• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Laboratoire de Conception Fabrication Commande (LCFC)
  • View Item
  • Home
  • Laboratoire de Conception Fabrication Commande (LCFC)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
A compter du 1er janvier 2026 le portail institutionnel "HAL - Arts et Métiers Sciences et Technologies" remplacera l'archive ouverte SAM qui ne sera plus mise à jour. Pour permettre un alignement des données entre ces deux sites, les dépôts dans SAM seront arrêtés à compter du 28 novembre 2025 (17h). Pendant tout le mois de décembre l'équipe d'administration de SAM est joignable à cette adresse pour toute question sur le passage au portail Hal scienceouverte@ensam.eu

Key Characteristics identification by global sensitivity analysis

Article dans une revue avec comité de lecture
Author
IDRISS, Dana
322672 SIGMA Clermont [SIGMA Clermont]
BEAUREPAIRE, Pierre
322672 SIGMA Clermont [SIGMA Clermont]
GAYTON, Nicolas
322672 SIGMA Clermont [SIGMA Clermont]
ccHOMRI, Lazhar
107452 Laboratoire de Conception Fabrication Commande [LCFC]

URI
http://hdl.handle.net/10985/17468
DOI
10.1007/s12008-019-00625-z
Date
2019
Journal
International Journal on Interactive Design and Manufacturing

Abstract

During the design stage of product manufacturing, the designers try to specify only the necessary critical dimensions or what is called “Key Characteristics”. Knowing that dealing with Key Characteristics is time consuming and costly, it is preferable to reduce their number and exclude the non-contributing parameters. Different strategies that are based on qualitative or quantitative approaches for the identification of these dimensions are followed by the companies. The common way is to define the critical functional requirements which are expressed in terms of dimensions. When the functional requirements are set as critical, all the involved dimensions are labelled as Key Characteristics. However they do not have the same importance and need to be classified between contributing and non-contributing parameters. There is not a quantitative method that serves for the identification of Key Characteristics in the critical functional requirements. This paper suggests a numerical methodology which can be a step forward to a better ranking of the Key Characteristics. It is based on the global sensitivity analysis and more precisely on Sobol’ approach. The sensitivity of the Non Conformity Rate corresponding to the production of the product is measured with respect to the variable parameters characterizing the dimensions. The method is applied, first on a simple two-part example, then on a system having a linearised functional requirement and finally on a system with two non-linear functional requirements. The results show the main effects of the dimensions in addition to their interactions. Consequently it is possible to prioritize some and neglect the effect of the others and classify them respectively as Key Characteristics or not.

Files in this item

Name:
LCFC_IJIDEM_2019_HOMRI.pdf
Size:
757.4Kb
Format:
PDF
Embargoed until:
2020-05-01
View/Open

Collections

  • Laboratoire de Conception Fabrication Commande (LCFC)

Related items

Showing items related by title, author, creator and subject.

  • Probabilistic-based approach using Kernel Density Estimation for gap modeling in a statistical tolerance analysis 
    Article dans une revue avec comité de lecture
    GOKA, Edoh; BEAUREPAIRE, Pierre; ccDANTAN, Jean-Yves; ccHOMRI, Lazhar (Elsevier, 2019)
    The statistical tolerance analysis has become a key element used in the design stage to reduce the manufacturing cost, the rejection rate and to have high quality products. One of the frequently used methods is the Monte ...
  • Geometrical variations management for additive manufactured product 
    Article dans une revue avec comité de lecture
    HUANG, Zhicheng; GOKA, Edoh; BONNET, Nicolas; ccDANTAN, Jean-Yves; ccETIENNE, Alain; ccHOMRI, Lazhar; ccRIVETTE, Mickaël (Elsevier, 2017)
    Additive manufacturing (AM) became an advanced research topic due to its ability to manufacture complex shapes. But the ability to achieve predictable and repeatable shapes is critical. Therefore, to optimize the design ...
  • Tolerance Analysis of a Deformable Component Using the Probabilistic Approach and Kriging-Based Surrogate Models 
    Article dans une revue avec comité de lecture
    BEAUREPAIRE, Pierre; MATTRAND, Cécile; GAYTON, NIcolas; ccDANTAN, Jean-Yves (American Society of Civil Engineers (ASCE), 2018)
    Tolerance analysis is a key issue in proving the compatibility of manufacturing uncertainties with the quality level of mechanical systems. For rigid and isostatic systems, multiple methods (worst case, statistical, or ...
  • Optimum machine capabilities for reconfigurable manufacturing systems 
    Article dans une revue avec comité de lecture
    ASGHAR, Eram; ZAMAN, Uzair Khaleeq Uz; BAQAI, Aamer Ahmed; ccHOMRI, Lazhar (Springer Verlag, 2018)
    Reconfigurable manufacturing systems constitute a new manufacturing paradigm and are considered as the future of manufacturing because of their changeable and flexible nature. In a reconfigurable manufacturing environment, ...
  • Enhancing Fault Diagnosis in Process Industries with Internal Variables of Model Predictive Control 
    Article dans une revue avec comité de lecture
    ccDIALLO, Abdoul Rahime; HOMRI, Lazhar; ccDANTAN, Jean-Yves; BONNET, Frédéric; BOEUF, Thomas (Elsevier BV, 2024-08)
    This paper introduces the use of internal variables, estimated through Model Predictive Control (MPC), for fault detection and diagnosis in process industries. To do so, a data-driven methodology is proposed. Three ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales