工艺知识管理系统的设计

工艺知识库是ＣＡＰＰ系统的重要组成部分。本文提出了一种分类层次模型以组织和管理工艺知识，并据此建立工艺知识库ＰＰＫＢＳ。用四种形式表达工艺知识，并以外部和内部两种形式表现。提出了工艺知识的冗余、矛盾和句法结构检查方法。     

工艺设计知识库的建造与维护

文中根据工艺设计知识的特点,构造了层次化的知识表达、组织与知识库模型,分析了工艺知识库不一致的表现形式,并给出了相应的一致性验证算法,提出了基于广义决策表的知识库完备性检查方法。     

基于知识的计算机辅助工艺设计系统

介绍了一个较为通用的基于知识的计算机辅助工艺设计（ＣＡＰＰ）系统结构。包括知识表达和关联函数，知识库管理，任务分解与综合策略，解释机制，与其他系统的接口。     

基于知识的故障诊断系统的设计

针对大型测试系统的故障诊断技术的特点和设计要求,讨论了基于知识的故障诊断专家系统的设计思想和实现方法,重点介绍了其基本结构和软件实现。     

知识库管理系统程序设计

知识库设计是专家系统设计的基础环节，本文提出了一种知识库管理系统的设计方法，它具有简洁性、高效性和透明性的特点。为今后建造实用的专家系统提供了方便。     

一个基于开放式结构的工艺设计知识库系统

根据工艺设计知识库的开放性要求,提出了一个基于开放式结构的层次化知识库模型。在此基础上构造了工艺设计知识库及其管理系统,并给出了工艺知识的综合表示方法和知识库的维护算法。     

集成环境下基于加工特征的工艺设计系统的研究

本文研究了ＣＩＭＳ集成环境下面向ＣＡＤ／ＣＡＭ的基于特征的工艺决策系统以及ＣＡＰＰ的基于加工表面的特征建模和工艺数据库的组织与应用。具体分析了工艺规划过程的特点，提出了ＣＡＰＰ系统应具有的功能模块及其要解决的主要技术问题。     

CAD／CAM集成系统中轴类零件CAPP专家系统的研制

当代在推进ＣＩＭＳ中，专家系统日益受到重视，本文论述了专家系统方法在自动生成零件加工工艺文件中的应用进行了研究和讨论，研制了一种创成式轴类零件ＣＡＰＰ专家系统－ＧＳＣＡＰＰ。该系统通过人机图形选单对话或与ＣＡＤ系统连接输入的方式输入少量信息（如零件结构，尺寸，精度及热处理方式等），即可在知识库的支持下自动生成完整的零件的加工工艺文件，系统运行简捷，可编工艺范围广，维护方便，输出的工艺文件符合工厂要     

知识库管理系统HDS-KBS1

本文介绍我们在micro VaxⅡ上开发的知识库管理系统HDS-KBS1,以及有关技术:扩充Prolog使其成为知识库管理系统的推理子系统;推理子系统和库管理系统INGRES的联结;demo谓词和语义完整性维护的实现。     

纺织专家系统中知识与知识库的应用

专家系统是人工智能的一个分支，是一种模拟专家决策能力的计算机系统，知识库是系统的重要组成部分，是系统的核心。本文结合纺织工艺设计及管理专家系统介绍了基于知识的专家系统的概念和结构，对系统中知识的获取、存储方式予以说明．并对其知识的表示方法加以阐述。     

基于知识库的企业诊断原型系统的设计与实现

企业诊断是改善企业管理工作,提高企业经济效益的有效手段。利用计算机获取专家诊断知识,自动智能地分析企业数据,实时对企业作出诊断与评价,对企业发展有着深元的影响,文中研究了制造类型企业的诊断方法和技术,建立了企业诊断和知识库的系统结构,并设计与实现了企业诊断计算机软件原型系统。     

基于模糊理论的造纸专家系统--知识库的设计

基于模糊理论的造纸专家系统(PMES)的研究对于保障设备的稳定运行,提高产品质量具有重要的意义.本文探讨了模糊理论在知识表示方面如何和专家系统进行有效地结合,并对PMES的知识库进行设计.对知识库采用知识分级的方式,使知识的表达更具有层次性.通过各个知识表中的相互约束关系保证知识的一致性.     

A knowledge-based process planning system for injection mold

The goal of this study is to develop a knowledge-based process planning system interfaced with design for injection mold. Mold parts are interactively designed by using feature-based design approach, and then a part feature database is created through a data conversion module. Attribute information of the database is used as an input for the expert process design module and the standard time estimation module of the knowledge-based process planning system developed in this study. In this developed system, decision making of process design is performed by rules which were acquired from experienced process planners through interviews, and machining operation time is estimated by using empirical formulas derived from the actual shop floor data. A case example of split cavity plate is used to demonstrate the system performance.     

The knowledge base partitioning problem: Mathematical formulation and heuristic clustering

Allocation of production rules among several partitions in a knowledge base can shorten the compilation and execution of expert systems applications and facilitate their verification, validation and maintenance. The problem of allocation of rules or groups of rules among partitions of limited size while minimizing the sum of inter-partition connections is formulated as a 0–1 integer programming problem with a quadratic objective function. Since this type of problems is NP-complete, a clustering algorithm based on the nearest neighbor heuristic is proposed.     

The design of a knowledge based process diagnostic system

This paper describes the need for and the design of, a knowledge based process diagnostic system. A prototype system is implemented using Intellicorp's Knowledge Engineering Environment (KEE). The system is being implemented at a planned new assembly plant.     

On the use of dynamic feedback in knowledge base system design

The problems of the physical design of knowledge base systems is discussed. A basic architecture for adding monitoring and reorganization software to knowledge base management systems is presented. This software uses dynamic feedback from the system to restructure the physical representation of data. Examples of the incorporation of monitoring and reorganization software into existing systems are given.     

Modeling of expert system of quality standard in supply chain

The quality of the products is tremendously hard to retain and even goes out of control when excess links of supply chains are involved in the process and if the quality standards and requirements of the products and parts are neglected. As a result, it is highly necessary to set up an expert system to combine all parts, such as but not limited to: technical standards, experiences of processing and manufacturing involved, the standard rules, and characteristic of parts, etc. together in the form of a knowledge base, so as to inquire and deduce known and unknown standards of products and parts in a timely and effectively manner. This knowledge base is then stored with relational database, relational calculus to be inquired and similarity to be deduced, and these can further form new rules by inductive learning as described in this paper.