October 7, 2022
A proposal submitted by Mississippi State Department of Industrial and Systems Engineering professor Mohammad Marufuzzaman was selected for funding by the United States Department of Agriculture through June 2025.
The proposal idea, “The Image Based Assessment of Wood Chip Qualities: Transferred Learning Model Development to Field Validation,” was created in the summer of 2021 by Marufuzzaman, whose research interests include operations research, machine learning with applications in transportation and agricultural systems. Marufuzzaman collaborated with Mississippi State faculty Jason Street from the Department of Sustainable Bioproducts, as well as engineering professors Gnaneswar Gude (formerly Civil & Environmental Engineering), Haifeng Wang (Industrial & Systems Engineering), and extension associate James Wooten (Agricultural & Biological Engineering).
Marufuzzaman’s research for this proposal aims to develop a cost-effective, computationally sound, industry-scale image-based contact-free analysis tool to assess wood chip qualities rapidly and with high accuracy. Wood chips are primary sources of raw materials for many industries, such as pelleting mills, biorefineries, pulp-and-paper industries, and biomass-based power generation facilities, but the consistency of the wood chip qualities (e.g., moisture/ash contents, size distributions) is a major problem for these industries. The ongoing industry-scale woodchip quality assessment processes take several hours, which the team strives to achieve in a few seconds by developing advanced artificial intelligence-driven solutions. The prototypes will be tested and verified in several facilities in Drax Biomass, Inc.
The funding, which includes $650,000 through the United States Department of Agriculture, allowed Marufuzzaman to start researching this project in July 2022.
Marufuzzaman recognizes the importance of Mississippi State’s commitment to research and the level of expertise of the faculty members.
“Our interdisciplinary team has a strong prior agricultural-based research record, supported by the resources provided by the respective departments and the colleges to help us secure this competitive grant. To the end of this project, we strive to develop an AI-guided physical tool that can be readily implementable by the bioenergy industries.”
Marufuzzaman and his team began research for the proposal this July and will complete their research in June 2025.