I. Introduction
The development of CAD technology has gone through the following stages: In the 1970s, the use of CAD technology to generate digital drawings improved the efficiency of drawing engineering drawings, but did not really play a role in assisting design. In the 1980s, parametric modeling technology used feature-based CAD technology to build a fully parametrically driven 3D model. Based on this, finite element analysis, motion analysis, assembly interference checking, and NC automatic programming were performed on the overall design and components. Etc., to ensure that the design meets the actual engineering needs. But this time the CAD technology is only for a certain part of the product development process. Since the 1990s, process-based CAD technology has made it possible to delete some of the systems here. It is impossible to integrate domain design principles and knowledge, similar designs and expert experience into geometric models. Therefore, the reuse of knowledge resources cannot be realized. A lot of repetitive design work is required. In the early stages of product design, this situation affected the designer's innovative work.
In order to enable designers to focus on innovative work, CAD systems should help designers free themselves from repetitive tasks. Therefore, the next generation of mechanical CAD systems should use computer to extend the design capabilities of human experts with creative thinking as the core. It is possible to automate the design process. This is the true design tool. The process of human expert design depends on the expert's mastery, processing and application of knowledge. Without knowledge, analysis, judgment and decision-making cannot be carried out. Therefore, design automation is the automatic processing of knowledge. Currently, KBE (Knowledge Based Engineering) technology is the most promising solution to this problem.
The KBE system proposes solutions to the problems existing in traditional CAD systems, such as the embodiment of design principles, whether the constraints are conflicting, how to evaluate the products during the design phase, whether the design and manufacture are feasible, and whether the final product of the design meets the appearance requirements, and provides optimization. Program. The goal of the KBE system is to enable product information to be applied throughout its life cycle for optimal optimization.
Second, the concept of KBE
KBE is a computer-integrated processing technology that provides the best solution to engineering problems and tasks through the drive and propagation of knowledge. Due to the openness of KBE technology, there has not been a well-recognized complete definition so far. The KBE Center at Coventry University in the United Kingdom considers the KBE system to be a computer system that stores and processes knowledge related to product models and based on product models; the University of Washington in the United States considers KBE to be a design methodology that will be closely integrated with next-generation CAD technology. . It uses heuristic design rules that will cover the development of components, assemblies, and systems. The KBE system storage product model contains geometric, non-geometric information and engineering guidelines that describe how the product is designed, analyzed, and manufactured.
In summary, the connotation of KBE can be summarized as follows: KBE is the inheritance, integration, innovation and management of domain expert knowledge, and is the integration of CAx technology and AI technology. The KBE system framework is shown in Figure 1.
To make the KBE system the center of the engineering process, it must be applied to the relevant design principles at all stages of the product. To effectively utilize KBE systems from design analysis to manufacturing, KBE systems are required to be flexible, open, reusable, and customizable. The KBE system is deeply embedded in the CAx system, rather than simply being added to an existing system. Therefore, the KBE system should have the following basic functions.
(1) Use of knowledge – easy access to knowledge databases Knowledge databases exist in many forms and can be persistent databases or spreadsheets. The KBE system has easy access to these knowledge databases, so the openness of the KBE system is very important.
(2) Representation of knowledge - Creating and applying knowledge rules Knowledge rules are a representation of knowledge. Knowledge representation is a set of conventions that describe the world. It is the symbolization of knowledge. This method conveniently represents human knowledge as a knowledge structure that computers can receive and process. Knowledge representation must consider both the storage of knowledge and the use of knowledge. Knowledge representation is divided into rules, predicate logic and framework. A rule is a textual description of a behavior that corresponds to a certain input. It can refer to various forms of knowledge base and produce certain results according to corresponding logical conditions, such as feature modeling, parameter calculation, and specified type of selection. Or generate a warning when the constraint is violated.
Knowledge rules can be established at any time during the life of the project. The form of the rules is flexible and can be applied to a variety of disciplines. Therefore, rules can be used at all stages of the product life cycle.
Knowledge rules have always been relevant to their related objects. For example, when a knowledge rule is applied to create a geometry, the rule and the geometry remain relevant during its existence. Designers can use this rule to edit this geometry, or they can generate a new geometry. If there is no such correlation, using this rule again can only regenerate another geometry, and the information of the first geometry is completely independent of this rule, so that the entire life cycle becomes a strictly serial process, which is impossible. Parallel engineering.
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