Management of mechanized harvesting through operational modeling - Ferraz Dias Neto, Américo (2022)
The activity of agricultural experimentation may require high budget and long periods of time for obtaining data. Due to production features, decision-making processes within agro-industrial mills that use sugarcane as raw material must be optimized. In this scenario, modeling operating systems that use embedded technology as agricultural automation enables the optimization of decision-making and influences operational performance and costs. This article presents a model for receiving and processing sugarcane based on its harvesting capacity, considering the harvestability index and the nominal capacity of the harvester. Sensitivity analysis enables the assessment of potential offenders and the reallocation of assets, thus optimizing resources and ensuring plant operation. This analysis also enables new possibilities, such as harvesting under different row spacings and harvesting simultaneously different rows.