Model Study And Application System Design Of Heat Setting Process

Dyeing and finishing is the last link in the fabric production, but also the key aspects of determining quality of textile products. However in a long time,during drying and heat-setting process most dyeing and finishing enterprises set the production parameters relying on the experience accumulated in the past product, according to the off-line measured values to carry on exploration production. Over time, high energy consumption, low passing rates, varying qualities among the same batch of products becomes thorny issues for companies. To solve these problems, this article analyzes the principle of fabric drying process, then establishes a fabric moisture prediction model; basing on the theory of heat setting mechanism and producing data collected in the enterprise workshop, establishes quality indicators prediction models, and design optimization algorithms on the basis of these prediction models to get optimal heat setting production parameters.The main researches are listed as follows:(1) Establishing fabric moisture prediction model. On the basis of analysis of fabric drying principle, respectively, the article uses the least squares method and least squares support vector machine to build fabric moisture prediction model.(2) Establishing heat setting quality indicators prediction models. On the basis of analysis of fabric heat-setting mechanism and production data collected in the workshop, the article establishes heat setting quality indicators including width and gram weight prediction models.(3) Designing process parameters optimization model. Basing on heat setting quality index prediction model, taking width, gram weight and customer requirements error minimum as objective functions, the article establishes process parameters optimization model, and designs optimization algorithm to obtain the optimal process parameters.(4) Introducing quality index prediction model correction methods. Through calibration the article applies heat setting quality index prediction models to multiple type of fabric, gives model correction method and effectiveness verification results.(5) Designing and developing heat setting parameter computer-aided design system. The heat setting quality indicators prediction, process parameter optimization design, and process parameters quantitatively solve is achieved on the Visual Studio 2008 platform, and data are stored in Access database.Researches of this article can provide effective reference for dyeing heat setting production quality assurance and process parameters formulation, and all of these are important for improving products pass rates and reducing energy consumption.