The use of early design tools in engineering processes : a comparative case study

Nowadays, product design is increasingly complex: not only must it answer customer needs through complex functions; it must also ensure traceability throughout the design process, keeping in mind that standards and stringent regulations must be complied with. Faced with new challenges, engineering practices have evolved to allow stakeholders to be able to manage projects in new work environments, especially during the early stages of design. After presenting a state of the art of early design tools used in product design and their integration in PLM context, we compare class diagrams for two of them : TDC software (Knowllence©) and RFLP module of CATIA V6 (Dassault Systems©). Then, our paper presents an experiment focusing on these tools, which aims to assess their usability, to evaluate and compare them. Users can raise issues, take note of which functionalities are appreciated, and provide qualitative feedback. We analyze the results obtained in this experiment and propose a comparison based on four topics: learnability, satisfaction of users, efficiency and error correction. Finally, we present some links between class diagrams and usability of the tools

An ontology-based approach for semantic level information exchange and integration in applications for product lifecycle management

During product lifecycle management (PLM), product information fromCAD/CAE applications regularly needs to be exchanged and shared between the variousapplications. However, these applications often have different product data semantics andcorresponding representations. The interoperability problem caused by the heterogeneoussemantics and data representation is critical and needs to be addressed and automated.Recent research has focused on integration frameworks for CAD/CAE applications inorder to improve interoperability. There are fundamental problems that still need to beaddressed.We identified the following important roadblocks and sought to address thesespecifically in our work: 1) The need for an adequate product knowledge representationof engineering design/analysis, which is easily expandable, and customizable fortraditional and non-traditional (e.g. virtual prototyping) design information systems thatalso allows the sharing of product data semantics across all these heterogeneous systemsto support distributed, collaborative engineering capabilities; 2) The need for a way togenerate product data semantics by using engineering design/analysis knowledge tointerpret actual product data 3) The need for a way to reconcile the differences in thedifferent product semantics by finding underlying similarities between differentknowledge representations that are from different viewports and reconcile, and use thesesimilarities to then translate product data semantics correctly.This dissertation proposes an ontology-based approach for a semantic levelexchange and integration to improve interoperability, which includes an ontologybuilding tool, ontology mapping tools and custom tools to associate ontologies to prductdata. For the purpose of semantic level integration, a way of representing engineeringdesign/analysis knowledge using an engineering ontology is proposed. A layeredstructure is used for building knowledge into engineering ontologies so as to improve thescalability and composition adaptivity. Based on the knowledge, a semantic layer is builtupon product data to use concepts/relations in ontologies to describe actual product data,which can be used to represent understandings about a product design from differentperspectives. To enable translating different understandings (product data semantics)using different ontologies, an ontology mapping method is proposed to find matchingconcepts between different ontologies, based on three basic relation types betweenconcepts: composition, inheritance and attribute.A scenario is explained to describe the working mechanism of the system and todemonstrate the concept of semantic level integration framework for a simple example. Asample assembly is designed and simulated in different software packages and anintegrated process is made to exchange information between them. The scenariosuccessfully demonstrates the ontology based approach

An automated method mapping parametric features between computer aided design software

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonEnterprise efficiency is limited by data exchange. A product designer might specify the geometry of a product with a Computer Aided Design program, an engineer might re-use that geometry data to calculate physical properties of the product using a Finite Element Analysis program. These different domains place different requirements on the product representation. Representations of product data required for different tasks is dependent on the vendor software associated with those tasks, sharing data between different vendor programs is limited by incompatibility of the vendor formats used. In the case of Computer Aided Design where the virtual form of an object is modelled, no standard data format captures complete model data. Common data standards transfer model surface geometry without capturing the topological elements from which these geometries are constructed. There are prescriptive data representations to allow these features to be specified in a neutral format, but little incentive for vendors to adopt these schemes. Recent efforts instead focus on identifying similar feature elements between different vendor CAD programs, however this approach relies on onerous manual identification requiring frequent revision. This research develops methods to automate the task of mapping relationships between different data format representations. Two independent matching techniques identify similar CAD feature functions between heterogeneous programs. Text similarity and object geometry matching techniques are combined to match the data formats associated with CAD programs. An efficient search for matching function parameters is performed using a genetic algorithm that incorporates semantic data matching and geometry data matching. A greedy semantic matching algorithm is developed that compares with the Doc2vec short text matching technique over the API dataset tested. A SVD geometric surface registration technique is developed that requires fewer calculations than an equivalent Iterative Closest Point method