COMPUTER AIDED PRODUCTION CONTROL

Computer-aided flow-simulation programs are also available for dies. All the programs can successfully predict a certain amount of shrinkage under specific conditions that can be applied to experience. The actual shrinkage is finally determined after molding or extruding the products. When not in spec process control changes can meet the requirements unless some drastic error had been included in the analysis. 

The correct interpretation of measured process data is essential for the satisfactory execution of many computer-aided, intelligent decision support systems that modern processing plants require. In supervisory control, detection and diagnosis of faults, adaptive control, product quality control, and recovery from large operational deviations, determining the mapping from process trends to operational conditions is the pivotal task. Plant operators skilled in the extraction of real-time patterns of process data and the identification of distinguishing features in process trends, can form a mental model on the operational status and its anticipated evolution in time. 

Any on-line process control model used for computer-aided manufacturing of high-performance composite laminates must include a thorough treatment of void stability and growth as well as resin transport. These two key components, along with a heat transfer model and additional chemorheological information on kinetics and material properties, should permit optimized production of void-free, controlled-thickness parts. A number of advances have been made toward this goal. 

A series of computer aids for the control of polymer processing will be discussed, emphasizing the practical aspects of choosing the proper tool for the application. Where possible, examples of production, or at least developmental experience, will be included. Because there are a variety of processes used in polymer processing, the advantages and disadvantages of each method will be discussed in the context of the types of processes. 

The first persons to point out the possibility of computer monitoring of indirectly measured parameters were Yamashito, Hisashi, and Inagaki in 1969 (2). The method was described in a U.S. Patent in 1975 (3). Examples of the application of computer-aided indirectly measured parameters to the control and optimization of batch-fed Baker s Yeast fermentation were described by Jefferis and Humphrey in 1973 (4) and by Wang, Cooney, and Wang in 1977 (5). Background and detailed history of this application can be found in the review by Humphrey (1). The work to be discussed in this report is another example of computer-aided indirectly measured cell biomass and growth rate and the use of this information in the feed back control of the carbon substrate, ethanol, in a process for the production of a yeast single cell protein (SCP). 

Guided by the quality plan, the computer-aided quality inspection and quality data collection receive quality data during different phases. The phases include purchased-mateiial and part-quality inspection, part-production-quality data collection, and final-assembly quality inspection. The methods and techniques used in quality inspection and data collection are discussed in special books on quality control (Taguchi et al. 1990). 

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