Performance Evaluation and Optimization of a Palm Kernel Cracker–A Taguchi-Grey Relational Analysis Approach

Abstract

The palm kernel cracking machine plays an important role in the palm oil and kernel oil processing industries for removing kernels from the outer shells. The parameters of the machine operation are required to be optimized to achieve the best machine efficiency. This study optimizes a palm kernel cracker using the Taguchi-Grey relational analysis approach. A L9 orthogonal array was used for the experimental design using two factors at three levels (speed–1000, 1200, and 1400 rpm; weight–2, 4, and 6 kg). Analysis of variance and regression analysis were done. The results revealed that the machine's efficiency greatly influences the rotation speed compared to the nuts' weight. The throughput capacity was higher at higher weight and lower cracking time. For most of the responses, the weight of the palm kernel nuts was ranked more important than the machine's rotation speed. For the optimization, optimum cracking efficiency was at 1000 rpm speed and 4 kg weight; optimum throughput capacity and optimum labour requirement were obtained at 1000 rpm speed and 6 kg weight, respectively. Mathematical models were developed for all responses using the input parameters. The experimental values and the predicted optimum results were determined to be close based on the processing conditions. Also, the mathematical models suitably predicted the performance of the developed palm kernel cracking machine.