The industrial management of SMEs in the era of Industry 4.0 A Moeuf, R Pellerin, S Lamouri, S Tamayo-Giraldo, R Barbaray International journal of production research 56 (3), 1118-1136, 2018 | 1325 | 2018 |
Identification of critical success factors, risks and opportunities of Industry 4.0 in SMEs A Moeuf, S Lamouri, R Pellerin, S Tamayo-Giraldo, E Tobon-Valencia, ... International Journal of Production Research 58 (5), 1384-1400, 2020 | 520 | 2020 |
Strengths and weaknesses of small and medium sized enterprises regarding the implementation of lean manufacturing A Moeuf, S Tamayo, S Lamouri, R Pellerin, A Lelievre IFAC-PapersOnLine 49 (12), 71-76, 2016 | 110 | 2016 |
Data analytics in pharmaceutical supply chains: state of the art, opportunities, and challenges A Nguyen, S Lamouri, R Pellerin, S Tamayo, B Lekens International Journal of Production Research 60 (22), 6888-6907, 2022 | 76 | 2022 |
Deliveries optimization by exploiting production traceability information S Tamayo, T Monteiro, N Sauer Engineering Applications of Artificial Intelligence 22 (4-5), 557-568, 2009 | 64 | 2009 |
Industry 4.0 and the SME: a technology-focused review of the empirical literature A Moeuf, S Lamouri, R Pellerin, R Eburdy, S Tamayo 7th International Conference on Industrial Engineering and Systems …, 2017 | 47 | 2017 |
Development of a leagile transformation methodology for product development AA Lemieux, S Lamouri, R Pellerin, S Tamayo Business Process Management Journal 21 (4), 791-819, 2015 | 37 | 2015 |
City logistics 3: towards sustainable and liveable cities E Taniguchi, RG Thompson John Wiley & Sons, 2018 | 28 | 2018 |
Analysis of the opportunities of industry 4.0 in the aeronautical sector I Guyon, R Amine, S Tamayo, F Fontane 10th International Multi-Conference on Complexity, Informatics and …, 2019 | 27 | 2019 |
Vehicle routing problem with roaming delivery locations and stochastic travel times (VRPRDL-S) A Lombard, S Tamayo-Giraldo, F Fontane Transportation research procedia 30, 167-177, 2018 | 27 | 2018 |
Using artificial neural networks to predict grain boundary energies SE Restrepo, ST Giraldo, BJ Thijsse Computational materials science 86, 170-173, 2014 | 25 | 2014 |
Simulation applied to urban logistics: a state of the art S Jlassi, S Tamayo, A Gaudron City Logistics 3: Towards Sustainable and Liveable Cities, 65-87, 2018 | 24 | 2018 |
Relationships between national culture and Lean Management: A literature Review AF Martins, RC Affonso, S Tamayo, S Lamouri, CB Ngayo 2015 International Conference on Industrial Engineering and Systems …, 2015 | 22 | 2015 |
Loading/unloading spaces location and evaluation: an approach through real data S Tamayo, A Gaudron, A de La Fortelle City Logistics 3: Towards Sustainable and Liveable Cities, 161-180, 2018 | 16 | 2018 |
A genetic algorithm for generating grain boundaries SE Restrepo, ST Giraldo, BJ Thijsse Modelling and Simulation in Materials Science and Engineering 21 (5), 055017, 2013 | 15 | 2013 |
Unsupervised machine learning to analyze City Logistics through Twitter S Tamayo, F Combes, A Gaudron Transportation research procedia 46, 220-228, 2020 | 13 | 2020 |
Industry 4.0 in SMEs: a sectorial analysis J Luco, S Mestre, L Henry, S Tamayo, F Fontane Advances in Production Management Systems. Production Management for the …, 2019 | 10 | 2019 |
Electronic health record in the era of industry 4.0: the French example S Manard, N Vergos, S Tamayo, F Fontane arXiv preprint arXiv:1907.10322, 2019 | 8 | 2019 |
Interactive simulation for collective decision making in city logistics A Gaudron, S Tamayo, A de La Fortelle Transportation Research Procedia 46, 157-164, 2020 | 5 | 2020 |
Classifying logistic vehicles in cities using Deep learning S Benslimane, S Tamayo, A de La Fortelle arXiv preprint arXiv:1906.11895, 2019 | 5 | 2019 |