ROSSELLA POZZI è Professore Associato di Impianti Industriali Meccanici presso la LIUC – Università Cattaneo. Ha conseguito il PhD in Gestione Integrata d’Azienda presso la LIUC – Università Cattaneo, spendendo un periodo all’Istituto dalle Molle sull’Intelligenza Artificiale di Lugano.
Le sue aree di competenza riguardano le Operations, con particolare focalizzazione sulla gestione dei materiali in situazioni di capacità produttiva finita e sul Lean Manufacturing nelle imprese industriali.
Attualmente sta approfondendo le tematiche relative all’impatto del Lean sul processo di digitalizzazione dei processi manifatturieri e di adozione delle tecnologie Industry 4.0. E’ coinvolta in una ricerca sul tema Digital Manufacturing Readiness e in una ricerca sulle opportunità di adozione del paradigma Industry 4.0 da parte delle aziende produttrici di macchine per la plastica e gomma.
Ha partecipato a numerose iniziative di formazione, ricerca e consulenza con aziende di primaria importanza tra cui Lindt&Sprungli, Carl Zeiss, CentroStyle, Mazzucchelli, Eurojersey.
Coordina le attività del Lean Club LIUC, con cui collabora dal 2012, ed è coordinatrice dell’Executive Program L’eandustry 4.0, incentrato sul trasferimento delle tematiche del Lean e Industry 4.0.
Nell’ambito delle attività sul Lean Management ha avuto occasione di effettuare gemba walk negli stabilimenti in Giappone di Toyota, Daikin, Denso, Sekisui e Tatekita e negli stabilimenti europei ed italiani di Toyota Material Handling, Schneider Electric, Franke, Slimpa Kone, Lindt&Sprungli, Aermacchi, ABB Dalmine.
Saporiti, N., Cannas, V. G., Pozzi, R., & Rossi, T. (2023). Challenges and countermeasures for digital twin implementation in manufacturing plants: A Delphi study. International journal of production economics, 261, 108888.
Pozzi, R., Rossi, T., & Salani, M. (2023). Economic production quantity (EPQ) model in ‘pull’managed single-machine multi-item production systems. Annals of Operations Research, 1-21.
Strozzi, F., & Pozzi, R. (2023). Trend and seasonality features extraction with pre-trained CNN and recurrence plot. International Journal of Production Research, 1-12.
Pozzi, R., Cannas, V. G., & Ciano, M. P. (2021). Linking data science to lean production: a model to support lean practices. International Journal Of Production Research, 1-22.
Pozzi, R., Rossi, T., & Secchi, R. (2021). Industry 4.0 technologies: critical success factors for implementation and improvements in manufacturing companies. Production Planning & Control. 2021, 1-21.
Ciano, M. P., Pozzi, R., Rossi, T., & Strozzi, F. (2021). Digital twin-enabled smart industrial systems: a bibliometric review. International journal of computer integrated manufacturing, 34(7-8), 690-708.
Rossi, T., Pozzi, R., Pirovano, G., Cigolini, R., & Pero, M. (2020). A new logistics model for increasing economic sustainability of perishable food supply chains through intermodal transportation. International Journal of Logistics Research and Applications, 1-18.
Ciano, Maria Pia, Pozzi, Rossella, Rossi, Tommaso, Strozzi, Fernanda (2019). How IJPR has addressed ‘lean’: a literature review using bibliometric tools. International Journal Of Production Research, p. 1-34, ISSN: 0020-7543, doi: 10.1080/00207543.2019.1566667
Pozzi, Rossella, Pero, Margherita, Cigolini, Roberto D., Zaglio, Francesco, Rossi, Tommaso (2019). Using simulation to reshape the maintenance systems of caster segments. International Journal Of Industrial And Systems Engineering, vol. 33, p. 75-96, ISSN: 1748-5037, doi: 10.1504/IJISE.2019.102047
Pozzi, Rossella, Noe’, Carlo, Rossi, Tommaso (2018). A methodological approach to assess the content of work in air cargo operations. International Journal Of Operational Research, vol. 31, p. 224-244, ISSN: 1745-7645, doi: 10.1504/IJOR.2018.08913
Cannas, Violetta Giada, Pero, Margherita, Pozzi, Rossella, Rossi, Tommaso (2018). Complexity reduction and kaizen events to balance manual assembly lines: an application in the field. International Journal Of Production Research, vol. 56, p. 3914-3931, ISSN: 0020-7543, doi: 10.1080/00207543.2018.1427898
Pozzi, Rossella, Strozzi, Fernanda, Rossi, Tommaso, Noe’, Carlo (2018). Quantifying the benefits of the lean thinking adoption by the beer game supply chain. International Journal Of Operational Research, vol. 32, p. 350-363, ISSN: 1745-7645, doi: 10.1504/IJOR.2018.092739
Cigolini, R., Pero, M., Pozzi, R., Rossi, T. (2017) ‘Improving production planning through finite- capacity MRP’, Int. J. Production Research, Vol. 55, No. 2, pp. 377-391.
Rossi, T., Pozzi, R., Testa, M. (2017) ‘EOQ-based inventory management in single-machine multi-item systems’, Omega, vol. 71, pp. 106-113.
Cannas, V.G., Pozzi, R., Pero, M., Rossi, T. (2016) ‘Performance improvement of manual assembly lines in a context characterized by complexity’, Proceedings of the Summer School Francesco Turco, 13-15-September-2016, pp. 171-175.
Pozzi, R., Noè, C., Lazzarotti, V. and Rossi, T. (2015) ‘Using simulation for reliable investment appraisal: evidence from a case study’, Int. J. Operational Research, Vol. 23, No. 1, pp.45–62.
Pozzi R., Noè C., Rossi T. (2014), ‘Experimenting ‘learn by doing’ and ‘learn by failing’, European Journal of Engineering Education, Vol. 40, No. 1, pp.68-80.
Ciarapica, F.E., De Sanctis, I., Pozzi, R., Rossi, T. (2014) ‘Lean and agile in the Italian manufacturing context’, Proceedings of the Summer School Francesco Turco 09-12-September-2014, pp. 138-146.
Böttcher, M., Pero, M., Pirovano, G., Pozzi R. and Rossi T. (2013) ‘Simulation of train loading/unloading in an intermodal maritime container terminal’ – Paper accepted at 8th International Conference of Logistics, held from September the 5th to the 7th, 2013, in Hamburg, Germany .
Strozzi F., Rossi T., Noè C., Pozzi R. ‘Quantifying the benefits of the lean thinking adoption in a supply chain at a local and global level’, Int. J. Operational Research, In press. 10.1504/IJOR.2018.10002669
Del Torto, A., Pozzi, R., Porazzi, E., Garagiola, E., Strozzi, F. ‘Length Of Stay Reduction in the Emergency Department and its quantification Using Complex Network Theory’ Int. J. Operational Research, In press.
Pozzi R., Noè C., Rossi T. ‘A methodological approach to assess the content of work in air cargo operations’, Int. J. Operational Research, In press.
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