Dynamic Simulation Modeling of Industrial Robot Kinematics in Industry 4.0

This paper studies the kinematic dynamic simulation modeling of industrial robots in the Industry 4.0 environment and guides the kinematic dynamic simulation modeling of industrial robots in the Industry 4.0 environment in the context of the research. To address the problem that each parameter error has different degrees of influence on the end position error, a method is proposed to calculate the influence weight of each parameter error on the end position error based on the MD-H error model. The error model is established based on the MD-H method and the principle of differential transformation, and then the function of uniform variation of six joint angles with time t is constructed to ensure that each linkage geometric parameter is involved in the motion causing error accumulation. Through the analysis of the robot marking process, the inverse solution is optimized for multiple solutions, and a unique engineering solution is obtained. Linear interpolation, parabolic interpolation, polynomial interpolation, and spline curve interpolation are performed on the results after multisolution optimization in the joint angle, and the pros and cons of various interpolation results are analyzed. The trajectory planning and simulation of industrial robots in the Industry 4.0 environment are carried out by using a special toolbox. The advantages and disadvantages of the two planning methods are compared, and the joint space trajectory planning method is selected to study the planning of its third and fifth polynomials. The kinetic characteristics of the robot were simulated and tested by experimental methods, and the reliability of the simulation results of the kinetic characteristics was verified. The kinematic solutions of industrial robots and the results of multisolution optimization are simulated. The methods, theories, and strategies studied in this paper are slightly modified to provide theoretical and practical support for another dynamic simulation modeling of industrial robot kinematics with various geometries.

The Pusher as an Object of the Simulation Model in the Tasks of Studying Cyclic Mechanisms Dynamics

The cyclic mechanism is one of the basic automatic machines components. It is the cyclic mechanisms that define the performance and reliability limits of these machines. The methods for assessing the automatic machines reliability are based on data of dynamic forces acting on the mechanism's links, leading to their deformation and possible destruction under certain operating conditions. Simulation modeling of dynamic processes in cyclic mechanisms is based on its representation in the form of interconnected typical objects, the allowable properties and limits of which are known. The article presents the dynamics study results one of the basic high-speed automatic machines mechanism in the object-oriented representation. Mechanism performs translational motion and allows the possibility of one-way kinematic connection breaking.

Cell lysis analysis for respiratory viruses through simulation modeling

An ordinary system of differential equations leading to a simulation model is propose as methodological approach to analysis the incidence of infectious-contagious diseases, in this case using SARS-CoV-2 virus as pathogenic model. The dynamics of the model are drive by the interaction between susceptible cells contemplating respiratory epithelial cells and viral infection mediated by two types of lysis response. To perform the simulations, values of some variables and parameters were selected from referenced sources, considering that previous reports suggested that the viral load in the lower respiratory tract might reach its peak in the second week after the beginning of disease symptoms. The scenarios described in the simulations evidence the performance of the cell lysis response from susceptible cells that have been infected. The recommend model shows that an excess response from both the original virus and the mutated virus leads to an increase in the approximate time to control viral infection within the organism.