A Study on Methodology of Production Line Control and Quality Assurance System under CIM Environment

由于CIM-计算机集成制造在工业中的快速引入，过程控制和质量保证所扮演的角色变得更加重要。这些系统成功实施的前提条件是控制数据的实时监控的发展和改进，本研究旨在开发支持这种实时监控的方法和工具。本研究取得的具体成果如下：1.基于定性仿真技术的应用，设计了一个框架，便于建立支持过程控制系统开发的模型库。这些系统能够实现实时过程控制和质量保证，以及预测生产系统的未来状态。该方法被测试并应用于一个实际的问题，以控制在光感鼓的生产中的涂层过程。这项测试导致了一种 关于我们 原型系统本研究仍未能完全达成研究计画中所提出的建立人机介面的目标，但所提出的方法透过允许以实际操作资料为基础的系统详细分析，证明其有效性.开发了一个原型系统作为真实的时间分析的质量信息的工具。该系统采用ARIMA模型对质量相关信息序列进行分析。该系统除了具有对需求信息序列进行预测的能力外，还可以根据现有的时控过程数据结构，方便地咨询和选择合适的分析方法.基于制造过程的真实的实时质量信息，基于最小描述语言（MDL-Minimum Description Language），建立了一种学习增量式的概念聚类方法。这种方法可以允许，在未来，用于识别缺陷及其发生模式的自动工具的建设。少

Due to the fast introduction of CIM-Computer Integrated Manufacturing in the industries, it is becoming even more important the role played by process control and quality assurance. The pre-condition for the successful implementation of these systems is the development and improvement of real-time monitoring of the control data.This research is aimed in the development of methods and tools to support this real-time monitoring. The concrete results obtained in this research is listed below:1. Design of a framework, which based on the application of qualitative simulation technique, facilitates the creation of model bases to support the development of process control systems. These systems enable the real-time process control and quality assurance, as well as forecasting of future status of the production systems. This methodology was tested and applied to an actual problem to control the coating process in the production of light sensing drums. This test resulted in the development of a … More prototype system. This study still not totally accomplishes the objective of building a man-machine interface as proposed in the research plan, but the proposed approach demonstrated its effectiveness through allowing detailed analysis of the system based on actual operating data.2. Development of a prototype system as a tool for real time analysis of the quality information. This system applies ARIMA model for analyzing sequence of quality related information. This system besides the capacity for forecasting the series of demand information, it also facilitates the consultation and selection of proper analytical methods considering the existing time-controlled process data structure.3. Based on the real time quality information about manufacturing process and on the MDL-Minimum Description Language a learning incremental concept clustering method is built. This method may allow, in the future, the construction of automatic tools for the identification of defects and the patterns of their occurrence. Less