{\rtf1\ansi\deff0\deftab360

{\fonttbl
{\f0\fswiss\fcharset0 Arial}
{\f1\froman\fcharset0 Times New Roman}
{\f2\fswiss\fcharset0 Verdana}
{\f3\froman\fcharset2 Symbol}
}

{\colortbl;
\red0\green0\blue0;
}

{\info
{\author Biblio}{\operator }{\title Biblio RTF Export}}

\f1\fs24
\paperw11907\paperh16839
\pgncont\pgndec\pgnstarts1\pgnrestart
Dinis, Duarte. "Maintenance capacity planning, spare parts management, and maintenance scheduling: An overview." \i Reference Module in Social Sciences\i0 . Elsevier,  2025. \par \par Dinis, Duarte. "Maintenance Management: A Review on Problems and Solutions." \i Procedia Computer Science\i0 . 253 (2025): 3069-3077.\par \par Dinis, Duarte Caldeira, Jos\'e9 Rui Figueira, and \'c2ngelo Palos Teixeira. "A multiple criteria approach for ship risk classification: An alternative to the Paris MoU Ship Risk Profile." \i Socio-Economic Planning Sciences\i0 . 90 (2023): 101718.\par \par Pereira, Miguel Alves, Duarte Caldeira Dinis, Diogo Cunha Ferreira, Jos\'e9 Rui Figueira, and Rui Cunha Marques. "A network Data Envelopment Analysis to estimate nations? efficiency in the fight against SARS-CoV-2." \i Expert Systems with Applications\i0 . 210 (2022): 118362.\par \par Dinis, Duarte, Ana Barbosa-P\'f3voa, and \'c2ngelo Palos Teixeira. "Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems." \i International Journal of Forecasting\i0 . 38 (2022): 178-192.\par \par Dinis, Duarte, \'c2ngelo Palos Teixeira, and Ana Barbosa-P\'f3voa. "ForeSim-BI: A predictive analytics decision support tool for capacity planning." \i Decision Support Systems\i0 . 131 (2020): 113266.\par \par Dinis, D., A. P. Teixeira, and Guedes C. Soares. "Probabilistic approach for characterising the static risk of ships using Bayesian networks." \i Reliability Engineering & System Safety\i0 . 203 (2020): 107073.\par \par Dinis, Duarte, Ana Barbosa-P\'f3voa, and \'c2ngelo Palos Teixeira. "Valuing data in aircraft maintenance through big data analytics: A probabilistic approach for capacity planning using Bayesian networks." \i Computers & Industrial Engineering\i0 . 128 (2019): 920-936.\par \par }