Size grading is one of important processes for producing the Robusta green coffee bean because it can increase the value of green coffee bean and decrease the problem in the manufacturing process, especially roasting process. Therefore, the objective of this work was to investigate the effects of inclined angle and oscillating revolution speed on the performance of size grading machine of Robusta green coffee bean using oscillating sieve with swing along width direction. When increasing the inclined angle from 4 to 6 degree, the weight purity index and the clogging sieve percentage were decreased. For the size grading efficiency, it found that the size grading efficiency was increased when the inclined angle increased from 4 to 5 degree. However, the size grading efficiency was decreased when increasing the inclined angle from 5 to 6 degree. When considering in term of oscillating revolution speed, the increase of oscillating revolution speed provided the decrease of weight purity index, size grading efficiency and clogging sieve percentage. The appropriate condition for using the size grading machine of Robusta green coffee bean using oscillating sieve with swing along width direction is the inclined angle of 5 degree and the oscillating revolution speed of 185 rpm.
One of the essential processes for producing the green coffee bean with Robusta variety is size sorting process because it is able to add the value of green coffee bean. The excellent size sorting can be done by using the size sorting machine. In this study, the size sorting machine with revolved sieve which provided the good distribution of green coffee bean was used and the three factors such as sorting angle, revolved speed and feed rate were investigated using Response Surface Methodology (RSM) based on a Central Composite Design (CCD). The optimum conditions of size sorting efficiency were revolved speed of 8.35 rpm, sorting angle of 5.05 degree and feed rate of 26.59 kg/h. These provided the size sorting efficiency of 75.15% with high correlating coefficient (R2 = 97.65). This indicated that the data predicted with Response Surface Methodology was good agreement and adequacy of models.
Grading according to the sizes is an important value adding technique for Robusta green coffee bean. Mechanical grading can increase the sorting efficiency and the need for workers is decreased. Therefore, the sorting efficiency of size grading machine was optimized based on inclined angle and oscillating speed. The Response Surface Methodology (RSM) combined with central composite design (CCD) was applied in the optimization of the sorting efficiency of the machine. A quadratic model was suggested for the sorting efficiency of size grading machine. The results showed that the optimum operating parameters for size grading machine using oscillating sieve with swing along width direction were inclined angle of 5.06 degree and oscillating speed of 183.28 rpm with a sorting efficiency of 79.99%. The high correlation coefficient (R2 = 0.9676) indicated that the data predicted using RSM were in good agreement with the experimental results.
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