Special issue on: Collaborative and Multi-disciplinary Product Design
Notice bibliographique
Résumé
Collaborative and multi-disciplinary design can be defined as a process to coherently exploit the synergy of mutually interacting disciplinary expertise to optimize complex and large-scale product development. Due to the product complexity and the disciplinary backgrounds of engineers, the organization and management of the process remains as a challenge. Some difficulties include: there is no effective collaborative and multidiscipline development platform; efficient ways for knowledge and information exchange across domains do not exist; collaborative engineering needs sophisticated and optimized strategies to solve conflicts and to achieve better system performance; more research is required to provide designers with better understanding and more efficient approaches on the integration of conceptual design and detailed design to achieve the overall optimization, etc. To find effective solutions, many organizations, including academic, researchoriented, governmental, industrial and commercial ones, have recently started a number of research initiatives. In this special issue, seven papers are included to update the latest progress in this significant research area. The majority of the papers are the extended and peer-reviewed versions of those selected from the 2008 International Conference of Advances on Product Development and Reliability (PDR’2008), Chengdu, China, in which more than 100 papers were presented. The topics covered by this special issue are: unified product models to support lifecycle knowledge sharing, interoperability in collaborative engineering across design, manufacturing, operation, maintenance, and end-of-life stages, multi-disciplinary optimization models to support collaborative conceptual design, systematic and collaborative methodologies to generate innovative design from product requirements, and the development of software platforms and tools to support collaborative design processes and information retrieval. The first paper by Ding et al. presents a unified and XML-based product model to support lifecycle information and knowledge exchange. The model offers the potential to enable designers to revisit and retrieve the information throughout the lifecycle of machine design and build processes dynamically. An industrial case study for cleaning tank design has been used to demonstrate the effectiveness of the operation of the model. The second paper by Ma investigates the interoperability in collaborative engineering across design, manufacturing, operation, maintenance, and end-of-life stages with an expanded generic feature paradigm. A unified and consistent interoperable semantic scheme has been proposed to support an open and flexible knowledge realization system. The scheme and system have been applied to the oil production industry, and three design cases for grating layout, oil tank scaffolding and the piping system during an oil rig design process have been discussed. The third paper by Chu et al. addresses the uncertainty issue in collaborative and multi-disciplinary conceptual design. Based on the summary of uncertainties in conceptual design, a systematic tool based on the rough set theory and advanced kriging model has been developed to represent the approximate relationships between major design parameters. With the approximate relationships, designers can adjust design parameters and evaluate the impact of the changes to the overall performance of the design so as to facilitate decision making in the conceptual design stage. The fourth paper by Tang et al. proposes a new design process model based on Axiomatic Design (AD) and Design Structure Matrix (DSM). Both AD and DSM are design process management methods but applicable to different stages of design. The rationale of this research work is to combine the two models to take their *Author to whom correspondence should be addressed. weidong.li@coventry.ac.uk
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,010 | 0,006 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,109 | 0,046 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».