards hybrid systems that facilitate the transition to Industry 4.0, especially for SMEs through continuous training and the development of human capital are key to ensuring the success and sustainability of these technologies.

In this research, the Total Productive Maintenance methodology was implemented in a tinplate packaging factory, with the purpose of improving product quality and increasing customer satisfaction. The implementation process included training of operators, improvement of equipment maintenance and optimization of machinery availability. The study was conducted due to the presence of recurring defects in production, mainly caused by worn and outdated machinery. Through quantitative and qualitative analysis, quality management tools such as Pareto and Ishikawa diagrams were used to identify the root causes of the problems, highlighting factors such as lack of preventive maintenance and inefficient personnel training. Key variables such as overall equipment efficiency, failure rate and productivity were analyzed. The results showed a 0.5% increase in the operating efficiency of the most critical machines, as well as a notable reduction in the defect rate of the final product. The research concludes that the application of TPM not only improves quality and reduces defects but also fosters a culture of continuous improvement in the company. Furthermore, the particularity of the present research is to provide an approach to ensure the long-term sustainability of the organization in the manufacturing sector, marking a significant difference with respect to previous studies by focusing on long-term solutions and a comprehensive approach to continuous improvement.

This study analyzes the entrepreneurial proposals developed by students from the PE-IEPE01 parallel course in Electrical Engineering at the Universidad Bolivariana del Ecuador (UBE), evaluating five fundamental dimensions: problem identification (20%), proposed solution (15%), innovation (20%), triple impact (20%), and feasibility (15%), along with clarity and time management (10%). The research was conducted with a population of 54 students (53 men and 1 woman), who developed projects focused on innovative energy solutions. A mixed-methods approach was employed, using specific evaluation rubrics. The overall results show that 75% of the projects effectively identified significant problems, with 68% presenting viable solutions. Feasibility was supported by functional business models and financial analysis.