Predictive model adjusted to the milling process and the effect on economic profitability simulated with Montecarlo, a rice processing company

Escalante-Correa L.; Geldres-Marchena T. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2021) · DOI: 10.18687/laccei2021.1.1.173

Resumen

The main objective of this research was to show the predictive model implementation effects adjusted to grinding process on the economic profitability of a rice milling company. In first instance, quality and production area database was used to model a multiple regression equation, using the “Step by Step” technique in Minitab 19, resulting in: Actual Performance = 0.001 + 0.9317Hest Analysis - 0.000339 Processed Sacks; Predictive R2 = 95.81% and PRESS = 47.5168; concluding that the model fits the process, it is significant and has good predictive capacity. The regression equation was then simulated with Monte Carlo by analyzing probabilities and ranges in MS-Excel, earning operational revenue amounting to S/. 3,263,787.74 corresponding to an improvement of 3.94% compared to 2019, thus improving the company's economic profitability to 9.34% in Net Profit Margin and 15.92% in the ROA. Finally, the financial analysis of the project was carried out obtaining a Financial VAN of S/. 284,307.56, a Financial TIR of 133% and a Profit-Cost of S/.1.10, so the investment proposal is viable for the company.

Instituciones: Universidad Privada del Norte