Research On Intelligent Management Of Manufacturing Process Quality In Company D

As one of the important factors affecting the core competitiveness of manufacturing enterprises,quality not only affects the production cost of products,but also profoundly affects the reputation of enterprises and the further occupation of the market by enterprises.For enterprises,in order to achieve full-cycle quality control of products,not only the quality planning in the early stage of product design,but also the quality control in the manufacturing process is the top priority.In the intelligent production process,there are many production influencing factors,large quality data,fast update speed.traditional quality management methods can not achieve real-time collection,monitoring and analysis of process quality data,in the context of the continuous implementation of big data and industrial interconnection,traditional quality management can no longer match the intelligent production process.Intelligent management mode and tools are applied to quality management,and the quality data of product manufacturing process is mined and analyzed through intelligent equipment to achieve early warning and identification of quality risks,which is of great significance for improving product quality and reducing enterprise costs.Taking the quality management of the manufacturing process of Company D as the research object,it was found that the quality of the manufacturing process of Company D was manifested as unstable product quality,high manufacturing quality cost and low customer satisfaction through on-site investigation and other methods.Through questionnaire survey,manager interview and other methods,it is found that the quality management problems of Company D’s manufacturing process are mainly reflected in the frequent occurrence of equipment management,frequent quality problems affected by human factors of operators,untimely handling of quality problems,and difficulty in tracing quality data,etc.,and the key reasons for the diagnosis of problems by using 5M1 E fishbone analysis method come from low hardware automation,low software version,and irregular logistics equipment and technological flow.Through reading relevant literature and their own work practices and experiences,suggestions for using intelligent management methods to promote quality management are put forward: first,intelligent management ensures the stable work of equipment,combines automation and intelligent technology to improve hardware,monitors equipment status,automatically reminds equipment maintenance and detects equipment interconnection;Second,intelligent management reduces the impact of human factors on the quality level,and replaces manual,continuous flow production,automatic material transfer,and the use of pull systems through automation;Third,intelligent management improves the timeliness of quality data retrieval,and collects operator data,equipment parameter data,and parts process quality data through collation;Fourth,intelligent management improves the efficiency of quality problem handling,through the use of project management tools,database establishment,quality problem visualization and software version upgrade.So as to improve product quality as a whole,reduce production quality costs and increase customer satisfaction.The purpose of the research is to optimize the current manufacturing process quality management mode in the manufacturing industry,using intelligent manufacturing and digital technology,combined with the current situation of Company D,to prove that intelligent management is effectively applied to the quality optimization of manufacturing enterprises,so as to improve product quality stability,reduce production costs,and improve customer satisfaction.Through continuous practice,Company D has explored a set of theories and methods of intelligent manufacturing process quality management,which have certain economic and social benefits,and also hope to provide some reference and reference for the same type of manufacturing enterprises.