Yoshinobu Kitamura

Deployment of an ontological framework of functional design knowledge

Although the importance of knowledge sharing among designers has been widely recognized, knowledge about functionality in the conceptual design phase is hard to capture and is often scattered across technical domains. Aimed at capturing such functional knowledge that can easily be applied to other domains, we developed an ontological framework to systematically describe it. It includes six kinds of knowledge about functionality, i.e. two types of functional models, two types of organization of generic knowledge, and two ontologies of functionality. This paper reports on the successful deployment of the framework in a production company. The Plant and Production Systems Engineering Division of Sumitomo Electric Industries has used our framework to share functional design knowledge on production systems since May, 2001. An empirical evaluation by Sumitomos engineers was unanimously positive. They said that this framework enabled them to make implicit knowledge possessed by each designer explicit and to share it among team members. This paper discusses some successful use-cases in tasks such as a design review, a patent application, and solving a quality problem. We also discuss effects of our ontological framework as a consistent viewpoint for capturing implicit functional knowledge and as a conceptual interlingua among designers. The limitations of our framework are also discussed.

Ontology-based Description of Functional Design Knowledge and its Use in a Functional Way Server

In conceptual design of engineering devices, a designer decomposes a required function into sub-functions, so-called functional decomposition, using a kind of functional knowledge representing achievement relations among functions. However, such knowledge about functionality of engineering devices is usually left implicit because each designer possesses it. Even if such knowledge is found in documents, it is often scattered around technical domains and lacks consistency. Aiming at capturing such functional knowledge explicitly and sharing it in design teams, we discuss its systematic description based on functional ontologies which provide common concepts for its consistent and generic description. We propose a new concept named “way of achievement” as a key concept for capturing such functional knowledge. Categorization of typical representations of the knowledge and its organization as is-a hierarchies are also discussed. The generic concepts representing functionality of a device in the functional knowledge are provided by the functional concept ontology, which makes the functional knowledge consistent and applicable to other domains. We also discuss development of a design supporting system using the systematized knowledge, called a functional way server. It helps human designers redesign an existing engineering device by providing a wide range of alternative ways of achievement of the required function in a manner suitable for the viewpoint of each designer and then facilitates innovative design.

Ontology-based systematization of functional knowledge

It has been recognized that design knowledge is scattered around technology and target domains. One of the two major reasons for it is that different frameworks (viewpoints) for conceptualization of design knowledge are used when people try to describe knowledge in different domains. The other is that several key functional concepts are left undefined or even unidentified. In this paper, we first overview the state of the art of ontological engineering, which we believe is able to make a considerable contribution to resolving these difficulties. We then discuss our enterprise aiming at systematization of functional knowledge used for synthesis. We discuss ontologies that guide conceptualization of artefacts from the functional point of view. The framework for knowledge systematization is based on an extended device ontology and a functional concept ontology built on top of the extended device ontology. This paper particularly discusses the extended device ontology and its application in the mechanical domain. The utilization of the systematized functional knowledge in several application systems is also discussed, together with its advantages.

A functional concept ontology and its application to automatic identification of functional structures

Abstract Functionality of artifacts as well as structure and behavior plays crucial roles in problem-solving such as design. This article discusses automatic identifications of functional structures of artifacts from given behavioral models of components and their connection information (called functional understanding). We propose a functional concept ontology which provides a rich vocabulary representing functions together with clear definitions grounded on behavior. The ontology enables the automatic identification system to make the search in the functional space tractable and to screen out meaningless interpretations. Furthermore, the ontology includes a new category of functional concepts named meta-functions representing conceptual categories of interdependency between functions. It plays a crucial role in consolidation of functions to give criteria of grouping functions, that is, identity of consolidated functions. It enables the identification system to generate such functional hierarchies that do not correspond to physical structure.

Hozo: An Environment for Building/Using Ontologies Based on a Fundamental Consideration of Role and Relationship

We have developed an environment for building/using ontologies, named Hozo, based on both of a fundamental consideration of an ontological theory and a methodology of building an ontology. Since Hozo is based on an ontological theory of a role-concept, it can distinguish concepts dependent on particular contexts from so-called basic concepts and contribute to building reusable ontologies.

Construction and Deployment of a Plant Ontology

Although the necessity of an ontology and ontological engineering is well-understood, there has been few success stories about ontology construction and its deployment to date. This paper presents an activity of ontology construction and its deployment in an interface system for an oil-refinery plant operation which has been done under the umbrella of Human-Media Project for four years. It also describes the reasons why we need an ontology, what ontology we built, what environment we used for building the ontology and how the ontology is used in the system. The interface has been developed intended to establish a sophisticated technology for advanced interface for plant operators and consists of several agents. The system has been implemented and preliminary evaluation has been done successfully.

An environment for distributed ontology development based on dependency management

This paper describes a system for supporting development of ontology in a distributed manner. By a distributed manner, we mean ontology is divided into several component ontologies, which are developed by different developers in a distributed environment. The target ontology is obtained by compiling the component ontologies. These component ontologies are identified according to their conceptual level or domain characteristics. The distributed development of ontologies applies to many situations such as cooperative development, reusing ontologies and so on. To support such a way of ontology development, we investigate the dependency between component ontologies and design some functions for management of these ontologies based on their dependencies. We next consider the influence of a change of one ontology to others through its dependencies and design a function to suggest a few candidate modifications of the influenced ontology for keeping the consistency. We also present some examples of how the system works.

A representation language for behavior and function: FBRL

Abstract Although a lot of researchers have pointed out the significance of functional representation, the general relations between function and behavior are not yet fully understood. We consider the knowledge of each component in a system as consisting of two elements. One is a necessary and sufficient concept far simulation of the component which we call the behavior model. The other is the interpretation of the behavior under a desirable state which the component is expected to achieve, which we call function. By classification of the primitives necessary for the interpretation of the behavior in various domains, which we call “domain ontology”, we can capture and represent the function by selection and combination of the primitives. This paper proposes FBRL, a new language for representing behavior and function by combining the primitive we identified. Also we investigate the relation between function and behavior based on the primitives. As the primitives can represent concepts at various levels of abstraction, they will contribute to those tasks which rely on the simulations on the model of the target object, such as diagnosis, design, explanation and so on.

An Ontology-Based Annotation Framework for Representing the Functionality of Engineering Devices

This paper proposes a metadata schema relating to functionality based on Semantic Web technology for the management of the information content of engineering design documents. The schema enables us to annotate web-documents with RDF metadata, which represents devices as having specific functions. The metadata provide a clear and operational semantics for the functional terms in documents. The metadata schema is based on our own functional ontologies, which we believe to provide effective guidelines for consistent functional annotation. These ontologies have been developed over many years and deployed successfully in industry. We then demonstrate a document search system using the metadata, which enables us to retrieve web-documents using the types of function and relationships defined in the schema rather than more superficial terms. Such function-oriented management of information is especially useful in the conceptual design phase. It allows one to find previous cases of the same function in earlier designs and to find related patents. We go on to discuss the following two issues on the interoperability of the functional knowledge. The first is automatic transformation of the functional model in our modeling framework into a chart-style form commonly used for the FMEA (Failure Modes and Effects Analysis) activity using a mapping between our ontology and an FMEA ontology. The second is translation of the functional model between our functional vocabulary and other taxonomy of function, that is, Functional Basis proposed by Stone et al. Another mapping between our functional vocabulary and Functional Basis can be done via a richer, generic reference ontology of functions. This mapping would aim at clarifying ontological differences between functional taxonomies and enabling translation between them.

Towards a Reference Ontology for Functional Knowledge Interoperability

Functionality is one of the key aspects of artifact models for design. A function of a device, however, can be captured in different ways in different domains or by different model-authors. Much research on functions has been conducted in the areas of engineering design, functional representation and philosophy, although there are several definitions and notions of functions. We view conceptualization of function is multiplicative in nature: different functions can be captured simultaneously from an objective behavior of an artifact under different teleological contexts of users/designers, or from different viewpoints (perspectives) of a model-author. Such differences become problematic for sharing functional knowledge among engineers. In this article, we attempt to clarify the differences of such perspectives for capturing functions on the basis of the ontological engineering. On the basis of a generalized model of the standard input-output model in the well-known systematic design methodology, we show descriptive categorization of some upper-level types (classes) of functions with references to some definitions of functions in the literature. Such upper-level ontological categories of functions are intended to be used as a reference ontology for functional knowledge interoperability. One of the two usages here is to convert functional models between different functional taxonomies. A functional term in a taxonomy is (ideally) categorized into a generic type defined in the reference ontology. It is widely recognized in the literature that such an upper-level ontology helps automatic “mapping discovery” which is to find similarities between two ontologies and determine which concepts represent similar notion. The reference ontology of function might have such an effect. Another usage of the reference ontology is to integrate fault knowledge into functional knowledge and automatic transformation of FMEA sheets. The designer can describe an integrated model of both functional knowledge and fault knowledge. Based on ontology mappings, automatic transformations of FMEA sheets can be realized. In this article, we discuss the detail of the definitions of the upper-level categories of functions ontologically. Then, we give an overview of usages and effects of the upper-level categories as a reference ontology for functional knowledge interoperability.Copyright