The Order Prediction Research For Textile Machinery Industry Based On Customer Requirements

With the rapid development of science and technology, a diversified andsegmented trend of meeting consumers’ demand is showing up, manufacturersgradually transformed into many varieties of small batch production. In the conditionof meeting the diverse needs of customers’,textile enterprises are facting theenormous challenges of reducing production costs, reducing waste and improvingtextile product qualities,we take orders as the reflector of customer’s demands andbusiness life, in the complicated market environment, making accurate orders’predictions can effectively solve these problems.With the development of information technology, through the use of informationmanagement systems, textile machinery manufacturing enterprises stored a lot ofsales order history datas in the database. Based on the company’s sales data, thispaper analysised the changed characteristics and influenced factors of curtomers’sdemand, which is the research tangent point of history order datas, so we canestablish the orders’s pridicted models. The main contents are as follows:(1) Introducted the textile manufacturing industry’s background and products’features, and described the knowledge and the status of research related to customers’demands and orders’ forecasts in detail, also pointed out the lack of commonly orderpredicted method, proposed orders forecasting model to customers’ demand for theestablishment of textile enterprises.(2) Described the dialectical relationship between customers’ needs and orders,on the basis of the completed specification of historical sales data in the textileindustry, the importance of customers’ needs for order forecast was analysised, andthe way that traditional time-series forecasting methods transformed to customers’demand forecasting methods was proposed.(3) Based on the real-time sales data, and combined with the characteristics ofthe textile machinery market analysis of changes in customers’ needs, proposed therelevant fuzzy factors customers’ needs, build a new time series decomposedforecasting method on the basis of fuzzy affecting factors of customers’ demands, andthe model forecasting methods and the principles used in this paper were described.At the same time, the actual end customer orders were analyzed on the basis of comparative analysis, and the order forecasting methods’ evaluation was alsoproposed.(4) With the specific textile enterprises, we should make the order forecastingmodel for software development and verification. And I have analysised the needsand goals of textile enterprises’ order management and forecast system, researchedthe systems’ framework and developed environment, and based on the modelprinciple to design the functional structure, finally in the case of orders for textilemachinery business management and forecasting system instance applications,providing efficient and reliable production order information to carry out follow-upactivities.Finally, the full text summarizes the research contents, analyses the shortage ofthe subject of further research was forecasted.