Computer modeling is a method for solving the problems of analysis or synthesis of a complex system based on the use of its computer model. Simulation, as a component of computer modeling, allows you to construct most of the possible states of the analyzed system. In this way it allows to correct the processes of assembling machines in a minimum time and with minimal costs, to foresee possible risks and to avoid unreasonable decisions regarding the organization of processes, to reduce material costs. Simulation gives the best results for modeling uncertain or probabilistic systems. Simulation, as a component of computer modeling, gives the best results for modeling systems with uncertainty or with a probabilistic nature. Mathematically calculating all possible variants of the system’s behavior is a laborious task, and using average values in the calculations gives inaccurate results. For assembly production systems, simulation modeling is used to select the optimal production organization parameters. The aim of this work is to build a computer simulation model that allows you to evaluate the impact of production factors (number of employees, operating parameters and type of assembly process) on the assembly process and substantiate the effectiveness of the model. The current assembly process of the machine was considered for modeling. The assembly process includes: two streams of verification, synchronization of request from these two streams, and a machine collection stream. The vacated line starts servicing the application that entered the system earlier than others. Such a discipline is called “earlier entered - earlier served” (FIFO - First In - First Out).s from flows, and a machine assembly flow. An optimization experiment was carried out after the construction and verification of the simulation model. The maximum value of profit was chosen as the objective function. Iterations were performed during an optimization experiment. The optimal number of employees was selected for two inspection flows and a machine assembly stream in the assembly shop. The first experimental result showed the effectiveness of the request flow synchronization method. The following optimization experiment showed the relationship between the number of workers in certain threads of the assembly process and profit. The results of using agent-based models for simulation can be used to optimize assembly processes.
Application of computer agent modeling for optimization of the assembly process
