Design and development of a circular disc type efficient automatic decorticator for Charoli (Buchanania lanzan)

Abstract

The manual decortication process of charoli seeds by beating the dried seeds on the ground with a hand hammer or stone and, by domestic grinder is a laborious, inefficient, time‐consuming as well as uneconomical process. Therefore, an attempt has been taken toward the automation of the charoli decortication process. The decorticator performance was evaluated at three levels of disc speeds, disc clearances, and different moisture levels of charoli seed viz. 197, 246, and 286 rpm; 6, 7, and 8 mm; and 7.83, 8.57; and 9.04% wb, respectively. The selected input parameters were optimized by using the response surface methodology (RSM). The optimum value of disc speed, disc clearance, and seed moisture content was found to be 197 rpm, 7 mm, and 9.04% (wb), respectively. The corresponding response values in terms of decorticating efficiency, whole kernel, and broken kernel percentage at optimum conditions were recorded as 92.5, 21.6, and 3%, respectively. Novelty impact statement The decorticating capacity of the developed decorticator was found to be 70 kg per hour which was higher than the existing decorticator. Since the developed machine was automatically operated and each unit operation was sequentially and continuously carried out with no manual intervention, the ideal time in each decortication step was absent and subsequently, higher capacity was achieved. The efficiency of the decorticator was found to be 92.5%. The higher capacity and kernel recovery with no human drudgery and lower cost of decortication imply the significance of the development of the machine.

Optimization of the performance of an automated/continuous pilot scale soymilk plant for medium and small‐scale entrepreneurs

“…The goal set up for the optimization process of independent as well as response variable is presented in Table 3. In order to describe the effect of independent variables on the responses variables, a second order polynomial equation of quadratic type were fitted and, the model was examined for the goodness of fit using R 2 values (Nishad et al, 2022; Thakur et al, 2021). The general form of multiresponse optimization equation of quadratic form is described as follows: where Y is the response, α 0 is the constant, α i is the linear coefficient, α ii is the square coefficient, α ij is the interaction coefficient, and X i and X j are independent variables.…”

“…The goal set up for the optimization process of independent as well as response variable is presented in Table 3. In order to describe the effect of independent variables on the responses variables, a second order polynomial equation of quadratic type were fitted and, the model was examined for the goodness of fit using R 2 values (Nishad et al, 2022;Thakur et al, 2021). The general form of multiresponse optimization equation of quadratic form is described as follows:…”

Modeling and optimization of integrated earth air heat exchanger and direct evaporative cooling system using ANN and RSM approaches for preserving fruits and vegetables

“…The total number of experiments required to create the BBD model is expressed as (Nishad et al, 2022):…”

“…The RSM is typically used to plot a response area on a specific area of interest, optimize responses, or select operating conditions to achieve the performance objective (Nishad et al, 2022). Recently, ANN has become an interesting tool for nonlinear multidimensional modeling (Dey et al, 2021).…”

“…The response surface methodology (RSM) has been used extensively and efficiently to examine and optimize input variables for experimental design and model development (Mangaraj et al, 2022). The RSM is typically used to plot a response area on a specific area of interest, optimize responses, or select operating conditions to achieve the performance objective (Nishad et al, 2022). Recently, ANN has become an interesting tool for nonlinear multidimensional modeling (Dey et al, 2021).…”