Conference Agenda

The Fenton process was applied to treat wastewater from storage terminals of petrochemical products contaminated with xylene and toluene. The Fenton process is an advanced oxidation technology that involves the addition of H₂O₂ and Fe(II) to generate hydroxyl radicals, which degrade the contaminants. The wastewater was characterized, and tests were conducted by varying the molar ratio of the Fenton reagents (H₂O₂/Fe²⁺) in an acidic medium (pH 3.5), with a contact time of 45 minutes, to determine the optimal dosage. The efficiency of organic matter removal was evaluated by measuring the Chemical Oxygen Demand (COD) and the Biochemical Oxygen Demand (BOD₅). High removal efficiencies for COD and BOD₅ were achieved, reaching 92.44% and 93.15%, respectively, at the experimental scale, and 89.49% and 88.52% at the industrial scale. It was determined that a molar ratio of H₂O₂/Fe²⁺ of 31.3 was optimal at the experimental scale. It can be concluded that the Fenton process is effective for treating this type of wastewater, achieving compliance with the maximum permissible limits (MPL) established by Peruvian legislation.

The need to use sustainable and non-toxic ingredients drives the use of ayrampo as a natural pigment. The study evaluates the use of ayrampo within cosmetics as a pigment in lipsticks, measuring its impact on consumer acceptance. Logistic regression was used for data processing to identify the key factors that showed that the components related to pigments, fragrance, and texture are the most important. In this evaluation, ayrampo (coefficient =0.18) showed an intermediate impact in sixth place, surpassed by pigment 600 (coefficient 0.59) and Orange Fragrance (coefficient =0.50). To have an indication of the results obtained, the correlation of ayrampo with other components was measured, explaining that the intermediate impact may be since it interacts at the dependency level with high correlations (0.88) with other elements such as beeswax and coconut oil, which have a low impact (coefficients=0). Machine learning techniques such as Random Forest were applied to confirm its importance, which confirmed its intermediate influence, surpassed by pigments and fragrances. The findings reveal the importance and potential of ayrampo as a sustainable natural pigment, but further research is needed with new formulations to ensure acceptance by end consumers

Abstract– Six Sigma is a work methodology that allows companies to measure their operational efficiency, reduce defects in their processes, and improve their management. It is based on quality control and seeks to reduce variability and defects in the delivery of a product or service to the customer. The methodology can be applied to any type of process and organization.

This article deals with the application of DMAIC tool in the process of ship careening in a Latin American shipyard, Ecuadorian Navy Shipyards (Astinave). The research was conducted to optimize response times in the management of the development of maintenance, careening, and repair activities. Currently, the process takes an average of 17 to 21 days.

The article analyzes the delay in the arrival of materials and other inconveniences that result in the accumulation of unproductive time in the process. The DMAIC model was adapted, which stands for define, measure, analyze, improve, and control, for which different statistical and quality tools were used to obtain savings in the stay of the vessels.

The sequence of the process was first to diagnose the initial situation, for which statistical data of the vessels that entered the shipyard were used, then the measurement method was determined using techniques and tools that helped to identify causes for the subsequent analysis of the problems detected. Objectives were achieved with performance metrics. Finally, an action plan was proposed to provide quality, solutions, and control of the problems.

Greenhouse gas (GHG) emissions, particularly methane (CH₄), pose a critical challenge in climate change mitigation. Since the mid-18th century, CH₄ concentrations have increased significantly, surpassing other gases such as CO₂ and N₂O, which have also risen considerably. This study mathematically estimates CH₄ emissions resulting from enteric fermentation in cattle in the provinces of Herrera and Los Santos, Panama. The estimation employs the Tier 1 method of the Intergovernmental Panel on Climate Change (IPCC) and data from the 2021 national livestock census. The results indicate that these provinces contributed approximately 17,455,900 kg of CH₄ in 2021, representing 20.36% of the country’s total emissions. These findings highlight the need to implement mitigation strategies to reduce the environmental impact of the livestock sector. Methodologically, the study underscores the importance of considering regional factors when estimating emissions. However, the limited availability of detailed data prevented the application of the IPCC’s Tier 2 method, which would allow for greater accuracy by incorporating variables such as sex, age, diet, and feed digestibility. Since the results of this study provide only a general overview of CH₄ emissions in the Azuero region, improving the collection of individual cattle data is recommended. This would enable more precise estimations using the IPCC’s Tier 2 method and facilitate the identification of region-specific mitigation strategies.