Product data quality and collaborative engineering

Abstract

In this paper, the impact of product data quality in the implementation of collaborative engineering in an extended enterprise framework is analyzed. Previously, some definitions about collaborative and concurrent engineering and present concepts like extended and/or virtual enterprise, digital mock-up, virtual prototype and virtual factory are reviewed.The product data model as a key element for the product development process is analyzed. The different views of this model are placed according to the fields where they apply. The importance of product model quality in the current status of data exchange standards is highlighted, with particular attention to ISO 10303 (STEP) new developments. Current state-of-art on data quality models, and product data quality recommendations such as VDA 4955/2 and SASIG PDQ, are also revised. Finally, our own product data quality model is presented. This comprises three points of view or levels: morphological, syntactic and semantic. Hence, it provides a tool for a better understanding of product data quality that helps find solutions that avoid the interoperability problem. Throughout the paper, references to the automotive industry will be used to illustrate concepts. Front-page photo:The left image represents an automotive radiator model simplified for FEM analysis. The central image shows the mesh model, and the right image represents modal analysis results

Extended 3D annotations as a new mechanism to explicitly communicate geometric design intent and increase CAD model reusability

“…These errors are usually due to mismatches in the numerical inaccuracies of the geometric kernels upon which CAD systems are built. We hypothesize that this second type of problems may also be linked to the syntactical quality suggested by Contero et al [30]. These two types of problems can be termed extrinsic which, along with intrinsic problems, are out of the scope of our study.…”

“…According to the linguistic model proposed by Contero et al [30], three levels of CAD quality can be distinguished, the third of which, the semantic/pragmatic level, considers the capability of the CAD model for reuse and modification. Making changes or reusing a particular CAD model may be simple, difficult, or impossible, depending on the semantics associated to the modeling procedure chosen by the original creator.…”

“…Currently, these problems are well covered by standards such as VDA 4955/4.1 [32] and SASIG PDQ 2.1 [33]. These problems can be termed as intrinsic problems (associated to morphological quality, according to [30]). The second type of problems is related to the product data exchange process, i.e.…”

“…semantic quality [30]). According to Yan & Han [31], a third to a half of all quality problems arise either from poor design skills or from the inexperience of designers.…”

Integrated modeling with top-down approach in subsidiary industries

“…In addition, the lack of standards supporting the capabilities of current commercial CAx applications, the variety of downstream applications making use of product data and the heterogeneous nature of work teams lead to poor quality CAD models. In a previous work, we proposed a Linguistic Model of product data quality (Contero et al, 2002), where three levels of quality were distinguished: morphological, syntactic and semantic/pragmatic level. The morphological level is related to the geometrical and topological correctness of the CAD model, while the syntactic quality evaluates the use of the proper modeling conventions.…”