Layout Optimization Design Of Mining Excavator Control Room Based On Genetic Algorithm

As a more important link in the field of intelligent manufacturing,the layout optimization problem has a great influence on the final product presentation and operation efficiency.Especially for complex mechanical equipment,the layout of each component will have a great impact on the operating efficiency of the equipment:on the one hand,it can improve the speed and accuracy of the equipment design process,on the other hand,it will improve the comfort of the operator,This indirectly improves the production efficiency of the equipment.Therefore,the in-depth study of the product layout problem method can improve the design and manufacturing capacity of the country’s large-scale equipment.The main research work is as follows:(1)Starting from the layout problem,analyze the current situation,methods and methods of the layout problem and review the literature,so as to clarify the solution to the layout optimization and the advantages and disadvantages and focus of the related methods.Use the characteristics of layout methods to select directions for complex layout problems and optimize solutions in depth.(2)According to the layout of complex mechanical equipment and the operation characteristics of genetic algorithm,the idea of algorithm optimization combined with modular design thinking is proposed:by dividing the space to be distributed into modules,the layout modules of different levels are divided,and at the same time Differentiate the content of modules with different degrees of complexity in the way of division.The component hierarchy tree is divided by fuzzy clustering analysis,so that the equipment components of complex modules have sufficient functional correlation,and multiple modules that meet the layout requirements are obtained.(3)Use the relevant theoretical principles of ergonomics to establish a constraint function on the values of the field of view and the accessibility of the sitting posture that have an impact on the spatial layout;use the AHP to process the data of the frequency of component use,and distinguish the layout of each component.level,and further establish constraints;set overlapping coefficients between modules to ensure that the optimization iterative process takes into account the collision in the active space.(4)Through the algorithm output solution set,manual screening is carried out to obtain the preliminary scheme optimization set.In order to verify the availability of the solution set points,a spatial simulation is performed using modeling software such as Rhino.The fuzzy comprehensive evaluation method based on expert scoring data to sort the center of gravity can verify the feasibility of the optimized centralized scheme,and can achieve further design refinement.(5)Verification Through the process optimization of the modular genetic algorithm,compared with the operation efficiency of the basic genetic algorithm,the operation efficiency and the establishment of constraints have both improved numerically.