Research On Intelligent Production Scheduling For Personalized Customization

The rapid development of advanced intelligent manufacturing technology and the increasing demand for personalized customization have pushed manufacturing companies to adopt personalized customization models for rapid production to meet the diverse and smallbatch customization needs of consumers.The cost and delivery time of customized products are the primary challenges faced by personalized customized production enterprises.Production scheduling technology is the key for personalized customized enterprises to achieve low-cost and high-efficiency production to quickly respond to the market.In view of the problem that the traditional scheduling method is no longer suitable for the new characteristics of the personalized customized production mode,it is urgent to propose a new scheduling method to adapt to the dynamically changing personalized customized production environment.Therefore,the study of scheduling problems and optimized scheduling methods under personalized customized production methods is of great significance for guiding enterprises to efficiently control production and realize intelligent production scheduling.To this end,the following research work has been carried out in this paper:1.In order to better describe,model and analyze the scheduling problem,first summarize the main characteristics and production conditions of personalized customized production methods,and then determine the characteristics of personalized customized production scheduling under the background of intelligent manufacturing and the key technologies for solution.2.Describe and model the dynamic scheduling problems of personalized customization in discrete smart workshops with process path determination and uncertainty,and design dynamic smart scheduling strategies that optimize production scheduling to consider process path deterministic and stochastic production conditions The scheduling strategies is designed to prepare for a more superior scheduling algorithm and disturbance handling mechanism.3.Aiming at the new characteristics of the personalized customization scheduling problem,an improved genetic algorithm is designed to solve the dynamic scheduling problems of process path determination and randomization.At the same time,considering the situation that multiple Parato optimal solution sets are obtained when solving the random scheduling problem of the process path under multi-objective constraints,an evaluation method based on combination weighting and improved approach to ideal solution sorting is used to screen the obtained Parato optimal solution set to obtain the optimal scheduling plan.4.Using production scheduling examples to solve the scheduling model and simulation experiments,through the analysis of the results,it is verified that the optimized scheduling method designed in this paper has the characteristics of more sensitive and real-time effective scheduling,and the rationality of the scheduling model established in this paper.