Title
A.B. Editor et al. (Editors)
© 2005 Elsevier B.V./Ltd. All rights reserved.
1
Ontology-Based Information Management in
Design Processes
Sebastian C. Brandt
a
, Jan Morbach
b
, Michalis Miatidis
a
, Manfred Theißen
b
,
Matthias Jarke
ac
, Wolfgang Marquardt
b
a
Informatik V (Inform. Systems), RWTH Aachen University, 52056 Aachen, Germany
b
Process Systems Engineering, RWTH Aachen University, 52056 Aachen, Germany
c
Fraunhofer FIT, Schloss Birlinghoven, 53754 St. Augustin, Germany
Abstract
Engineering design processes are highly creative and knowledge-intensive tasks that
involve extensive information exchange and communication among diverse developers.
In such dynamic settings, traditional information management systems fail to provide
adequate support due to their inflexible data structures and hard-wired usage
procedures, as well as their restricted ability to integrate processes and product
information. In this paper, we advocate the idea of Process Data Warehousing as a
means to provide an information management and integration platform for such design
processes. The key idea behind our approach is a flexible ontology-based schema with
formally defined semantics that enables the capture and reuse of design knowledge,
supported by advanced computer science methods.
Keywords: Process Data Warehousing, Ontologies, Information Management
1. Introduction
Knowledge about engineering design processes belongs to the most valuable assets of
an enterprise. Typically, a vast amount of this design knowledge is manipulated by
legacy tools and stored in highly heterogeneous sources, such as electronic documents
and data bases. To fully exploit this intellectual capital, the knowledge must be made
explicit and shared among designers and across the enterprise. Thus, the prominent
concern of any successful approach is the integration of all these knowledge sources in a
coherent framework that supports the mining of knowledge and its reuse on demand.
In the literature, we can identify a plethora of contributions for the support of
engineering knowledge management inside manufacturing enterprises. Document
management systems are widely used in industrial praxis for the storage, maintenance,
and distribution of documents. A step further, Product Data Management (PDM)
systems provide extended facilities for the handling of detailed product information.
Regarding the process support, however, current PDM systems have largely focused on
the workflow management level [14], while the fine-grained support of development
activities (e.g. engineering best practices) has attracted less interest. The identified
contributions adequately support information exchange, especially in the later phases of
the engineering lifecycle, which are characterized by complete and well-known
processes and product models. They lack essential knowledge management capabilities
[5] and are less suited for the conceptual design stage [5; 14]. Conceptual engineering
design processes are highly creative and dynamic processes, which are hardly
predictable [12]. Any software solution has to cope with the continually changing
requirements and the many degrees of freedom within these processes. Because of their