Degree Type

Dissertation

Date of Award

2017

Degree Name

Doctor of Philosophy

Department

Agricultural and Biosystems Engineering

Major

Industrial and Agricultural Technology

First Advisor

Gretchen A. Mosher

Abstract

Occupational injuries continue to be a major issue for non-farm agricultural workplaces such as commercial grain elevators and ethanol plants. For preventing these injuries and improving workplace safety outcomes requires learning from past incidents, and identify the most significant causes and implement targeted prevention strategies. However, obtaining detailed records of past incidents is a challenge acknowledged by investigators across several industrial sectors including agribusiness. Previous researchers suggest workers ’ compensation claims as an excellent data source to address the existing informational gaps about safety incidents and injuries in the workplace. In this study, workers’ compensation claims obtained from a leading private insurance company were investigated using statistical techniques such as chi-square tests, regression analysis, and data mining techniques such as decision trees. The study objective was to analyze these claims, identify injury causes, risks, and problem areas so supervisors and safety professionals can make decisions needed to improve safety outcomes in the workplace. The findings of this study are documented in three separate manuscripts. Since safety incidents that cause injuries and fatalities have a widespread impact, therefore mitigating these incidents using a proactive data-driven approach rather than just compliance can benefit the worker, the organization, and society-at-large.

Copyright Owner

Sai Kumar Ramaswamy

Language

en

File Format

application/pdf

File Size

149 pages

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