# Energy Saving in Electromechanical Grain Cleaning Systems
## 3 Results  
The issue of optimizing the process of cleaning food grains on the production lines of grain dispensers is to find such modes of operation of the grain cleaning production lines, which result in the minimum SEC within the range of changes of input parameters. The process of cleaning food grains on the production lines without disc separators was investigated. A multifactorial experiment [8] is appropriate for determining the influence of factors on the optimization criteria of the grain cleaning process on the production lines of grain storage facilities. The theory and practice of its design are characterized by a high level of development and make it possible to obtain, with a minimum number of tests, a credible mathematical model of the object of the research and, in solving the problem of optimization, to determine the optimal conditions of its functioning. The relationship between the SEC and performance is non-linear, so second-order designs were used to obtain the regression equation. The selection of factors, ranges and the range of variation are based on the analysis of a priori information. The variation limits of the factors under investigation were adopted, considering the technical characteristics of the machines and the technological constraints conditioned by the production of high-quality grains [15]. The variables are: \(x_{1}\)--the machine's capacity, (Q), t/h; \(x_{2}\)--grain humidity, (Hum), % and \(x_{3}\)--grain dockage, (Doc), %. The specific electricity consumption (W\({}_{sp}\)), kW\(\cdot\)h/t, was selected as a response function. The Box-Wilson orthogonal central composite design (OCCD) of the second order [15] was used to mathematically describe the specific electricity consumption. A number of mathematical models describing the response function's dependence on input parameters were derived from the calculations. Factor levels and factor variability intervals were taken for ZAV-20 with one production line without disc separators (Table 1). A regression equation was obtained to calculate the specific electricity consumption depending on the productivity, humidity and dockage for the ZAV-20 grain-cleaning machine with one production line without disc separators both in dimensionless form: \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Levels**} & \multirow{2}{*}{
\begin{tabular}{c} **Standardized** \\ **Variable** \\ \end{tabular} } & \multicolumn{3}{c}{**Actual Scale**} \\ \cline{3-5}  & & \(x_{1}\)**, t/h** & \(x_{2}\)**, \%** & \(x_{3}\)**, \%** \\ \hline Base level & 0 & 6.5 & 13.5 & 3.5 \\ Variability level \(\Delta x_{i}\) & \(\pm 1\) & 1.5 & 1.5 & 0.5 \\ Lower level of the FFE & \(-1\) & 5.0 & 12.0 & 3.0 \\ Upper level of the FFE & \(+1\) & 8.0 & 15.0 & 4.0 \\ Lower star point of the OCCD & \(-1.215\) & 4.7 & 11.7 & 2.9 \\ Upper star point of the OCCD & \(+1.215\) & 8.3 & 15.3 & 4.1 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Factor levels and factor variability intervals for ZAV-20 (one production line without disc separators). \[\widetilde{y}=2.748-0.5451x_{1}+0.0411x_{2}+0.0703x_{3}+0.1216x_{1}^{2}+0.0271x_{2 }^{2}+0.0203x_{3}^{2} \tag{1}\]  
and in natural values of the factors:  
\[\text{W}_{sp}=9.7-1.065\cdot\text{Q}-0.296\cdot Hum-0.427\cdot Doc+0.054\cdot \text{Q}^{2}+0.012\cdot Hum^{2}+0.081\cdot Hum^{2}, \tag{2}\]  
Similar studies were performed on two production lines with no disc separators (Table 2). A regression equation was obtained to calculate the specific electricity consumption depending on the capacity, humidity and dockage for the ZAV-20 grain-cleaning machine with two production lines without disc separators both in dimensionless form:  
\[\widetilde{y}=1.7437-0.4629x_{1}+0.053x_{2}+0.0183x_{3}+0.0275x_{1}x_{2}+0.20 42x_{1}^{2}+0.0455x_{2}^{2}+0.0118x_{3}^{2} \tag{3}\]  
and in natural values of the factors:  
\[ \begin{array}{c}\text{W}_{sp}=9.941-0.5864\cdot\text{Q}-0.5709\cdot Hum-0.2 938\cdot Doc+0.0052\cdot\text{Q}\cdot Hum+\\ +0.0167\cdot\text{Q}^{2}+0.0202\cdot Hum^{2}+0.0472\cdot Doc^{2}\end{array}