In line with the goals of sustainable development in quality education and fostering partnerships to achieve these objectives, Asst. Prof. Dr. Qasim Mousa Madlol, a faculty member in the Department of Agricultural Machines and Equipment, College of Agricultural Engineering Sciences, University of Baghdad, participated as a member of the examination committee for the master’s thesis entitled:
“Evaluation of the Performance of the Hammer Mill and the Performance of Prediction Models to Simplify Operational Settings and Achieve Different Grinding Grades with Accuracy”
by the M.Sc. student Ali Khairallah Dhahir, Department of Agricultural Machines and Equipment, College of Agriculture, University of Basrah.
“Evaluation of the Performance of the Hammer Mill and the Performance of Prediction Models to Simplify Operational Settings and Achieve Different Grinding Grades with Accuracy”
by the M.Sc. student Ali Khairallah Dhahir, Department of Agricultural Machines and Equipment, College of Agriculture, University of Basrah.
The thesis aimed to evaluate the performance of the hammer mill under the effect of three factors: sieve hole diameter, clearance, and number of hammers, in addition to the two-way and three-way interactions of these factors on certain performance indicators. It also sought to determine the relative importance of the main factors’ effects, as well as to assess the performance of the artificial intelligence prediction model in forecasting hammer mill performance indicators based on the three studied factors (three input parameters), and to compare it with the prediction model based on the single most influential factor (one input parameter). Furthermore, the research aimed to identify the best interaction among the studied factors that achieves the target particle size distribution without excessive energy consumption or deterioration of machine productivity.
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