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Effects of Operational Factors on The Productivity, Efficiency, And Power Consumption of a Fish Meal Pelleting Machine Kosemani, Babajide; Sule, Shakiru Okanlawon; Adewumi, Idowu Olugbenga; Afolabi, Bukola Olanrewaju; Mufutau, Monsuru Olayinka
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Pelletizing remains one of the most economical and technologically advanced techniques for producing fish feed. The quality characteristics of the resulting pellets are influenced by several operational variables, which, when improperly controlled, can lead to suboptimal feed quality. This research work optimizes some operational parameters including die size, shaft speed and feeding rate of an indigenous fish meal pelletizing machine for productivity, efficiency, power consumption and specific energy consumption. Mixed fish feed materials were pelletized at 29, 31 and 31m/s die speed, loaded onto the pelleting machine at different feeding rates (15, 20, and 25kg/hr) and die hole (3, 4, 5). The RSM was employed to improve the machine performance by analysing the impact of multiple operational variables on the response including productivity, efficiency, power consumption and specific energy consumption. The interaction of the operational parameters and response factors were established through Quadratic models. The impact of the operational parameters on productivity, efficiency, power consumption and specific energy consumption were significant (p ?0.01). The optimal condition of the process for die speed, die hole and feeding rate were 31m/s, 5mm and 20kg/hr, respectively, resulting in machine productivity, efficiency, power consumption and specific energy consumption of 82.02kg/hr, 86.09%, 2.55kW, and 0.029 kWh/kg, respectively. This indicates that the fish meal pelletising machine ran efficiently under optimal conditions, therefore validating the generated models.