Masters Theses

Orcid ID

http://orcid.org/000-0003-0633-2252

Date of Award

5-2018

Degree Type

Thesis

Degree Name

Master of Science

Major

Industrial Engineering

Major Professor

James A. Ostrowski

Committee Members

Jamie B. Coble, Mingzhou Jin, Erin Webb

Abstract

Harvest cost is a major concern for making biomass a viable option. Unproductive time in-field significantly contributes to this cost. Variability of harvest timeliness is largely due to maneuvering equipment in-field, operator experience, equipment failures, and field and crop conditions, among other reasons. These are particularly important for farm management to know how to best handle interruptions during harvest. Consequently, there is a serious need to better account for harvest untimeliness. For this research, the crops of interest are Miscanthus and shrub willow. These crops are attractive for several reasons. They do not compete with cash crops because they grow on marginal land and have the potential normalize feedstock qualities. In general, three aspects of harvest productivity will be focused on, which include: equipment maneuverability at the headlands, operator performance, and equipment reliability. More specifically, maneuvering equipment during harvest operations can have a significant impact on production cost; therefore, the fieldwork pattern is critical for optimal productivity and a cost-efficient harvest. Harvest pattern influences time wasted due to excessive unproductive time and distances traveled during operational tasks. Equipment is maneuvered at the skill of the operator. Often, operator experience is a bottleneck for operations and a key factor influencing productivity. In addition, unproductive times are largely due to repair and maintenance on the equipment caused by unexpected harvest complications. The uncertainty of these factors cause inconsistency in productivity. It is crucial to achieve optimum harvest efficiency for the feasibility of the biomass supply chain. Evaluating these aspects will allow us to better understand and model for these limitations.

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