Application Of Big Data In A Liquid Chrystal Display(LCD) Company A Data

Company A has been in liquid crystal display(LCD)business for more than 20 years.In the recent years,the LCD industry has bloomed significantly.Besides traditional LCD,the new star product,organic electroluminescent display(OLED),and the future product,flexible display,attract large investments,and the industry quickly expends.Facing tremendous competition,Company A needs to increase production efficiency to alleviate the cost pressure.Therefore,Company A resource to exemplary management and innovative manufacturing.From "Made in China" to "Smartly Made in China",the 18 th National Congress of the Communist Party of China urged a new industrial model that is a fusion of informational and industrial concepts and a remedy for Company A.The key technology for this fusion model is the "big data," which provides strong informational support for manufacture industry.Moreover,industrial big data are essential to manage intelligent manufacturing.After analyzing how big data application in the domestic and global LCD industries,the author proposed an information operation model for Company A to promote product quality/quantity,delivery rate,and operation efficiency.The model is divided to three layers.Layer 1(operation);collecting data through both wireless and wired devices and directly analyzing the date with software to locate the root of a problem.This layer mainly deals with quality/quantity and efficiency issues.Layer 2(control):analyzing big data to find the correlations.Multivariate statistical analysis was used to establish a dynamic management model to deal with variability and uncertainty,promote productivity,and optimize procedures.Layer 3(planning):Following business management strategy,decision making big data are used to timely allocate resources,optimize organization,monitor and anticipate risks to reach company target Under this three-layered-model,the first-line operators make adjustments and modifications based on data instead of relying on experience of senior employee.With the data,manager can make effective policy and efficient improvement,and decision maker can set company goal and allocate resources to increase manufacturing efficiency,elevate product quality,raise product delivery rate,and improve production efficacy.This work is an educational guide for related industry.