Analysis and Design of Industrial Plants and Production Systems (Goods and Services)

Description

This line of research includes the study of technical, economic, and organizational aspects related to the design and feasibility study of systems for the production of goods and/or services understood as complex systems. The main research items related to this line are: feasibility studies and cost-benefit analyses; location and production relocation choices; layout studies; choice of the degree of integration and outsourcing of the production system; environmental impact assessment (EIA) of industrial plants; risk analysis and plant safety; energy assessment and optimization of plants; forecasting and optimization of technical and economic performance using analytical, computer-based, and experimental methodologies; project and risk management; plant sizing techniques. Development of innovative and automated models and operational tools for the optimization of complex systems, such as industrial warehouses with a focus on picking and the configuration of logistics and distribution networks.

Publications

• Del Gallo, M., Antomarioni, S., Mazzuto, G., Marcucci, G., & Ciarapica, F. E. (2024). A self-learning framework combining association rules and mathematical models to solve production scheduling programs. Production & Manufacturing Research, 12(1), 2332285. https://doi.org/10.1080/21693277.2024.2332285
• Pietrangeli, I., Mazzuto, G., Ciarapica, F. E., & Bevilacqua, M. (2023). Smart retrofit: an innovative and sustainable solution. Machines, 11(5), 523. https://doi.org/10.3390/machines11050523
• Fani, V., Antomarioni, S., Bandinelli, R., & Bevilacqua, M. (2023). Data-driven decision support tool for production planning: a framework combining association rules and simulation. Computers in Industry, 144, 103800. https://doi.org/10.1016/j.compind.2022.103800
• Di Carlo, F., Mazzuto, G., Bevilacqua, M., & Ciarapica, F. E. (2021). Retrofitting a process plant in an industry 4.0 perspective for improving safety and maintenance performance. Sustainability, 13(2), 646. https://doi.org/10.3390/su13020646
• Lucantoni, L., Antomarioni, S., Ciarapica, F. E., & Bevilacqua, M. (2025). A data-driven framework for supporting the total productive maintenance strategy. Expert Systems with Applications, 268, 126283. https://doi.org/10.1016/j.eswa.2024.126283

Staff

Prof. Maurizio Bevilacqua 
Tel. +39 071 220 4874
email: m.bevilacqua@staff.univpm.it

Prof. Filippo Emanuele Ciarapica 
Tel. +39 071 220 4435
email: f.e.ciarapica@staff.univpm.it

Prof.ssa Claudia Paciarotti 
Tel. +39 071 220 4696
email. c.paciarotti@staff.univpm.it

Prof. Giovanni Mazzuto
email. g.mazzuto@staff.univpm.it