Date of Award

12-2018

Degree Type

Thesis

Degree Name

Master of Science

Major

Forestry

Major Professor

Timothy M. Young

Committee Members

Bogdan C. Bichescu, Terry Liles, Alexander Petutschnigg

Abstract

Cellulosic biomass is a highly variable feedstock. The large variation in key quality attributes (e.g., ash content, moisture content, and particle size) challenges the consistency of the feedstock supply from a technological and economical perspective. This affects the cost and the overall competitiveness of the sustainable bio-based industries. This research focuses on developing strategies to reduce variation and cost throughout the supply chain for the bio-based industries.The goal of this research is to provide practitioners with tools to quantify variation of the components of the supply chain and illustrate that variation accumulates throughout the supply chain which induces costs from higher than necessary operational targets. The objectives of this research are: 1) develop quality loss functions for the components of the biomass supply chain; 2) create a simulation model suitable to quantify feedstock variation; 3) characterize the impact of variation on the financial loss, and 4) develop a handbook of statistical and continuous improvement techniques to promote variation reduction.The Excel simulation model uses Statistical Process Control and Taguchi’s Loss Function combined with Galton’s theory of ‘components of variance’ to estimate the financial loss due to variation. Sensitivity analyses are used to characterize the impact of variation on loss for ash content, moisture content, and particle size. The handbook provides practitioners with a guide for improved application of universally accepted key continuous improvement techniques.The additional loss per unit on average for Switchgrass from ash content variation was estimated to be $17.33 per dry ton, while for particle size (woody residues) the loss was $10.32 per dry ton. The additional loss per unit on average for moisture content variation was estimated for an example supply chain. The loss per unit for harvest/collection was $2.02, transport was $4.93, drying was $3.19, and densification was $13.23 per dry ton. The results of this study suggest that Taguchi’s Loss Functions are suitable to estimate the loss for feedstock quality characteristics based on variation. The simulation tool and handbook will help practitioners of the sustainable bio-based industries improve the supply chain’s performance (available at www.spc4lean.com).

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