Modeling And Optimization Of Production Scheduling In Wafer Fabrication Shop

Affected by the COVID-19 and global trade protectionism,China urgently needs to improve the chip self-sufficiency rate.Wafer manufacturing is the most difficult and valuable link in semiconductor chip manufacturing.Its production efficiency has become an urgent problem in the semiconductor industry.Production scheduling is the core of enterprise production management.However,due to the particularity and complexity of wafer manufacturing products.Its production scheduling problem is different from other workshops.Therefore,it is very important to build a scheduling problem model that conforms to the dynamic and complex environment of the wafer manufacturing workshop and improve the overall production efficiency.Based on the above research background and the characteristics of the wafer manufacturing workshop,this paper constructs a multi-objective production scheduling model for the wafer manufacturing workshop,solves it by improving the genetic algorithm,and optimizes the multi-objective weight,which is verified by an example.Firstly,according to the characteristics of wafer manufacturing production,four performance indicators,wafer card waiting time,equipment load time,wafer card processing time and equipment repair time,are determined as the objectives of scheduling optimization.A multi-objective model is established.Genetic algorithm is improved to solve the optimal scheduling strategy.The optimal scheduling scheme is obtained.The simulation results show that,compared with the existing algorithms in other litterateurs,the algorithm in this paper has faster solving speed and better results.Secondly,through the analysis,expansion and reorganization of other scholars’ fuzzy rule base,a new rule base is obtained.T-S fuzzy logic reasoning is constructed,and the weight adjustment model based on fuzzy logic is established.The weights of the four indicators of the objective function are dynamically adjusted.The production scheduling of wafer manufacturing is optimized with the improved genetic algorithm.40 groups of rules in the extended fuzzy rule base are randomly selected by simulation data for simulation analysis,and the mean and standard deviation of the four optimization objectives in this case are obtained.By analyzing the result data,it is verified that a group of rules in the expanded rule base is superior to the original rules,and then the optimal rule group is obtained.Finally,under the optimal rules,the case of wafer manufacturing enterprises is simulated based on fuzzy weight genetic algorithm.Comparison with other improved genetic algorithms in different wafer sizes.The results show that the genetic algorithm based on fuzzy weight has faster solving speed and better results in different wafer sizes.At the same time,the algorithm is used to solve the three optimal scheduling schemes and the optimal capacity of the wafer box A,B,C.The wafer manufacturing workshop production scheduling model and optimization method constructed in this paper have practical reference significance for enterprises to enhance overall competitiveness and improve market share.