Research And Design Of The Garment Manufacturing Data Collaboration And Auxiliary Decision-making System

With the new round of advancement featuring informatization in the garment industry,the garment enterprises strive to achieve informatization, intelligentization and digitization.China’s garment enterprises are mostly labor-intensive, and the low degree of automationbrings a certain degree of difficulty to the realization of informatization in the garmentindustry. Meanwhile, the business process of the garment enterprises are complicated andarduous. Generally speaking, many garment enterprises need to deal with thousands kindsof inventory raw materials, auxiliary accessories, products and so on; at the same time,data of a multitude of styles, structures and customer identifications need to be managed.Itis a hot-spot issue in the current garment industry to research into the ways to achieve datacollaboration in the garment manufacturing process and dig out the means to conductingauxiliary decision-making more sensibly and reasonably in intelligentized construction.On the basis of the acquisition of the extensive theoretical knowledge of datacollaboration and auxiliary decision-making, the researcher conducts in-depth and effectualresearches and analysis in the garment industry, and proposes a solution, aiming improvinginformation application condition and meeting development requirements. In terms of datacollaboration, the researcher attempts to materialize the data integration and sharing of theexistent customer database, material database, template database, and workmanshipdatabase thorough the construction of style database, so as to further realize the dynamiccollaboration of the garment manufacturing data.In terms of the working hours in the manufacturing process, based on the existingGSD (General Sewing Data) system, the researcher analyzes the differences between theactual working hours and standard working hours of the employees, upon which a datawarehouse is built. First and foremost, the researcher classifies the data by using themethod of decision tree, and then the researcher makes a detailed data mining of each kind of data thorough correlation analysis, attempting to make an analysis of the impact thatstyle, material, seniority have made upon the differences between actual working hours andstandard working hours. Last but not least, the researcher optimizes original standardworking hours so as to achieve the purpose of supporting decision-making process,improving the rationality of standard working hours and providing an insightful solution tothe construction of informatization and intelligentization in the garment enterprises.