| An ontological basis for computer aided innovation C Zanni-Merk, D Cavallucci, F Rousselot Computers in Industry 60 (8), 563-574, 2009 | 105 | 2009 |
| Smart condition monitoring for industry 4.0 manufacturing processes: An ontology-based approach Q Cao, F Giustozzi, C Zanni-Merk, F de Bertrand de Beuvron, C Reich Cybernetics and Systems 50 (2), 82-96, 2019 | 82 | 2019 |
| Context modeling for industry 4.0: an ontology-based proposal F Giustozzi, J Saunier, C Zanni-Merk Procedia Computer Science 126, 675-684, 2018 | 81 | 2018 |
| Use of formal ontologies as a foundation for inventive design studies C Zanni-Merk, D Cavallucci, F Rousselot Computers in Industry 62 (3), 323-336, 2011 | 81 | 2011 |
| KSPMI: a knowledge-based system for predictive maintenance in industry 4.0 Q Cao, C Zanni-Merk, A Samet, C Reich, FDB De Beuvron, A Beckmann, ... Robotics and Computer-Integrated Manufacturing 74, 102281, 2022 | 78 | 2022 |
| Towards a formal definition of contradiction in inventive design F Rousselot, C Zanni-Merk, D Cavallucci Computers in Industry 63 (3), 231-242, 2012 | 68 | 2012 |
| Initial situation analysis through problem graph D Cavallucci, F Rousselot, C Zanni CIRP Journal of Manufacturing Science and Technology 2 (4), 310-317, 2010 | 63 | 2010 |
| Starting from patents to find inputs to the problem graph model of IDM-TRIZ A Souili, D Cavallucci, F Rousselot, C Zanni Procedia engineering 131, 150-161, 2015 | 52 | 2015 |
| An ontology-based approach for inventive problem solving W Yan, C Zanni-Merk, D Cavallucci, P Collet Engineering Applications of Artificial Intelligence 27, 175-190, 2014 | 47 | 2014 |
| On contradiction clouds D Cavallucci, F Rousselot, C Zanni Procedia Engineering 9, 368-378, 2011 | 47 | 2011 |
| An ontology-based approach for failure classification in predictive maintenance using fuzzy C-means and SWRL rules Q Cao, A Samet, C Zanni-Merk, FDB De Beuvron, C Reich Procedia Computer Science 159, 630-639, 2019 | 45 | 2019 |
| Ontologies for manufacturing process modeling: A survey Q Cao, C Zanni-Merk, C Reich International conference on sustainable design and manufacturing, 61-70, 2018 | 44 | 2018 |
| Ontology population with deep learning-based NLP: a case study on the Biomolecular Network Ontology A Ayadi, A Samet, FB de Beuvron, C Zanni-Merk Procedia Computer Science 159, 572-581, 2019 | 42 | 2019 |
| Linking contradictions and laws of engineering system evolution within the TRIZ framework D Cavallucci, F Rousselot, C Zanni Creativity and Innovation Management 18 (2), 71-80, 2009 | 41 | 2009 |
| Assisting R&D activities definition through problem mapping D Cavallucci, F Rousselot, C Zanni CIRP Journal of Manufacturing Science and Technology 1 (3), 131-136, 2009 | 35 | 2009 |
| IngeniousTRIZ: An automatic ontology-based system for solving inventive problems W Yan, H Liu, C Zanni-Merk, D Cavallucci Knowledge-Based Systems 75, 52-65, 2015 | 34 | 2015 |
| Towards a formal model of the lean enterprise P Masai, P Parrend, C Zanni-Merk Procedia Computer Science 60, 226-235, 2015 | 33 | 2015 |
| A conceptual framework for the analysis, classification and choice of knowledge-based diagnosis systems C Zanni, ML Goc, C Frydman International Journal of Knowledge-based and Intelligent Engineering Systems …, 2006 | 31 | 2006 |
| Combining chronicle mining and semantics for predictive maintenance in manufacturing processes Q Cao, A Samet, C Zanni-Merk, F de Bertrand de Beuvron, C Reich Semantic Web 11 (6), 927-948, 2020 | 29 | 2020 |
| Enhancing Deep Learning with Semantics: an application to manufacturing time series analysis X Huang, C Zanni-Merk, B Crémilleux Procedia Computer Science 159, 437-446, 2019 | 29 | 2019 |
