Conference Agenda

The purpose of this research was to propose improvements in workstations to increase productivity on a salt processing line. The initial diagnosis revealed low labor productivity of 13 CMK bags/day-operator and an absenteeism rate of 13,8% due to MSDs, resulting in losses from unfulfilled orders. High ergonomic risks were identified, with maximum REBA scores of 11, OCRA Checklist values above 22,5, and load handling indices greater than 18 kg. In addition, noise levels reached 100,6 ± 2,1 dB, and 80% of workstations had insufficient lighting. Based on these results, improvement strategies were proposed following the hierarchy of controls. These included replacing manual operations with machinery, engineering controls for the design of a filling machine using SolidWorks, administrative controls, and the use of PPE. The improvement is estimated to be a decrease in ergonomic risk at all workstations, a 23% increase in labor productivity, and a 10% increase in total productivity. Finally, the feasibility and profitability of the project were demonstrated by a NPV of S/ 25 648,98, an IRR of 30,38%, and a B/C ratio of 1,51.

The overall objective of the research was to increase the productivity of the pineapple peeling and cutting process in the agro-industrial freezing stage by designing an automated system. For the first specific objective, the performance of the manual process was diagnosed using direct observation, analysis of production records, and ergonomic evaluation. During the annual season, 1,124,948.2 kg of fresh pineapple were processed, yielding an average net yield of 34.85%, a rejection rate of 65.15%, a cycle time of 39 s per pineapple, and a Total Factor Productivity (TFP) of 1.103, evidencing low efficiency and high raw material waste. For the second objective, an automated system was designed using SolidWorks for the mechanical design, CADe SIMU for the electrical and pneumatic system, and SoMachine for the simulation of the control logic with PLC. The simulation made it possible to reduce the cycle time to 25 seconds per pineapple, representing a 35.89% improvement in productivity, in addition to projecting a reduction in the rejection rate to 22.80% and an increase in overall net yield to 77.20%. Finally, the comparative economic analysis showed a reduction of 476,415.56 kg in waste, an estimated saving of S/ 1,191,038.91, and an increase in PTF to 2.73. The financial evaluation yielded a NPV of S/ 221,773.81 and an IRR of 40.35%, confirming the technical and economic viability of the proposal

In this article, we benchmark three popular constraint programming (CP) solvers for the job shop scheduling problem (JSSP) under identical hardware and computation-time conditions, with the objective of minimizing the makespan. For evaluation purposes, we use 80 classic Taillard instances. Overall, CP Optimizer proved to be the most competitive solver, demonstrating optimality in 38 instances, despite a slightly higher average optimality gap (3.06%). OR-Tools followed closely, achieving a marginally smaller average gap of 2.86%, proving optimality in 23 instances, and consistently producing competitive lower bounds. In third place, Hexaly exhibited improved performance as the instance size increased.

Inventory inefficiency represents a critical operational and financial challenge for small and medium-sized enterprises (SMEs) in the gastronomic sector, particularly in emerging economies where formal control systems are often absent. This study presents an applied case analysis of inventory optimization in a small-scale restaurant located in Guayaquil, Ecuador. Using transactional sales data from a one-month operational period, an integrated inventory control framework combining ABC classification and Just-in-Time (JIT) policies was designed and implemented. The study evaluates the impact of differentiated stock control policies, safety stock calculations, and reorder point mechanisms on storage costs, waste reduction, and working capital utilization. Results indicate that Category A products accounted for approximately 80% of total revenue, enabling prioritized control strategies. The implementation of the proposed framework reduced estimated storage costs by 30%, waste by 60%, and improved working capital liquidity with a projected payback period of three months. Despite data limitations, findings demonstrate that structured inventory control models can significantly enhance operational efficiency in small-scale food service businesses. The study contributes practical evidence for inventory optimization in data-constrained SME environments.

Thermal process optimization in the food industry is essential for reducing variability and ensuring operational standardization. This study, conducted by Industrial Engineering students, aimed to evaluate the influence of three critical variables, egg type, fatty medium, and cooking surface material, on the response time during the egg white frying process. A methodology based on Design of Experiments was employed, utilizing a 2x2x2x2 full factorial model with two replicates, totaling 16 experimental runs performed under strict principles of randomization, replication, and control of external variables. Data were processed using ANOVA with a 95% confidence level, allowing for the determination of the statistical significance of main effects and their interactions. The results demonstrated that the pan type is the only main factor with a significant influence (p < 0.05) on cooking kinetics, which is attributed to differences in thermal diffusivity and inertia of the evaluated materials (Teflon vs. stainless steel). This study allowed the students to integrate advanced statistical tools into a practical scenario, strengthening competencies in systems analysis and process optimization through specialized software (Excel and SPSS v.31). It is concluded that tool control and the strategic selection of input combinations are decisive for optimizing cycle time, providing future engineers with a robust quantitative basis for data-driven decision-making and demonstrating that systematic experimentation is essential for efficiency improvement in both academic and industrial contexts.