A parameter-extended case-based reasoning method based on a functional basis for automated experiential reasoning in mechanical product designs

The mechanical product design process involves much experiential reasoning which relies extensively on accumulated experience knowledge and ambiguous synthetic decision of experts (ASDE). This makes it hard to achieve the automated, intelligent and rapid design of mechanical products. Furthermore, due to the lack of consideration of experts' cognition of product functions and structures in the application of the current case-based reasoning (CBR) method in the field of automated experiential reasoning (AER), the parameter solving process is separated from ASDE. Aiming at improving the accuracy and intelligence level of AER in mechanical product design, this paper proposed a parameter-extended CBR (PECBR) method based on a functional basis by integrating ASDE into AER. The PECBR method mainly contains two parts: firstly, in order to acquire and quantitatively describe expert experiential knowledge to provide an effective basis for AER, a knowledge representation method integrating a function-flow-parameter matrix set (FFP-MS) using functional bases and a parameter experiential correlation matrix (PEC-M) extracted from FFP-MS were presented for mechanical products, where the FFP-MS characterized the operation of function and energy flow during the working process of products. An acquisition rule for FFP-MS was designed to extract the degree of correlation between each two parameters, in which the implicit knowledge hiding among functions, flows and parameters was mined to form PEC-M; secondly, to cope with the difficulty in integrating ASDE into AER, a feature-weighted case adaptation (FCA) method was proposed by adopting a presented weighted kernel support vector machine (WK-SVM) and dynamic particle swarm optimization (DPSO). The FCA method can achieve the intelligent and automated solving of product parameters through identifying PEC-M during the case adaptation process. Two case studies on two-stage reducers and corn huskers were carried out to demonstrate the validity of the PECBR method. Compared with other conventional CBR methods, PECBR method can derive a more accurate value of parameters in mechanical product designs especially in the case of limited similar cases.     

A smart conflict resolution model using multi-layer knowledge graph for conceptual design

Reducing the impact of conflicts on requirement-function-structure mapping in the early stage of product design is an important measure to achieve conceptual innovation, which relies on accurate reasoning of multi-domain knowledge. As product requirements become more personalized and diverse, traditional discrete knowledge organization and reasoning methods are difficult to adapt to the challenges of continuity and precision in conceptual solution. Knowledge graphs with complex networks have obvious advantages in association detection, knowledge visualization, and explainable reasoning of implicit knowledge, which offer innovative opportunities for conflict resolution in conceptual design. Therefore, a smart conflict resolution model using a multi-layer Knowledge Graph for Conceptual Design(mKGCD) is proposed in this study. A knowledge expression form of FBS-oriented design patent vocabulary is proposed, which is used for knowledge entity recognition and relation extraction based on natural language processing. A label mapping method based on inventive principles is used for patent classification and a four-layer semantic network for conflict resolution is constructed. Through semantic distance calculation, the designer's requirements for function/behavior/structure are smart deployed to obtain appropriate knowledge. A case study of the conceptual design of a collapsible installation and handling equipment demonstrates the feasibility of the proposed approach. The proposed method can not only meet the functional solution and innovation in the context of different design requirements, but also effectively improve the design efficiency in the iterative design process by means of multiple meanings of one graph.     

视觉知识：跨媒体智能进化的新支点

回顾跨媒体智能的发展历程,分析跨媒体智能的新趋势与现实瓶颈,展望跨媒体智能的未来前景。跨媒体智能旨在融合多来源、多模态数据,并试图利用不同媒体数据间的关系进行高层次语义理解与逻辑推理。现有跨媒体算法主要遵循了单媒体表达到多媒体融合的范式,其中特征学习与逻辑推理两个过程相对割裂,无法综合多源多层次的语义信息以获得统一特征,阻碍了推理和学习过程的相互促进和修正。这类范式缺乏显式知识积累与多级结构理解的过程,同时限制了模型可信度与鲁棒性。在这样的背景下,本文转向一种新的智能表达方式——视觉知识。以视觉知识驱动的跨媒体智能具有多层次建模和知识推理的特点,并易于进行视觉操作与重建。本文介绍了视觉知识的3个基本要素,即视觉概念、视觉关系和视觉推理,并对每个要素展开详细讨论与分析。视觉知识有助于实现数据与知识驱动的统一框架,学习可归因可溯源的结构化表达,推动跨媒体知识关联与智能推理。视觉知识具有强大的知识抽象表达能力和多重知识互补能力,为跨媒体智能进化提供了新的有力支点。     

Knowledge-based approach and system for assembly-oriented design,Part II: the system implementation

Assembly is one of the most important stages for product development. Assembly-oriented design (AOD) is a new approach to designing assemblies, which uses a number of design and analysis tools to help the designer plan out and analyze candidate assembly schemes prior to having detailed knowledge of the geometry of the parts. Using this approach, many assembly schemes can be inexpensively evaluated for their ability to deliver the important characteristics of the final product. This research proposes a knowledge-based approach and develops an expert design system to support top-down design for assembled products. The presentation of research report is divided into two parts: the knowledge-based approach (Part I) and the knowledge-based expert design system (Part II). This paper is the second part of the report (Part II). It will focus on the development of knowledge-based expert design system for assembly oriented design. The knowledge-based assembly oriented design system, i.e., the assembly oriented design expert system (AODES) is constructed to integrate assembly modeling and design, assembly planning, assemblability analysis and evaluation within a concurrent engineering environment. This intelligent system is implemented by integrating object-oriented representation, constraint-based modeling, rule-based reasoning, truth maintenance, and interfacing to database management system and CAD module, in which fuzzy logic based knowledge representation and inference technique are also applied to deal with uncertain data and knowledge in the design process. The developed system differs from the existing systems adopting part-first bottom-up modeling technique, in which a comprehensive intelligent framework is used for assembly modeling and design in a top-down manner from the conceptual level to the detailed level. It is able to help obtain better design ideas, provide users with suggestions so as to create and improve a design, and therefore give users the possibility to assess and reduce the total production cost at an early stage during the design process. Through the use of the system, the concurrent engineering knowledge can be effectively incorporated into the assembly design process in an integrated manner. A case assembly design shows that the intelligent modeling and design system is feasible.     

基于产品动态模型的智能快速响应设计理论和方法研究

文中将产品动态模型应用于快速响应变型设计中,研究了快速响应变型设计智能化理论和方法,提出了采用规则推理和实例推理相结合的混合推理策略;并针对设计的过程性,将变型设计分为概念变型设计、装配变型设计和产品定义变型设计;最后分析了基于产品动态模型的智能变型设计过程。     

基于CBR与神经网络的摩托车智能设计系统研究

针对摩托车总体设计过程依据相似性进行局部创新设计的特点,提出了基于CBR与神经网络的摩托车智能设计系统结构。采用面向对象方法对摩托车实例知识进行表示与组织,并将神经网络引入到实例推理中,利用ART1网络实现基于特征的动态层次聚类,通过BP网络实现从聚类模板到每一实例的索引,从而提高系统的推理效率与质量,形成有效的推理系统。     

形式化智能世界的建模过程

各种网络化实体或智能实体的嵌入将物理世界转变为智能世界,增加了基于物理世界统一抽象模型的推理复杂性.基于Saitta和Zucker定义的知识重构与抽象模型,提出一种新的表示智能世界的方法.通过感知重构过程,根据构成实体之间的通信关系自动构建3个可区分的、相互关联的子模型,即物理世界、网络化世界和虚拟世界,3个子模型之间的关系构成了智能世界的一个集成化模型.着重介绍了感知重构过程的形式化表示和推理机制.实际搭建的智能世界设计诊断推理实验表明,与基于知识重构和抽象一般物理世界模型相比,基于提出的智能世界模型的推理过程可以将系统故障限制在一个子模型中,从而较大程度地缩小了诊断的搜索空间.     

基于实例的智能工艺设计系统

针对传统智能工艺设计系统的缺陷与不足，结合基于实例推理（Case-Based Reasoning,CBR）和基于规则推理（Rule-Based Reasoning,RBR)的方法，设计了一个基于实例的智能工艺设计系统，给出了工艺实例一个完整清晰的形式化描述，阐述了新零件与实例进行比较和匹配的策略和算法，在检索出相符的实例后，调用RBR方法对实例进行修正，最终完成复杂的工艺设计任务。     

智能设计体系结构的研究

本文研究智能设计的体系结构,首先提出了智能设计的抽象层次模型,在分析设计师的智能行为后,提出智能设计的异构知识的概念,探讨了智能行为的内在运行机制,以及 计算机处理异构知识的集成推理方法,给出了基于上述模型的系统集成推理求解策略和实现方法。     

A hypernetwork-based approach to collaborative retrieval and reasoning of engineering design knowledge

Complex product development increasingly entails creation and sharing of design knowledge in a collaborative and integrated working environment. In this context, it has become a central issue to address the multifaceted feature of design knowledge for such a collaborative knowledge sharing scheme. This paper proposes a hypernetwork-based approach to explicitly capturing the relationships between various elements in a multifaceted knowledge representation. Specifically, a knowledge hypernetwork model is constructed, which is composed of a designer network, a product network, an issue network and a knowledge unit network. The relationships between various nodes from different networks are identified and defined according to specific node properties. In addition, topological characteristics of the hypernetwork structure are analyzed together with the statistical indicators. Based on this model, the Bayesian approach is adopted to conduct the collaborative reasoning process whereby knowledge elements relevant to the current design task are recommended according to the issues to be resolved and the current design context. A case study conducted in this work shows that the proposed approach is effective in capturing the complex relationships between multi-faceted knowledge elements and enables collaborative retrieval and reasoning of knowledge records.     

SEMANTIC CONSTRAINT MODELER FOR 2D AND 3D GEOMETRY

Design changes for 2D & 3D geometry are the most important features in the process ofproduct design.Constraint modeling for variationl geometry based on geometric reasoning is one ofthe best approaches for this goal.However,it is difficult for the proposed systems to maintain orhandle the consistency and completeness of the constraint model of the design objects.To changethis situation,a semantic model and its control approach are presented,aiming at the integrationof the data,knowledge and method related to design objects.Aconstraint definition system for in-teractively defining the semantic model and a prototype modeler based on the semantic model arealso implemented to examine the idea which is extended to 3D geometric design too.     

Developing a quantitative intelligent system for implementing concurrent engineering design

This research focuses on the development of a quantitative intelligent system for implementing concurrent engineering design. The paper first discusses the task of concurrent engineering design and the basic requirements for conducting integrated concurrent engineering design. The proposed quantitative intelligent system approach combines qualitative reasoning, based upon design and manufacturing knowledge, and quantitative evaluation and optimization, conducted using design information and manufacturing data generated in the knowledge-based reasoning. The method allows considerations on non-operating principle aspects of a product to be incorporated into the design phase, such as manufacturing, maintenance, service, recycle, etc., with an emphasis on production costs. The proposed method serves as a convenient software tool for gathering information required in the concurrent engineering design process and integrates tasks from different parts of the product development life cycle, particularly function design, manufacturability analysis and production cost estimation. A prototype software system is developed based upon this method using Smalltalk-80. In the prototype system, concurrent engineering design is carried out by: (1) describing and representing design requirements; (2) generating feasible design candidates and evaluating their design functions; (3) representing design geometry; (4) finding the associated production processes and predicting the production costs of each feasible design; and (5) identifying the costeffective design that satisfies given design requirements and requires minimum production costs.     

智能世界的建模与诊断

统一的抽象建模框架以及形式化表示可以帮助实现自动推理.随着物联网技术的发展,物理世界中嵌入了各种智能对象,改变了物理世界的部分特征,增加了建模和推理的复杂性.根据物联网带来的智能世界的特征,在知识重构与抽象模型(KRA模型)的统一建模框架基础上,提出了可区分的知识重构与抽象模型(dKRA模型).该模型通过3个相互关联的子模型及其之间的关系来表示智能世界,并给出相关定义和定理说明在所提出的模型框架内,可以将基于模型的诊断过程限制在一个(或多个)子模型中.研究内容侧重于系统设计阶段的模型验证,分别从理论和实验角度分析了基于智能世界dKRA模型的诊断过程时间效率的提高(与基于智能世界KRA模型的诊断过程相比).     

A knowledge intensive multi-agent framework for cooperative/collaborative design modeling and decision support of assemblies

Multi-agent modeling has emerged as a promising discipline for dealing with decision making process in distributed information system applications. One of such applications is the modeling of distributed design or manufacturing processes which can link up various designs or manufacturing processes to form a virtual consortium on a global basis. This paper proposes a novel knowledge intensive multi-agent cooperative/collaborative framework for concurrent intelligent design and assembly planning, which integrates product design, design for assembly, assembly planning, assembly system design, and assembly simulation subjected to econo-technical evaluations. An AI protocol based method is proposed to facilitate the integration of intelligent agents for assembly design, planning, evaluation and simulation process. A unified class of knowledge intensive Petri nets is defined using the O-O knowledge-based Petri net approach and used as an AI protocol for handling both the integration and the negotiation problems among multi-agents. The detailed cooperative/collaborative mechanism and algorithms are given based on the knowledge objects cooperation formalisms. As such, the assembly-oriented design system can easily be implemented under the multi-agent-based knowledge-intensive Petri net framework with concurrent integration of multiple cooperative knowledge sources and software. Thus, product design and assembly planning can be carried out simultaneously and intelligently in an entirely computer-aided concurrent design and assembly planning system.     

基于知识挖掘和案例推理的电渣重熔过程智能优化设定控制

依据电渣重熔生产工艺特点、操作经验和历史数据库,提出了基于案例推理的电渣重熔生产过程智能 优化设定控制方法．采用粗糙集理论从积累的大量电渣重熔过程历史控制数据中获取知识,将典型工况总结成案例 的形式以构造案例库,并对案例推理过程中的案例检索、案例修正及存储方法进行详细描述．该智能控制策略应用 于某电渣重熔生产过程,稳定了电渣重熔过程工艺指标,取得了较好的应用效果．     

基于综合推理的构图知识生成模型

讨论了一种集成图案拓扑结构和元素表达内容的构图设计知识的表达模型,研究并提出一种应用综合推理的思想来生成新的构图设计知识的推理模型。这种方法可以直接从原有构图设计知识的形象信息出发,根据一定的初始要求,迅速综合生成新的构图设计知识,大大提高了知识的生成速度,使得智能图案设计系统具有更高的智能性与创新能力。     

A model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets

In many application areas there is a need to represent human-like knowledge related to spatio-temporal relations among multiple moving objects. This type of knowledge is usually imprecise, vague and fuzzy, while the reasoning about spatio-temporal relations is intuitive. In this paper we present a model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets. The model should be suitable for the design of a knowledge base for real-time, multi-agent-based intelligent systems that include expert or user human-like knowledge. The central part of the model is the knowledge representation scheme called FuSpaT, which supports the representation and reasoning for domains that include imprecise and fuzzy spatial, temporal and spatio-temporal relationships. The scheme is based on the high-level Petri nets called Petri nets with fuzzy spatio-temporal tokens (PeNeFuST). The FuSpaT scheme integrates the theory of the PeNeFuST and 117 spatio-temporal relations.The reasoning in the proposed model is a spatio-temporal data-driven process based on the dynamical properties of the scheme, i.e., the execution of the Petri nets with fuzzy spatio-temporal tokens. An illustrative example of the spatio-temporal reasoning for two agents in a simplified robot-soccer scene is given.     

Fuzzy reasoning approach to similarity evaluation in image analysis

In image analysis, the concept of similarity has been widely explored and various measures of similarity, or of distance, have been proposed that yield a quantitative evaluation. There are cases, however, in which the evaluation of similarity should reproduce the judgment of a human observer based mainly on qualitative and, possibly, subjective appraisal of perceptual features. This process is best modeled as a cognitive process based on knowledge structures and inference strategies, able to incorporate the human reasoning mechanisms and to handle their inherent uncertainties. This articlea proposes a general strategy for similarity evaluation in image analysis considered as a cognitive process. A salient aspect is the use of fuzzy logic propositions to represent knowledge structures, and fuzzy reasoning to model inference mechanisms. Specific similarity evaluation procedures are presented that demonstrate how the same general strategy can be applied to different image analysis problems. © 1993 John Wily & Sons, Inc.     

Integrating multi-granularity model and similarity measurement for transforming process data into different granularity knowledge

The core of intelligent manufacturing is to incorporate the expert knowledge in manufacturing process, and knowledge transformation is the key to knowledge accumulation and application. In this paper, the research carried on transformation for different granularity knowledge from the cases of sheet metal parts in process planning. First of all, this paper analyzes the difference of organization structure between process data and knowledge in the base. The multi-granularity model of process knowledge is established in the form of tuple, which helps to clarify the hierarchy structure and internal relations. Thereafter, the concrete process is presented to transform single granularity process data into multi-granularity process knowledge, i.e., process data extraction, state determination and knowledge construction. With respect to state determination, similarity measure methods for different granularity knowledge are established to reduce the redundancy in the transformation process. As a novel approach, sequence alignment based on edit distance is proposed to calculate similarity exactly between two process flows. Finally, the knowledge transformation tool for different granularity knowledge is developed to enhance knowledge acquisition and improve the strength of knowledge reuse in fabrication order design for sheet metal parts through application of the above method. Also an example is given to illustrate the usefulness of the proposed method.     

产品的相似性推理:一种描述逻辑的方法

采用产品本体理论对设计进行本体标注,得到对应产品设计的形式化概念,在此基础上通过本体的推理——基于描述逻辑的知识推理,对产品进行分类．文中分别就设计的相似性和基于实例的设计中实例间的相似性推理提出了明确的算法,并通过实例进行了说明．