A Novel Remaining Useful Estimation Model to Assist Asset Renewal Decisions Applied to the Brazilian Electric Sector
Hemir da Cunha Santiago,
José Carlos da Silva Cavalcanti,
Ricardo Bastos Cavalcante Prudêncio,
Mohamed A. Mohamed,
Leonie Asfora Sarubbo,
Attilio Converti,
Manoel Henrique da Nóbrega Marinho
Affiliations
Hemir da Cunha Santiago
Polytechnic School, University of Pernambuco (UPE), Recife 50720-001, PE, Brazil
José Carlos da Silva Cavalcanti
Informatics Center, Federal University of Pernambuco (UFPE), Recife 50740-560, PE, Brazil
Ricardo Bastos Cavalcante Prudêncio
Informatics Center, Federal University of Pernambuco (UFPE), Recife 50740-560, PE, Brazil
Mohamed A. Mohamed
Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia 61519, Egypt
Leonie Asfora Sarubbo
Department of Biotechnology, Catholic University of Pernambuco (UNICAP), Recife 50050-900, PE, Brazil
Attilio Converti
Department of Civil, Chemical and Environmental Engineering, University of Genoa (UNIGE), Pole of Chemical Engineering, Via Opera Pia 15, 16145 Genoa, Italy
Manoel Henrique da Nóbrega Marinho
Polytechnic School, University of Pernambuco (UPE), Recife 50720-001, PE, Brazil
Assets deteriorate over time, as well as being covered, corroded, or becoming old in less obvious ways. Maintenance can extend the remaining useful life (RUL) of an asset system, but sooner or later it must surely be replaced. In this study, we propose a new RUL estimation methodology to assist in decision making for the maintenance and replacement of assets from prioritizing equipment in a renovation plan. Our methodology uses advanced data analysis techniques that consider multiple competing criteria with the goal of maximizing values of the asset throughout its life cycle, while considering the rules of remuneration and service quality of the current regulation, as well as the values at risk according to the decisions and actions taken. Experimental results with real datasets show the efficiency of the proposed approach. Finally, this work also presents the development of an analytical tool to optimize asset renewal decisions applying the RUL estimation methodology proposed and its application to the Brazilian electric sector.
