Reconfigurable Low Entropy Layout Modeling And Optimization For Intelligent Workshop

With the development of globalization,the competition among enterprises has been increasingly fierce,customer orders have become more volatile,and the demand of customized service is keeping growing.The company's production process has become increasingly diverse and highly variable in terms of production planning,equipment technology,etc.The demand for flexibility,robustness,and low entropy in the layout of the shop floor has gradually increased.In recent years,more and more intelligent workshops have been put into production as a result of the development of new technologies and the concept of Industry 4.0.The reconfigurable and low-entropy intelligent workshop layout enables the smart workshop to have features like low-carbon energy saving and high flexibility,which help the company respond to the diversification of product demand without expanding the area of the shop floor.Therefore,studying the reconfigurable low entropy intelligent shop floor layout has a good theoretical significance and important practical value.The paper aims at the layout of smart workshops,the unit layout was adopted,different layout requirements within and between cells were taken into consideration,a reconfigurable low entropy intelligent shop layout model was constructed,and a double-level genetic cell algorithm was designed,finally applied the research results to practical projects to verify the feasibility and effectiveness of the results.The main contents of this thesis are as follows:1.Based on the theory of physical entropy and low entropy,the evaluation index of the workshop layout entropy was deduced,and the basic principle and implementation approach of the low entropy of the workshop layout were proposed.2.To construct the reconfigurable and low-entropy intelligent workshop,unit layout method was used,layout models of within and between cells were established according to the diverse characteristics of these two types of unit layout.Designed a multi-objective function for low-entropy workshop layout consisting of material handling cost,time lost cost,unit reconfiguration cost,equipment cost,workshop area utilization,and layout flexibility.The quantitative constraints including the boundary constraints,spacing constraints,fixed position constraints are given in accordance with the actual conditions of the workshop.3.According to the multi-constraint,multi-variable and non-linear characteristics for the workshop layout model,a double-level genetic cell algorithm was proposed,and the algorithm processes and key technologies including initial population generation based on elite strategy,the design of adaptive crossover and mutation probability were designed in detail.Validated the effectiveness of the algorithm through examples.4.The layout simulation model and framework for reconfigurable low-entropy intelligent workshops was established to complete the simulation interface and program design.5.The layout of S company was analysed and a layout optimization scheme was given,which was compared with the current status of the workshop layout and the SLP scheme to verify the feasibility and effectiveness of the model and the algorithm.6.The thesis aims at reconfigurable and low-entropy intelligent workshops,using layered ideas to construct a reconfigurable and low-entropy intelligent workshop layout model and design the corresponding solving algorithm,which can provide an effective analysis method and tools for workshop layout planners.