[ Instrument Network Instrument Development ] Recently, researchers from the Shenyang Institute of Automation of the Chinese Academy of Sciences proposed a general modeling and comprehensive optimization method for flexible assembly shop simulation, which can realize the optimization of the whole production process and production resource allocation. The latest issue of the International Journal of Simulation Modelling.
In the face of a new round of industrial revolution, all countries will develop smart manufacturing as the key to building a competitive advantage in manufacturing. An important feature of intelligent manufacturing is the realization of customized production through a flexible reconfigurable production system. The modeling and simulation optimization method is the basis for constructing a flexible reconfigurable production system.
For the complexity and limitation of solving the assembly shop performance optimization for mathematical models and intelligent algorithms, the scientific research personnel of Shenyang Automation Institute's intelligent production line and system research laboratory adopted an optimization method based on discrete event simulation (DES) and intelligent algorithm. A general logistics simulation modeling method for DES is proposed. The logistics process of all stations in the discrete workshop is described in a unified way, and the production model of the discrete workshop is quickly established to provide an efficient modeling method for complex discrete workshop production simulation. By using improved genetic algorithm and multi-factor experiment to optimize production process, facility layout and production configuration, the optimal layout scheme and optimal equipment configuration, staffing, temporary storage area configuration and logistics vehicle configuration were obtained.
This method has been successfully applied to multiple intelligent workshop planning projects and has achieved remarkable results. The Intelligent Production Line and Systems Research Laboratory will continue to conduct in-depth research on shop floor intelligence, dynamic configuration and self-optimization.

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