Research On Production Quality Management Method Of Flexible Machining Workshop In Ship Supporting Enterprise

The products processed by the discrete machining workshop have high degree of individualization and small batch production.According to the process requirements,the production is organized by setting up manufacturing units.Due to the large changes of parts and frequent changes of the process,the unstable phenomenon of the processing quality is very serious,which affects the efficiency of the whole production.Therefore,the production characteristics of this kind of machining workshop put forward more strict requirements for the quality management of the manufacturing process.Especially,under the development trend of intelligent manufacturing,how to realize digital quality management,so as to carry out effective quality management of the product production process will be an important problem to be solved urgently for this kind of enterprises.At present,the quality management of such enterprises relies heavily on paper-based program documents and the technology and experience of operators,which is quite arbitrary in the implementation process.At the same time,the current quality management system only has data collection,record,query and other functions.Therefore,how to deeply integrate the program requirements of quality system documents with the information system on site and convert the program requirements of system documents into effective process management behavior can effectively reduce the arbitrariness of process quality management and improve the accuracy of quality management.Based on M shipping enterprise quality management standards,on the basis of typical flexible machining shop to shipping industry as the research object,this paper proposes a forecast,control,detection of digital quality management method,the effective management of the process quality so as to reduce fraction defective products,and further guarantee product quality,the purpose of the research contents are mainly the following several aspects.Firstly,according to the characteristics of shipbuilding industry and the quality management standard of M shipbuilding enterprise,a kind of quality management framework and process of FMCS is established,and a new quality management method and strategy,namely the quality process management method based on rule base,is put forward.This method converts the semantic terms of the quality system into corresponding management policies or management rules to form a rule base.The management strategy of the rule base and the interface formed by rules are integrated with other information systems,such as MES and QMS,etc.Quality operations in the information system will be verified by the rule base,and then the follow-up actions will be carried out according to the requirements of rules and policies,so as to deeply integrate the requirements of the quality system files with the actual behavior management.Transforming semantic clauses into concrete quality management behaviors.Secondly,around the quality management framework and processes,in terms of quality prediction,this paper proposes a process quality prediction model based on improved BP network,the design of a dynamic learning rate adaptive adjustment,realize the resource combination process of a single working procedure quality forecast,provide data support for subsequent scheduling production scheduling,and then achieve the goal of quality control.Thirdly,in the aspect of quality control,quality problems considering the scheduling during,proposed scheduling model is given priority to with quality,delivery time,cost,work order prediction quality as the optimization goal set up a multiple resource scheduling based on the quality prediction model,and by introducing a mapping rule,an improved whale optimization algorithm to solve the combinatorial optimization model.Fourthly,in the aspect of quality inspection,a detection model based on improved differential clustering GA-BP network is proposed,which can realize product quality inspection more accurately and quickly.In the GA-BP network model,a combinatorial selection operator,a crossover operator and a combinatorial selection method close to the superior individual are designed to make the network obtain better initial parameters,such as the number of nodes in the hidden layer,each threshold value and weight value.On this basis,a clustering number determination strategy based on the minimum fitness value was designed,and an improved differential clustering algorithm containing adaptive crossover and mutation operators was proposed to effectively improve the learning rate and prediction accuracy.Finally,the production operation process of the flexible machining shop in the workshop of M Marine enterprise is taken as an example to verify the feasibility and superiority of the key technology methods,which has a guiding significance for the quality management of the actual production workshop.