A Smart System for Haptic Quality Control - Introducing an Ontological Representation of Sensory Perception Knowledge

Bruno Albert, Cecilia Zanni-Merk, François de Bertrand de Beuvron, Jean-Luc Maire, Maurice Pillet, Julien Charrier, Christophe Knecht

2016

Abstract

Perceived quality has become an important factor in the choice of products by customers. The human perception process involves complex phenomena at a physical and psychological level that enable us to sense the world and extract information about it. Because of the qualitative way humans represent and communicate sensations, the field of sensory perceptions makes extensive use of semantics. The use of knowledge-based systems in the field of perceived quality is hence natural. This project focuses on haptics in quality control in industry. In particular, the aim is to develop a smart system which will enable to make decisions about the haptic quality of a product. This paper introduces the framework used for the development of this smart system, based on the KREM model. An ontological structure is proposed in order to represent knowledge related to the measure of sensory perceptions in general, and of haptic ones in particular. The proposed domain ontologies about haptic control, that were elicited using semantic analysis, are aligned with the SSN ontology.

References

  1. Aamodt, A. and Plaza, E. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications, 7(1):39-59.
  2. Ba¯rzdi n¸s?, J., Ba¯rzdin¸s?, G., C?era¯ns, K., Liepi n¸s?, R., and Spro gis, A. (2010). Uml style graphical notation and editor for owl 2. In Perspectives in Business Informatics Research, pages 102-114. Springer.
  3. Baudet, N. (2012). Maˆitrise de la qualit é visuelle des produits - Formalisation du processus d'expertise et proposition d'une approche robuste de controˆle visuel humain. PhD thesis, Université de Grenoble.
  4. Bensmaïa, S. and Hollins, M. (2005). Pacinian representations of fine surface texture. Perception & psychophysics, 67(5):842-854.
  5. Compton, M., Barnaghi, P., Bermudez, L., García-Castro, R., Corcho, O., Cox, S., Graybeal, J., Hauswirth, M., Henson, C., Herzog, A., Huang, V., Janowicz, K., Kelsey, W. D., Le Phuoc, D., Lefort, L., Leggieri, M., Neuhaus, H., Nikolov, A., Page, K., Passant, A., Sheth, A., and Taylor, K. (2012). The SSN ontology of the W3C semantic sensor network incubator group. Journal of Web Semantics, 17:25-32.
  6. Crochemore, S., Vergneault, C., and Nesa, D. (2003). A new reference frame for tactile perceptions: Sensotact. 5th Rose Mary Pangborn, Boston MA, USA, pages 20-24.
  7. De Boissieu, F. (2010). Toucher artificielà base d'un microcapteur d'effort : traitement du signal et des informations associées. PhD thesis, Université de Grenoble.
  8. De Rossi, D. and Scilingo, E. P. (2006). Skin-like sensor arrays. Encyclopedia of sensors, 10:1-22.
  9. Dey, A. K., Abowd, G. D., and Salber, D. (2001). A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum.-Comput. Interact., 16(2):97-166.
  10. DOLCE+DnS Ultralite (2010). ontologydesignpatterns.org.
  11. Dumenil-Lefebvre, A. (2006). Integration Des Aspects Sensoriels Dans La Conception Des Emballages En Verre : Mise Au Point D'Un Instrument Methodologique Ì Partir Des Techniques D'Evaluation Sensorielle. PhD thesis, Ecole nationale supérieure d'arts et métiers.
  12. Gartiser, N., Zanni-Merk, C., Boullosa, L., and Casali, A. (2014). A semantic layered architecture for analysis and diagnosis of sme. In International, K., editor, Knowledge-Based and Intelligent Information & Engineering Systems 18th Annual Conference, KES2014, volume 35, page 1165-1174. Procedia Computer Science.
  13. Issa, M., Schacher, L., and Adolphe, D. C. (2005). Invariant attributes in the tactile characterization of fabrics. In Proceeding, Fiber Society Spring Conference.
  14. Jones, L. A. and Lederman, S. J. (2006). Human hand function. Oxford University Press.
  15. Lederman, S. and Klatzky, R. L. (2009). Haptic perception: A tutorial. Attention, perception & psychophysics, 71(3):1439-1459.
  16. Maire, J. L., Pillet, M., and Baudet, N. (2013). Measurement of the perceived quality of a product - Characterization of aesthetic anomalies. International Journal of Metrology and Quality Engineering, 4(2):63-69.
  17. Martin, S., Brown, W. M., Klavans, R., and Boyack, K. W. (2011). OpenOrd: an open-source toolbox for large graph layout. Proc. SPIE, 7868(JANUARY 2011):786806-786811.
  18. Milton, N. (2008). Knowledge Technologies. Polimetrica, Milano, Italy.
  19. Myrgioti, E., Bassiliades, N., and Miliou, A. (2013). Bridging the HASM: An OWL ontology for modeling the information pathways in haptic interfaces software. Expert Systems with Applications, 40(4):1358-1371.
  20. Picard, D., Dacremont, C., Valentin, D., and Giboreau, A. (2003). Perceptual dimensions of tactile textures. Acta Psychologica, 114(2):165-184.
  21. Roussey, C., Pinet, F., Kang, M. A., and Corcho, O. (2011). An Introduction to Ontologies and Ontology Engineering. In Ontologies in Urban Development Projects, chapter 2, pages 9-38. Springer London, London.
  22. Sanín, C. and Szczerbicki, E. (2009). Experience-based knowledge representation: Soeks. Cybernetics and Systems, 40(2):99-122.
  23. Sola, C. (2007). Y a pas de mots pour le dire, il faut sentir : Décrire et dénommer les happerceptions professionnelles. Terrain, (49).
  24. Summers, I. R., Irwin, R. J., and Brady, A. C. (2007). Haptic discrimination of paper. In Human Haptic Perception: Basics and Applications, number DECEMBER 2007, pages 525-535. Birkhäuser Basel.
  25. Zanni-Merk, C. (2015). Krem: A generic knowledge-based framework for problem solving in engineering - proposal and case studies. In INSTICC, editor, 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, pages 381-388. Science and Technology Publications, Lda.
  26. Zanni-Merk, C., Marc-Zwecker, S., Wemmert, C., and de Bertrand de Beuvron, F. (2015). A layered architecture for a fuzzy semantic approach for satellite image analysis. International Journal of Knowledge and Systems Science, 6(2):31-56.
Download


Paper Citation


in Harvard Style

Albert B., Zanni-Merk C., de Bertrand de Beuvron F., Maire J., Pillet M., Charrier J. and Knecht C. (2016). A Smart System for Haptic Quality Control - Introducing an Ontological Representation of Sensory Perception Knowledge . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016) ISBN 978-989-758-203-5, pages 21-30. DOI: 10.5220/0006048300210030


in Bibtex Style

@conference{keod16,
author={Bruno Albert and Cecilia Zanni-Merk and François de Bertrand de Beuvron and Jean-Luc Maire and Maurice Pillet and Julien Charrier and Christophe Knecht},
title={A Smart System for Haptic Quality Control - Introducing an Ontological Representation of Sensory Perception Knowledge},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)},
year={2016},
pages={21-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006048300210030},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)
TI - A Smart System for Haptic Quality Control - Introducing an Ontological Representation of Sensory Perception Knowledge
SN - 978-989-758-203-5
AU - Albert B.
AU - Zanni-Merk C.
AU - de Bertrand de Beuvron F.
AU - Maire J.
AU - Pillet M.
AU - Charrier J.
AU - Knecht C.
PY - 2016
SP - 21
EP - 30
DO - 10.5220/0006048300210030