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Title:Mapping and evaluation of machine performance data from farm operations
Author(s):Kennedy, Thomas
Advisor(s):Hansen, Alan C.
Department / Program:Engineering Administration
Discipline:Agricultural & Biological Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Geographic Information System (GIS)
Abstract:The costs associated with inefficient agricultural operations are increasing as the price of fuel, labor, and machinery increases. This study presents an analysis of the machine performance data collection method performed on two large-scale Midwestern farms. This data collection method sought to record data from each machine involved in agricultural production on a one second interval for one season. After the collection of the data, it was analyzed on a data quality basis and a machine performance basis. The objective of data quality analysis was to create a metric on which the confidence of the results of the machine performance analysis could be based. In analyzing machine performance, the geographic information system, ArcGIS™, was used to present the information in a geographic reference. Results of the analysis of the data collection process revealed several flaws that reduced the quality of the collected data. The cause of the data quality issues associated with the collection of the data was attributed to the transmission of the data via cellular networks instead of an error with the actual recording of data from the machine. Additional recommendations regarding the setup of data loggers were made in order to increase the detail of the data, and increase the value of conclusions that could be made based on these data. After reviewing the process with which the data were collected, a method to analyze the data was created. This method included a visual inspection of machine parameters for geographic trends in the data. Additionally, the data was analyzed statistically to determine the relationships between machine parameters on a single machine. The visual analysis of parameters on multiple machines was able to show the interaction of independent machines in field operations. A comparison of machine performance was provided on an individual field basis and a farm wide basis in order to identify fields in which machine performance differed significantly from the farm average. Combining the method included in this study with improved data quality resulting from the implementation of data collection recommendations was anticipated to provide information to improve machine design and to direct farm managers to areas of inefficiencies in the farming operation and the operation of individual machines in the fields.
Issue Date:2013-05-24
Rights Information:Copyright 2013 Thomas Kennedy
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05

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