Data driven decision support for reliable biomass feedstock preprocessing

Biomass feedstock preprocessing through comminution is an essential first step in biofuel production. Chemical, physical and mechanical variability in feedstock prevents the preprocessing plants from assuming constant control parameters. Constant control parameters can lead to suboptimal capability and reliability. However, adapting the control parameters to account for the variabilities is not a trivial task. This paper presents a framework for adapting control parameters through data driven methodologies. The framework named PDU- RS is a decision support system for human in the loop control. PDU-RS is implemented on the Biofuels National User Facility Preprocessing Process Demonstration Unit (PDU), operated by the Idaho National Laboratory (INL) in Idaho Falls, Idaho. PDU-RS aims at ensuring reliability in the overall operations of the PDU while maximizing throughput. Presented implementation of the PDU-RS uses Gaussian Processes (GP) for knowledge extraction from data. This paper elaborates on the PDU-RS and presents the experimental results of implementing the PDU-RS on the real Biomass PDU. The experimental results demonstrated that the PDU-RS is able to produce significantly higher throughputs while ensuring higher reliability when compared to the traditional control methodology used with the system.