International Journal of New Technology and Research (IJNTR) ISSN:2454-4116, Volume-2, Issue-10, October 2016 Pages 10-13 10 www.ijntr.org Abstract- A single response optimization model based on Response Surface Methodology was employed to determine the best combination of the functional machine parameters such blade type, basket orientation and speed of a developed automated grain drinks processing machine to attain the maximum drink output. The automated grain drinks processing machine blend soaked grains, mixed the slurry, extract the aqueous liquid and expel the paste from the machine all in single unit. The experiment was based on central composite rotatable design (CCRD). The experimental result showed that the developed regression model could describe the performance indicators within the experimental range of the factors been investigated. Blade type and speed of rotation were found to be significant (p≤ 0.05), while basket orientation was insignificant. Numerical optimization carried out produced optimum values of 3-blade assembly, basket orientation of 33.44 o and speed of 1385 r.p.m and the blending efficiency was 8.47 lires from 400g of soya beans. Index Terms- automated, grain, drinks, output. I. INTRODUCTION In the present investigation, a single response optimization model based on Response Surface Methodology was employed to determine the best combination of the functional parameters such blade type, basket orientation and speed of a developed automated grain drinks processing machine to attain the maximum drink output. In Nigeria the available equipment used for production of grain beverages are made from mild steel materials which can easily become rusted due to its frequent contact with water and this can lead to contamination of the product [1]. According to [2] the production process involves different stages using different equipment. In order to address the tedious of this operation and to produce hygienic drink with high quality, an automated grain drink processing machine was developed. Hence, there is a need to optimize the functional parameters of the machine based on the drink output in a systematic way to achieve the optimum parameters and maximum response by using experimental methods and statically models. Gbabo Agidi, Agricultural & Bioresources Engineering Department, Federal University of Technology, Minna, Nigeria, Gana, Ibrahim Mohammed, Agricultural & Bioenvironmental Engineering Department, Federal Polytechnic/ Bida, Nigeria, II. EXPERIMENTAL PROCEDURE The experiment was conducted as per design matrix shown in Table 2. The soya beans samples were obtained sorted and cleaned to remove foreign materials before soaking for 12 hours [2] : [3] : [4]. Water was drain from the soaked soya beans before feeding into the machine. The machine was switched on, data (blending and sieving time) were inputted and saved. The auto run switch was pressed which launched the system into automatic operation of the machine. The water valve was open in order to allow inflow of water into the system. The water to grain ratio of 10:1 was used for the washing of the milk from the paste in order to have proper washing of milk from the slurry. The blending blades blends the grains, mixed the slurry with water. The aqueous liquid with the paste were spins to the wall of the conical basket due to the centrifugal force generated, the liquid was filtered out of the machine through the perforated holes on the basket while the paste which are bigger in size than the perforated holes migrated up along the wall of the basket. The paste was discharged out at the top of the basket. The liquid were collected at the bottom of the basket and flow out to the temporary milk tank III. EXPERIMENTAL SET-UP A. EXPERIMENTAL APPARATUS For performing the experiments, an automated grain drink processing machine developed at Agricultural and Bioresources Department of Federal University of Technology Minna, Nigeria was used. From preliminary studies and review of literature, blade type, basket orientation and speed were found to be the most critical factors that affect the process of grain beverages production from grains [2] ; [5]. Therefore these factors were selected as the machine functional parameters and there levels are presented in Table 1. Variability Effect of Some Mechanical Parameters of an Automated Machine on Grain Drink Production Output Gbabo Agidi, Gana Ibrahim Mohammed