Simulação do método de Monte Carlo na viabilidade econômica financeira de pulverizadores: autopropelido e drones

Abstract

This study analyzes the economic and financial forecasting of two technologies used in addressing agricultural scarcity: self-propelled sprayers and spraying drones. Both technologies play significant roles in modern agriculture, particularly with the advent of Agriculture 4.0 and the growing need to optimize production processes. The research evaluates which of these technologies offers the best cost-benefit ratio across different operational scenarios, considering factors such as efficiency, operational costs, environmental impact Self-propelled sprayers stand out for their high operational capacity, being able to cover large areas in less time due to their robust and advanced application systems. However, they pose challenges related to high initial acquisition costs, maintenance expenses, and soil impact caused by weight and compaction. On the other hand, spraying drones provide greater precision in smaller or hard-to-reach areas, reducing input usage and minimizing losses due to drift. Nonetheless, their limitations, such as reduced load capacity and flight autonomy, present technical and financial challenges To perform this analysis, financial indicators such as fixed and variable costs, cash flow, Net Present Value (NPV), Internal Rate of Return (IRR), Benefit-Cost Ratio (BCR), and investment payback time were considered. Additionally, the Monte Carlo simulation was applied to measure the "confidence level," or the probability of achieving the calculated IRR and NPV values, taking into account risks, uncertainties, and variability in revenues, costs, and expenses included in the model. This approach provides a more robust probabilistic analysis of the expected results.The expected results indicate that drones are more efficient for small areas where precision is essential and operational costs are lower. Conversely, self-propelled sprayers demonstrate better economic performance in large properties due to their scalability and faster application times. The primary hypothesis is that the combined use of these technologies can maximize benefits, with drones complementing operations in specific regions while self-propelled sprayers ensure broader coverage and efficiency in larger areas.