Artificial Intelligence for Computer-Aided Design

本研究项目的总体目标是将人工智能(AI)方法论应用于计算机辅助设计(CAD)。在计算机辅助工程设计领域，人工智能技术有望实现两个重要的技术目标：1.生产CAD软件，使半熟练的非专业人员能够产生良好的候选设计，从而极大地加速新技术的传播和吸收。2.通过计算机辅助设计软件“发现”人类专家没有构思的新设计和设计方法的可能性。在过去的十年里，PI和他的同事开发了两个CAD程序包CONSYD和POLYRED，目前正被工业界和大学用作教学工具。CONSYD允许有经验的用户从数据中交互地建立过程模型，通过过程模拟确定主要的控制问题，并使用各种复杂的设计程序来综合几个可在工厂测试中评估的控制系统的候选设计。目前CONSYD(和其他用于控制系统设计的CAD程序包)的局限性是，设计程序要求用户对每种设计方法背后的控制理论有相对复杂的知识。同样，POLYRED可用于设计聚合反应器，并要求用户具备设计、聚合和反应工程方面的专业知识。为了克服可以使用这些CAD包的人群中的一些限制，PI建议设计人工智能策略，允许工业中的普通控制工程师使用CONSYD，以及参与聚合反应器建模和设计的典型工业科学家和工程师使用POLYRED。第一步是创建一个控制系统设计专家系统，该系统将位于CONSYD之上，并调用CONSYD和POLYRED程序包中的相应FORTRAN程序以进行详细的技术计算。该项目的第二部分将涉及“发现”和“学习”功能的研究，这些功能可以添加到人工智能设计包中。对于控制系统设计问题，有两种类型的“学习”将被研究：1.发现具有固定规则的专家系统的应用可能产生的新的、以前未知的控制系统设计类型。2.根据AI包积累的经验制定新的设计规则。类似的学习功能将被整合到聚合反应器系统中。其结果不仅将是针对这两个特定领域的新软件，而且还将增加使用人工智能技术和专家系统解决重大、真实问题的知识库。

The overall goal of this research project is to apply artificial intelligence (AI) methodology to computer aided design (CAD). In the area of computer-aided engineering design, AI techniques hold the promise of achieving two significant technical goals: 1. The production of CAD software which allows semi-skilled non-specialists to produce good candidate designs so as to dramatically hasten the dissemination and assimilation of new technology. 2. The possibility of "discovery" by CAD software of new designs and design methods not conceived by human experts. Over the past decade, the PI and his coworkers have developed two CAD packages CONSYD and POLYRED presently in use by industry as well as by universities as teaching tools. CONSYD allows the experienced user to interactively build a process model from data, determine the principal control problems through process simulation, and use a wide variety of sophisticated design procedures to synthesize several candidate designs of control systems which can be evaluated in plant testing. The current limitation of CONSYD (and other CAD packages for control system design) is that the design procedures require the user to have a relatively sophisticated knowledge of the control theory behind each design method. Similarly POLYRED can be used to design polymerization reactors and requires expertise in design, polymerization and reaction engineering on the part of the user. To overcome some of these limitations on the population that can use these CAD packages, the PI proposes to devise AI strategies which will allow the average control engineer in industry to use CONSYD and the typical industrial scientist and engineer involved in polymerization reactor modelling and design to use POLYRED. The first step will be to create an expert system for control system design which will sit above CONSYD and call the appropriate FORTRAN programs in the CONSYD and POLYRED packages for detailed technical calculations. The second part of the project will involve the study of "discovery" and "learning" features which could be added to the AI design package. For the control systems design problem there are two types of "learning" which will be studied: 1. The discovery of new, previously unknown, types of control system designs which may arise from the application of expert systems with fixed rules. 2. The formulation of new design rules based on the accumulated experience of the AI package. Similar learning features will be incorporated into the polymerization reactor system. The results will not only be new software for these two specific areas, but will also increase the knowledge base on the use of AI techniques and expert systems to nontrivial, real problems.