Ontology-Based Design Knowledge Representation for Complex Product

The ontolex interface is anchored on two essential elements of human knowledge: conceptual structure and lexical access. A well-structured ontolex interface facilitates bilingual representation of both the conceptual structure and the lexical information which will be crucial in overcoming linguistic barriers. In this chapter we propose a robust and versatile approach for constructing the ontolex interface infrastructure: Bilingual Ontological WordNet (BOW). The Academia Sinica Bilingual Ontological WordNet (Sinica BOW) was constructed in 2003 using this approach. We argue that this novel combination of ontology and WordNet will (1) give each linguistic form a precise location in the taxonomy, (2) clarify the relation between the conceptual classification and its linguistic instantiation, and (3) facilitate a genuine crosslingual access of knowledge.

The goal of this paper is to integrate the Conceptual Mapping Model with an ontology-based knowledge representation (i.e. Suggested Upper Merged Ontology (SUMO)) in order to demonstrate that conceptual metaphor analysis can be restricted and eventually, automated. In particular, we will propose a corpora-based operational definition for Mapping Principles, which are explanations of why a conventional conceptual metaphor has a particular source-target domain pairing. This paper will examine 2000 random examples of 'economy' (jingji) in Mandarin Chinese and postulate Mapping Principles based frequency and delimited with SUMO.

This chapter takes the complex knowledge systems of metaphors and shows that their structured knowledge can be represented and predicted by ontology. The complex knowledge system of metaphors contains two knowledge systems, source domain and target domain, as well as the knowledge mapping between the two domains. Hence metaphors offer a test case of how structured knowledge can be manipulated in an information system. In terms of the theory of metaphor, we integrate the Conceptual Mapping Model with an ontology-based knowledge representation. We demonstrate that conceptual metaphor analysis can be restricted and eventually, automated. In terms of knowledge processing, we argue that the knowledge structure encoded in ontology, such as the Suggested Upper Merged Ontology (SUMO), is the necessary foundation for manipulating information from multi-domain and multilingual sources. We first extract source domain knowledge structure based on ontology. Next we show that the ontological account allows correct explanation of the parallel yet different use of the same source domain in two different languages. Thirdly, we showed that the restricted set of upper ontology can be combined with the open lexical knowledgebase of wordnets to provide a principled, yet robust, general coverage of language-based knowledge systems.

Although current efforts have indicated the need for design verification and evaluation systems, little has been done to develop knowledge representation systems for implementing this class of expert systems. In this paper, we describe CANDLE, a knowledge representation system built to solve design verification and evaluation problems. We define the class of design verification and evaluation systems and the functionality required of knowledge representation systems used to develop these systems. We present an example design verification and evaluation problem, illustrating how this problem imposes these functionality requirements on the knowledge representation system used. In the remainder of the paper we discuss CANDLE, a knowledge representation system created to develop design verification and evaluation systems. We show that CANDLE meets the knowledge representation requirements for this class of systems. We also present some of CANDLE'S functionality that exceeds the defined knowledge representation requirements and provides a knowledge engineer with the capability to expand the functionality of a design verification and evaluation system.

Change detection is a fundamental approach in utilization of satellite remote sensing image, especially in multi-temporal analysis that involves for example extracting damaged areas by a natural disaster. Recently, the amount of data obtained by Earth observation satellites has increased significantly owing to the increasing number and types of observing sensors, the enhancement of their spatial resolution, and improvements in their data processing systems. In applications for disaster monitoring, in particular, fast and accurate analysis of broad geographical areas is required to facilitate efficient rescue efforts. It is expected that robust automatic image interpretation is necessary. Several algorithms have been proposed in the field of automatic change detection in past, however they are still lack of robustness for multi purposes, an instrument independency, and accuracy better than a manual interpretation. We are trying to develop a framework for automatic image interpretation using ontology-based knowledge representation. This framework permits the description, accumulation, and use of knowledge drawn from image interpretation. Local relationships among certain concepts defined in the ontology are described as knowledge modules and are collected in the knowledge base. The knowledge representation uses a Bayesian network as a tool to describe various types of knowledge in a uniform manner. Knowledge modules are synthesized and used for target-specified inference. The results applied to two types of disasters by the framework without any modification and tuning are shown in this paper.

Retrieving and composing individuals' capabilities are the matter of several research fields, like competence-based management, human resources management, enterprise knowledge management systems, knowledge representation systems, etc. This talk focuses on capability representation, discovery and composition in heterogeneous, and possibly distributed, knowledge representation environments. A driving motivation of this work is to provide a contribution to the satisfaction of the need for retrieving individuals who may carry out actions, as well as the need for retrieving individuals who, when putting their competences together, may carry out actions. We outline some formal capability description languages, and we propose approaches and algorithms for capability management, discovery and composition. In addition, we outline how our proposals are implemented in mediator-based prototype systems under a service oriented architecture and a Peer-to-Peer architecture.

Product design tends to be more complex and needs the effective cooperation among multidisciplinary designers and engineers. An ideal product design environment, which is both collaborative and intelligent, will be much appreciated. Agent technology is an innovative and promising approach to implementing distributed systems and is becoming popular in various areas of computing in recent years. In this paper, the dynamic nature of collaborative design process and the representation of collaborative design knowledge are presented. In order to model constantly evolving design process and the rationales resulted from collaboration, a Collaborative Product Data Model (CPDM), which extends traditional Product Data Model (PDM), and a constraint-based Collaborative Design Process Model (CDPM) are proposed. These are intended to facilitate the management and coordination of collaborative product design process and knowledge management. A design example is used to illustrate CDPM. While the system is being implemented, the architecture of our agent-based collaborative product design environment based on CPDM and CDPM is described.

Representation of functional micro-knowledge cell (FMKC) for conceptual design

For the features of complex product design knowledge, this study suggests a way of complex product design knowledge modeling based on Living systems theory. First, an in-depth analysis of the different levels defined in the LST and the functions of the twenty subsystems in the LST is performed. The structure and process parameters are also analyzed. This is done based on the common features of complex products and living systems. Then, a mapping model of the LST and complex products is created. This model is then used in the modeling of the design knowledge of complex products, including the various layers, functionalities, and structural and process parameters of the complex product in question. Finally, a case is studied to elaborate the implementation of the presented method and validate the effectiveness and practicability.

Conceptual design plays a pivotal role in generating creative design solutions and, in most cases, reuse of existing design knowledge is necessary. However, lack of a consistent design knowledge representation model and neglect of an integrated approach to support various formats of design knowledge reuse constrain conceptual design from transforming design requirements into practical promising design solutions. In order to solve these problems, this paper presents a constrained function-behavior-structure knowledge cell (CFBS) model to provide conceptual design process with a consistent knowledge representation model. CFBS-based integrated approach for design knowledge reuse is proposed, which includes three-level CFBS retrieval process to obtain most relevant CFBS expressed in various types, three-stage design synthesis process to produce suggested design solutions, and evaluation process to select the most feasible design solutions. The effectiveness of the proposed design process was illustrated with conceptual design of the micro-feed drive module of insulin pump based on the CFBS library.

Automatically Learning Preliminary Design Knowledge from Design Examples

A RFBSE model for capturing engineers’ useful knowledge and experience during the design process

Representing design knowledge as a network of function, behaviour and structure

In this article, ethical decision‐making methods for creating, revising, and maintaining knowledge representation and organization systems are described, particularly in relation to the global use of these systems. The analysis uses a three‐level model and the literature on ethically based decision‐making in the social and technical sciences. In addition, methods for making these kinds of decisions in an ethical manner are presented. This multidisciplinary approach is generalizable to other information areas and is useful for encouraging the development of ethics policies for knowledge representation and organization systems and for other kinds of systems or institutions.

Modern product development becomes increasingly collaborative and integrated, which raises the need for effectively and efficiently sharing and re-using design knowledge in a distributed and collaborative environment. To address this need, a framework is developed in this research to support design knowledge representation, retrieval, reasoning and fusion, which takes account of structural, functional and behavioral data, various design attributes and knowledge reasoning cases. Specifically, a multi-level knowledge representation based on the Base Object Model (BOM) is proposed to enable knowledge sharing using Web services technologies. On this basis, a multi-level knowledge reuse method is developed to support the retrieval, matching and assembly of knowledge records. Due to the tree structure of BOM, both depth-first and breadth-first searching strategies are employed in the retrieval algorithm while a novel measure is proposed to evaluate similarity. Moreover, a method based on the D-S evidence theory is developed to enable knowledge fusion and thus support effective decision-making. The framework has been implemented and integrated into an HLA-based simulation platform on which the development of a missile simulation example is conducted. It is demonstrated in the case study that the proposed framework and methods are useful and effective for design knowledge representation and reuse.