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Predictive modeling and risk analysis of Solar Hybrid Kiln

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.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-4612
Date09 August 2019
CreatorsParkhe, Mukul
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

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