Starting from the influencing parameters of threshing and separation and implicit seed losses that occur within this process, this paper searched for and identified the optimal threshing regimes to minimize losses depending on the process parameters. The evacuation losses (p_ev) depend on threshing rotor speed (n) and implicit rotor peripheral speed (v_p), material feed speed (v_a), the space between the rotor and counter-rotor (δ), material feed flow (Q), material density (ρ), and the length of the threshing apparatus (L). As the parameters ρ and L are constant, the variation of losses in relation to each of the arguments was followed: v_p, Q, ρ, and v_a, respectively, for the minimization of losses by the variation of the loss function by two arguments each (represented graphically); the four arguments targeted being: v_p, v_a, ρ, and Q. Using these input parameters, it was possible to determine the optimal threshing regimes for the variation of losses in relation to the rotor peripheral speed, the feed flow, the space between the rotor and the counter-rotor, and the feed speed, so as to obtain a seed separation percentage (S_s) as close as possible to 100% (and implicitly the smallest threshing losses—towards zero) in relation to these parameters.

The current study focuses on analyzing the impact of integrating an optical sorter in a seed-separation technological flow, in terms of increasing the quality of the maize seeds appropriate for sowing. The study showed that there are situations when the use of optical separation may result in a number of difficulties in removing a variable rate of good seeds from the raw mass, which can bring economic disadvantages. The identified issue encouraged the development of several flow assessment approaches in order to determine the problem’s essence and to develop the best strategy for action. The key finding was that the evaluated optical sorting equipment cannot eliminate impurities without also removing good seeds, resulting in every 1% increase in impurity level and a rate of 0.70% of the good seeds lost. Therefore, farmers must carefully consider the scenarios where integrating optical sorting into their technological flow is a suitable option, considering the input material quality, the selling price of the product, and the risk of missing an important quantity of high-quality seeds. The working method described may be of significant importance to other farmers who intend to choose the components of grain-cleaning processes effectively.

This paper presents theoretical and experimental research on the process of calibrating corn seeds using a specialized equipment with cylindrical sieves, studying the influence of process parameters and corn seed particularities on the quality of the calibration work. The research took into consideration corn seed characteristics, namely, their dimensions (length, width, and thickness) and weight, determining the influence of process parameters—the contact point between the seed and the cylindrical sieve, the influence of the length of the sieve, and the sieve’s revolution speed on the separation process. The experiments for determining the influence of these parameters on the calibration process were conducted on a calibrating equipment with cylindrical sieves using three different corn hybrids. It was noticed from the experiments that, overall, the revolution speed had the most important effect on the calibration process, with sieve length also affecting the process, but to a lesser degree. Seed calibration efficiency was best at the smallest revolution speed (33 rot/min) and decreased when the revolution speed increased up to 49 rot/min for all corn hybrids tested. The number of calibrated seeds decreased in the second part of the cylindrical sieve. Seed thickness influenced the process, in the respect that seeds smaller than 4.8 mm passed through the first third of the sieve and those with a thickness between 4.8 and 5 mm passed through the other two thirds of the sieve length.

This study presents a multivariate regression-based analysis aimed at quantifying the influence of key vibration-generating components in two types of grain combines—C110H (with straw walker) and CASE IH (axial flow)—on the operator’s seat (OS). Using triaxial accelerometers, vibrational measurements were performed under both stationary and operational working mode. RMS acceleration values were recorded for major subsystems (engine, threshing unit, chassis, chopper/header) and processed via multiple linear regression. The models generated for each combine and axis (Ox, Oy, Oz) revealed high coefficients of determination (R² > 0.85), confirming the linear model’s validity. Influence maps and standardized coefficients were used to rank the sources of vibration. Results indicate that the straw walker dominates vibration transmission in the C110H, while the header and threshing system are more significant in the CASE IH. The findings support the development of predictive algorithms for real-time vibration monitoring and ergonomic improvements in combine design. Moreover, the proposed methodology provides a cost-effective diagnostic tool for early fault detection, targeted maintenance, and the long-term reduction of operator fatigue and injury risks.