Research On Optimization Of System Operation Efficiency Of I Company

In the recent years,the transformation and upgrading on various global industries is flourish,the direction of automation,digitization,intelligence also drives the rapid expansion of semiconductor manufactories.Due to increasingly strict chip testing rules put forward higher requirements to production efficiency of semiconductor manufactories.Seeking an optimal option to help improving equipment utilization and to lower down the cost per unit during production is a vital subject that has been exploring.AMHS(Automatic material handling system)be widely used and plays a very important role in semiconductor manufactories for its high stability and reliability,high degree of automation demonstrated during production environment and gradually became the first choice for wafer manufactories.I Company is a leading semiconductor enterprise with a full set of manufacturing processes for wafer design,production and manufacturing,AMHS system also been used as the core system for material storage and delivery in production and manufacturing in this company as well.As the person in charge of the operation and management of AMHS system in the Chengdu Branch of I Company,I have participated in AMHS system design,construction and expansion with many years of experience in system sustaining and system performance analysis.This paper takes Chengdu branch of I Company as example,points out the existing deficiencies affecting system capacity of material storage component and material transmission component in AMHS system through data analysis and deep diving into the cause of the deficiencies.In this paper,the efficiency optimization strategy of the material transmission component of AMHS system is modeled and formulated based on the theory of reinforcement learning according to the system performance index.With an optimized material storage component of AMHS system constructed at the same time,a set of highly integrated,reliable dynamic model system optimization strategy established.This paper uses a variety of tools to analyze the external macro environment of AMHS system operation,the advantages and disadvantages,opportunities and challenges of the strategies in detail,sorting out the core indicators and key processes that affect system production performance in AMHS system architecture from the aspects of physical layout,parameter configuration,interaction mechanism and production process.The dynamic model and optimization strategy discussed in this paper achieved comprehensive optimization across average waiting time of material moving,average handling time and relevant performance indexes.In addition,an optimized capacity prediction process for AMHS system expansion was developed based on the dynamic model.The theories and methods involved in this paper have been verified in the actual production environment.The verification results show that the optimization strategy and dynamic model adopted in this paper can effectively improve the production efficiency of AMHS system and reduce the production cost per unit.In addition,the strategy and model also can be inheriting by other branches of I Company in the design,the management theory and testing data involved in this paper helps optimized layout at the beginning of the design,better design on production capacity balance,more reliable dynamic model for AMHS system capacity expansion,also makes more reasonable for equipment procurement cycle control and forecast the rational distribution of funds in the first place.