Online Semantic Knowledge Management for Product Design Based on Product Engineering Ontologies

Introduction

The assumption that a
single
user works with a single computer system and a single application characterized by a centralized local knowledge base is out of date and rapidly getting revised (Gil, 2011), especially in engineering. There is a tremendous volume and diversity of product design data that engineers now create through the use of multiple design and analysis tools. There are issues unique to engineering that are related to compatibility of data across the applications, interoperability, and the widespread use of the CAD model as the master model. The issue is compounded because the engineers are often distributed globally. The CAD models are local-based and sharing of that data in near real time over the internet is a big challenge. Although engineers are now working with these multiple systems and multiple applications in a distributed manner, there needs to be progress in parallel in terms of using new approaches and technologies to support the management and sharing of this engineering data.

Traditionally, the process to build applications to share data has depended on hand-tuned and ad hoc techniques to integrate information (Seagram, 2009). Recently, ontology-based approaches have been used for managing product data. An ontology is a data model that represents a domain and is used to reason about the objects in that domain and relations between them. Using description languages, such as Resource Description Framework (RDF) and Web Ontology Language (OWL), data can be made explicit with semantic relationships, and thus there are powerful possibilities for mitigating miscommunication between engineers because everyone will interpret an ontology the same way. Using these approaches, ontology modeling allows engineers in a specific domain to represent design knowledge in a relatively flexible manner along with a formal and machine manipulatable standard in a context-dependent way. Machines can now be used to solve relatively complex problems that require application of domain knowledge. However, in order to realize the full potential of ontologies and create knowledge-contextual design environments, we need to extend the scope of sharing and reusing product design knowledge that has been captured in existing ontology models.

The Semantic Web provides a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries (Herman, 2009). Currently Semantic Web applications are used for personal information management, travel planning, and exchange of data in telecommunication and legal domains (Sheth, 2010). A few Semantic Web applications have been developed for product design in the engineering domain, but more powerful and germane applications would serve to streamline knowledge sharing, and ultimately enhance individual and group contributions to the field of engineering.

The monolithic and “silo” nature of CAD data in each CAD system and the great difficulty in viewing this data in any way other than in a CAD system or as a “dumb” model is definitely a major concern in many small and large design companies. If the Semantic Web can help alleviate this problem and allow real time querying and display of this data, it essentially creates a “lightweight” version of the CAD system and this information is now on the web, can be shared, can be dynamically collated, and does not need the CAD system after the initial instantiation process.

This research aims to explore a product design semantic knowledge management system (PD-SKMS) and realize a knowledge-contextual design environment for product engineers by integrating design knowledge with Semantic Web technologies. This paper makes four significant contributions that differentiate it from other research groups in this domain:

• 1.

  It constructs a knowledge-contextual design environment based on concepts of semantic knowledge management;

• 2.

  It provides applications with the capability to query/reason and author/update on a host hybrid-data repository;

• 3.

  It develops a novel approach to present rich, dynamic visualizations of product data semantics through the Web;

• 4.

  It provides for the extension of knowledge sources by linking to external public linked data sources in a seamless manner.