Intelligent computer-aided-design systems: a synergical approach of artificial intelligénce and engineering

A synergism has begun to surface from the artificial intelligence (AI) and engineering communities: an effort to apply AI techniques to engineering problem-solving activities, and to study problems arisen from various engineering fields as a way to develop AI theories and methodologies. This paper first discusses the needs of such a synergical approach and identifies in a broad perspective some AI techniques currently being applied to engineering. It then describes a system, called KREATOR, which applies qualitative reasoning, a subfield of AI, to computer-aided design (CAD). The key observation is that an engineer designer's qualitative knowledge can offer a good basis for the reasoning of device behaviors. Such knowledge, however, is not captured by conventional CAD systems for lack of good representations. KREATOR is a knowledge capturing scheme that allows the designers to record their qualitative knowledge of how mechanical devices behave, KREATOR then automatically generates qualitative simulations.     

Integrated CAD development for building services engineering

The potential benefits of CAD in building design are well established. In reality most production CAD systems are developed in response to the particular requirements of users who are architects or building engineers. These requirements are often fragmented. They relate to different aspects of the complete building engineering design cycle and are often specified by different users at different moments in time. The role of the CAD systems developer is to design a coherent software system and to establish a consistent set of user interface conventions with which an integrated solution of these different requirements can be provided. This paper describes how this methodology has been successfully applied to an important aspect of CAD relating to building services engineering.     

Knowledge acquisition for fuzzy expert systems

Expert systems have been successfully applied to a wide variety of application domains. to achieve better performance, researchers have tried to employ fuzzy logic to the development of expert systems. However, as fuzzy rules and membership functions are difficult to define, most of the existing tools and environments for expert systems do not support fuzzy representation and reasoning. Thus, it is time-consuming to develop fuzzy expert systems. In this article we propose a new approach to elicit expertise and to generate knowledge bases for fuzzy expert systems. A knowledge acquisition system based upon the approach is also presented, which can help knowledge engineers to create, adjust, debug, and execute fuzzy expert systems. Some control techniques are employed in the knowledge acquisition system so that the concepts of fuzzy logic could be directly applied to conventional expert system shells; moreover, a graphic user interface is provided to facilitate the adjustment of membership functions and the display of outputs. the knowledge acquisition system has been integrated with a popular expert system shell, CLIPS, to offer a complete development environment for knowledge engineers. With the help of this environment, the development of fuzzy expert systems becomes much more convenient and efficient. © 1995 John Wiley & Sons, Inc.     

Structural shape optimization integrated with CAD environment

The research work presented here is based on the concept of the integration of optimization techniques and numerical analysis with the finite element method (FEM) and computer-aided design (CAD). A microcomputer aided optimum design system, MCADS, has been developed for general structures. Certain techniques to be discussed in the paper, e.g. the semi-analytical method for design sensitivity analysis, optimization analysis modelling for shape design, application oriented user interfaces and the coupling of automated optimization and user intervention have rendered MCADS pratical and versatile in applications for engineering structures. The above techniques and an application are presented in this paper.     

Artificial intelligence in Computer Aided Design

The combination of Artificial Intelligence (AI) and Computer Aided Design is a trend in computer aided techniques. In this paper, we discuss some AI techniques used in special CAD systems developed at Zhangjiang University. First, an expert system used in art pattern CAD is presented. Accessing the knowledge bases, the expert system reasons to produce various kinds of pseudo-3D art patterns which can be used for textile such as cotton, silk, and carpet. We shall focus on its knowledge representation and fuzzy reasoning mechanism. In the second part of the paper, a geometric modelling system for architectural CAD is described; and in particular, a method to construct the hierarchical geometry model of complex scene environment is introduced. The method is based on the clustering technique of Pattern Recognition. The geometric modelling system can build the hierarchical 3D geometric model automatically and the efficiency of the system is obviously improved with the method.     

为支持协同设计对EDBMS的扩充及其实现

计算机支持下的协同设计是ＣＡＤ／ＣＡＭ技术的进一步发展。设计过程中有效的数据共享是协同设计的前提条件；而协同设计过程中用于交流、协调、决策等数据和知识的管理是协同设计系统的成功的基本保证。本文在工程数据库管理系统ＥＤＢＭＳ的基础上，根据协同设计的要求，对ＥＤＢＭＳ进行了扩充，使其在数据共享的基础上，能对用于协同的数据和知识等进行有效管理。为此对ＥＤＢＭＳ增加了支持开放分布式计算，以及多用户、多库处     

On commercial expert systems projects

The development process of expert systems obeys to rules, which have no counterparts in traditional software engineering techniques. To a certain extent they even contradict them.

AI engineers in charge of the realization of industrial expert systems must be aware of this situation and be prepared to respond to it by providing technology transfer. As long as this transfer to the customers has not happened, commercial expert system projects will lead to frustration and compromises hampering the achievement of the economic objectives set to the projects. For the time being technology transfer must be a major task of AI companies.     

反求工程CAD建模技术研究

将设计思想或实物原型迅速、直接、精确地转变为可以再加工的CAD模型,是产品创新设计和快速原型制造面临的关键技术,综合国内外反求工程CAD建模的研究和应用现状,分析了反求工程CAD建模问题的特点和需要进一步解决的主要问题,讨论了目前工程界普遍采用的反求工程CAD建模技术与思路,以及作者在解决这一系列问题中取得的进展情况。     

智能化的产品设计环境

随着计算机全面引入到产品设计全过程中，形成了计算机化的产品设计环境。本文深入分析产品设计过程中各种活动的演变规律及其信息处理方法，基于产品设计过程的进行模型理论，提出了智能化的产品设计环境ＩＩＩＰＤＥ的总体构思，分析了系统结构和信息流程。该系统具有较强的适应性，对分布式协同设计环境的构架也有适用性。本文最后总结了智能化产品设计环境中涉及到的关键技术环节和有待进一步研究的问题。     

Mechanical design methodology: Implications on future developments of Computer-Aided Design and Knowledge-Based Systems

The Current Computer-Aided Design (CAD) and Knowledge-Based Systems (KBS, expert systems) tools are changing mechanical engineering design. Future development and integration of these technologies is dependent on an understanding of the methodology of the mechanical design process, an area of little study and one that is poorly understood. This paper reports on the progress of an effort to understand how practicing engineers perform design. The approach is to record engineers' verbalization of their solution of carefully constructed design problems. The recordings are reduced to determine the intellectual tasks and problem-solving methods used. The results will determine what needed capabilities future intelligent CAD systems will need to aid design engineers.     

The role of the industrial engineer in developing expert systems

The most popular area of Artificial Intelligence application today is in expert systems. This paper contains a discussion of expert systems, otherwise known as knowledge-based systems and knowledge systems. The principal components of an expert system, and the evolution of expert systems are presented. The suitability of a task to an expert system is proposed. When a task is suitable for an expert system application, the system must be developed by a knowledge engineer. The methodology that the knowledge engineer must go through to develop an expert system is demostrated. Industrial engineers have formal training in many areas which can be useful when assumming the role of knowledge engineer. These areas of industrial engineering and how they are beneficial is discussed. What the future may hold in store is also pondered.     

圆柱齿轮减速器设计专家系统(CGREST)的开发

专家系统是一种计算机软件编制技术,主要用于模拟人类专家解决专门问题。本文介绍的圆柱齿轮减速器设计专家系统(简称OGREST)是利用人工智能、专家系统技术开发的一个实用型的设计专家系统,是国家“七五”规划重型机械基础件CAD的一个子项目。本文对专家系统技术在圆柱齿轮减速器设计中的应用理论和实用技术进行了探讨和研究。在设计思想、实现策略、知识采集、知识描述、知识运行、机械绘图以及在模拟人类设计专家的思维等诸方面,进行了新的尝试,并取得了令人满意的结果。     

ICADS: Intelligent Car Audio Design System for product planning

This paper describes the development of a system, ICADS (Intelligent Car Audio Design System), that can be used to effectively support product development engineers in car audio product design. We have demonstrated the use of expert system technology and the technique of quality function deployment (QFD) in supporting car audio design planning. QFD is applied as a knowledge acquisition method in this study to support car audio design teams in the development of products in a structured way that relates market demand via engineering specifications to parts specifications. We believe that other industries can use a similar approach for developing an expert system that can support product design planning.     

Automating manufacturability evaluation in CAD systems through expert systems approaches

Design for Manufacturability (DFM) represents a new awareness of the importance of product design as an integral part of manufacturing activities. Good design guidelines exist in industry for frequently used manufacturing processes. These guidelines are systematic statements of good design practices, empirically derived over years of design and manufacturing experience. Ensuring that the given product design conforms to each of the guidelines specific to the selected process results in better manufacturability. To meet the objectives of the DFM approach, design and manufacturing planning activities have to be combined into a single engineering effort and applied througout the life cycle of a product. Computer-aided design (CAD) systems offer powerful features such as the ability to develop complex solid models and perform engineering analyses, including stress analysis, interobject interference, collision detection, and inertial analysis. However, a prominent limitation faced by designers in CAD systems is the lack of “intelligence.” Though designs could be developed, analyzed, and perfected from a functional viewpoint in CAD systems, manufacturability consideration may get little or no attention at all. As a result, product designs that are functionally sound may be developed at a high manufacturing cost. Thus, intelligence should be incorporated in CAD systems, whereby product designs could not only be developed and analyzed but also evaluated for cost and manufacturability. This study attempts to perform this task automatically in a CAD system using a knowledge-based approach: the manufacturability criteria are considered for milling and drilling operations performed on a computerized numerically controlled (CNC) milling machine. The results obtained from the application of the expert system suggest that the expert systems methodology is a feasible method for implementing manufacturability evaluation capability in CAD systems.     

多种智能技术的集成与应用

当前,人工智能的研究主要分散在专家系统、模糊逻辑、神经网络、进化计算、机器学习与数据挖掘等多个领域。其中专家系统是应用最广的技术之一。但是经典的专家系统存在着“知识瓶颈”问题,严重阻遏专家系统的更深层次的应用。该文旨在运用其他智能技术和专家系统进行结合,构造一种可以进行自动知识获取和整理的新型专家系统,并进一步介绍该理论在笔者构造的基于力信息的运动员训练指导系统中的应用     

人工智能在选线领域的研究现状分析

由于计算机辅助设计在铁路公路选线设计这种多方案多目标决策工作中存在局限性,有必要在选线领域研究人工智能的应用。通过大量的文献检索,对遗传算法、知识工程和神经网络在选线领域的应用研究现状作了综述,在此基础上提出了综合利用地理信息系统、多Agent技术、工程数据库技术的知识工程路线,并阐述了该研究思路体系结构。     

Improved modelling and control of oil and gas transport facility operations using artificial intelligence

In recent years, the application of artificial intelligence (AI) based techniques to a wide range of industrial processes has become increasingly common. One reason for this development is the level of maturity of both theory of AI concepts and its implementation into application tools for commercial use. Another very important reason is the persistent drive of many industries to increase efficiencies and the realisation that this requires more effective processing of gained knowledge and information. In the oil and gas industry, due to high saturation levels of many production fields and the complex nature of processes, the need for increased efficiencies and highly effective processing of a large amount of information is particularly evident. Some organisations have recognised the opportunities offered by AI-based techniques and started exploiting them in order to improve knowledge and information handling and process efficiencies. This paper discusses the application of two AI-based techniques, fuzzy logic and artificial neural networks (ANNs), to specific problems related to the operation of oil and gas transport facilities. The background for the work, which is carried out in a co-operation between a university and a leading engineering service provider, is described firstly. This is followed by a brief summary of the fundamentals of the AI techniques considered with respect to their use for industrial purposes. Then, two case studies are presented. The first case study demonstrates the application of fuzzy logic to the control of a pump station in a pipeline system whilst the second case study shows the use of an ANN for the determination of important pipeline characteristics. Problem backgrounds, design procedures and outlines for the implementation of the used AI techniques are given. Finally, benefits of the adopted approaches are highlighted and the wider impact on both industry and research community is discussed.     

An intelligent decision support system for management of petroleum-contaminated sites

Groundwater and soil contamination resulted from LNAPLs (light nonaqueous phase liquids) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies have been developed and implemented in the last two decades. They are classified as ex-situ and in-situ remediation techniques. One of the problems associated with ex-situ remediation is the cost of operation. In recent years, in-situ techniques have acquired popularity. However, the selection of the optimal techniques is difficult and insufficient expertise in the process may result in large inflation of expenses. This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation. The results from some case studies indicate that the expert system can generate cost-effective remediation alternatives to assist decision-makers.     

A KBES for integrated engineering

The expert process of engineering involves application of knowledge fundamental to the engineering process at one end, and of compiled knowledge in the form of heuristics gained through many years of experience at the other. Developments in Artificial Intelligence have made the process of computer aided engineering richer by enabling the simulation of this human process of engineering, which until now has been difficult to capture. Knowledge Based Expert Systems (KBES) in engineering developed so far have addressed only narrow domains of the entire process of engineering. This paper discusses a KBES shell (IES) that integrates various AI technologies, which makes it possible to implement new problem-solving strategies required for efficient handling of the entire engineering process. Issues in the integrated process of engineering are discussed first, in order to evolve a specification for the shell. The blackboard architecture is shown to be the ideal backbone for such a shell. The details of inference techniques, the knowledge based backtracking mechanism and the DBMS used in the IES are presented. The application of the IES is demonstrated using the domain of integrated engineering of steel industrial structures as an example. This application encompasses the engineering activities of conceptual design, detailed design, documentation and construction planning.