Optimal reliability allocation of heterogeneous components in pharmaceutical production plant

The COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed to be as reliable as possible. The present paper aims to optimize the design of a pharmaceutical plant through the reliability allocation of heterogeneous components under the design constrain...

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Detalles Bibliográficos
Autores principales: Aqel, Ibrahim, Mellal, Mohamed Arezki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Paris 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975440/
http://dx.doi.org/10.1007/s12008-023-01256-1
Descripción
Sumario:The COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed to be as reliable as possible. The present paper aims to optimize the design of a pharmaceutical plant through the reliability allocation of heterogeneous components under the design constraints. The problem is solved by resorting to three nature-inspired algorithms of artificial intelligence (AI): grey wolf optimizer (GWO), shuffled frog-leaping algorithm (SFLA), and adaptive particle swarm optimization (ADAP-PSO). A penalty function is implemented to handle the constraints and the results obtained are compared. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12008-023-01256-1.

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