Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Jaradat, Ra'ed
Committee Member
Ma, Junfeng
Committee Member
Millar, Richard C.
Committee Member
Mazzuchi, Thomas
Committee Member
Bian, Linkan
Date of Degree
8-9-2019
Document Type
Graduate Thesis - Open Access
Major
Industrial and Systems Engineering
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Industrial and Systems Engineering
Abstract
Increasing population equals increase in agricultural product consumption for which continuous food production is not a viable option. Solar drying, on the other hand is a promising method to preserve agricultural products for longer durations. This thesis focuses on calculating the predictability of the independent factors and a comprehensive risk assessment to improve the performance of Solar Hybrid Kiln. Biochar samples with different moisture content were selected for 3 tests. Principal component analysis and multiple linear regression analysis were conducted on the gathered data using Minitab 18R platform. Risk response plans associated with the kiln were provided through failure mode effects analysis. Results exhibited 3 significant principal components and reliable prediction model limits were obtained for both training and testing datasets. A total of 41 risks were identified and risk response plans were proposed for them. These results can be further used to increase the efficiency of biochar drying processes.
URI
https://hdl.handle.net/11668/14603
Recommended Citation
Parkhe, Mukul, "Predictive modeling and risk analysis of Solar Hybrid Kiln" (2019). Theses and Dissertations. 3613.
https://scholarsjunction.msstate.edu/td/3613
Comments
Solar Kiln||Hybrid||Prediction||Risk||Analysis