Techno‐Economic Analysis of Polylactic Acid from Corn Stover: Understanding Uncertainty and Variability via Artificial Intelligence Tools

Abstract As a renewable and bio‐based material, polylactic acid (PLA) can provide long‐term sustainable environmental benefits. This study focused on analyzing the economic performance of PLA production from corn stover at a large scale in the U.S. A modeling framework is established that integrates techno‐economic analysis with the process model developed in Aspen Plus and Monte Carlo simulation that analyzes the corresponding uncertainty and variability across the system. Monte Carlo simulation is enabled by artificial intelligence (AI) models, namely Artificial Neural Network (ANN) and Random Forest. This established framework aims at streamlining the process that requires high computational time and developing an easy‐access analysis tool. Scenario analysis investigated different energy options and biorefinery lifespans. The results indicate that the mean minimum selling price of 1 t PLA is $2523 (5th percentile–95th percentile (P5–P95) $2 107–$2 940) for a 30‐year lifespan using natural gas as the energy source, $2,731 (P5–P95 $2 400–$3 076) for a 10‐year lifespan using natural gas for extra energy, and $2 637 (P5–P95 $2 370–$2 903) for a 30‐year lifespan using wood pellets for additional energy. Both AI models demonstrate the ability to predict economic performance by showing relatively high prediction accuracy, but the ANN model exhibits better performance.