Design and Simulation of a Cocoa Bean Winnowing Machine to Optimize the Processing Workflow

Abstract

The design and simulation of cocoa depulping machines represent a key advancement in agricultural engineering aimed at optimizing pulp extraction and improving efficiency along the production chain. Traditionally, this process has been manual, limiting productivity and product uniformity; therefore, the incorporation of machinery powered by 2 HP motors has emerged as a viable alternative for small and medium-scale producers. These machines, developed using tools like SOLIDWORKS, have been validated through structural simulations and finite element analysis (FEA), ensuring durability, resistance, and functionality. The study employed a mixed-methods approach, combining qualitative and quantitative data through a systematic literature review and fieldwork in the province of Santo Domingo de los Tsáchilas, including surveys and interviews with producers, engineers, and technicians. Results demonstrate that these machines reduce processing time, production costs, and the reliance on intensive labor, while also improving worker safety and enabling product traceability. Furthermore, the integration of artificial vision and machine learning algorithms has enhanced cocoa bean classification, achieving a 90.5% accuracy rate. Economic analysis revealed that the initial investment in these machines is recoverable within a reasonable timeframe, supporting the profitability and sustainability of cocoa farms. Ultimately, efficient mechanical design, computational simulation, and thorough technical and economic feasibility analysis constitute an integrated strategy to boost the competitiveness of Ecuador's cocoa sector and foster rural technological development.