An ARIMA Decision Support Model Based On PLM And Its Application

With the transformation and upgrading of economic society,the competition of manufacturing enterprises is intensified,the enterprises need to be refined and standardized in the aspects of production planning,raw material purchase and product sales.They need real-time monitoring the change of product design,manufacturing,assembly,in store,out store,sales,returns and services and other aspects.With the past data of production for the sample and basis to predict the enterprise product production,sales and other processes in the next period.Provide data support for enterprises to make procurement plans,production plans and other strategic decision-making.This paper first analyzes the importance of decision support in the PLM process of enterprise and the influence of data predict on enterprise decision,Taking the past production data as the research object.Research the model build and application of data prediction to resolve how to obtain effective forecast data and show to the decision maker in a friendly and beautiful way.The specific research contents are as follows: Firstly,the data learning prediction model based on ARIMA is constructed.The model is verified by residual test,and the model is optimized by variance check and T check.Then,using methods combination of R language and Java-based JSP,Servlet and JavaBean technology and rJava to achieve resolve early warning model and test and optimization the model;Next,build the decision support system based on the browser / server structure to provide support for enterprise decision-making and adjust the prediction model based on the changing production conditions in the same time;Finally,build a web-based applications with the decision support system to make that decision-makers can be timely and intuitive understanding of real-time production of enterprises.