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ORIGINAL PAPER
Fault Prediction Of Pharmaceutical Air Compressor Using The Intelligent Model Based On The Bayesian Network
1
Mechanical Engineering, M'Hamed Bougara Boumerdes University, Algeria
Submission date: 2023-09-24
Final revision date: 2024-04-03
Acceptance date: 2024-11-15
Online publication date: 2025-06-13
Publication date: 2025-06-13
Corresponding author
International Journal of Applied Mechanics and Engineering 2025;30(2):20-30
KEYWORDS
Bayesian networkArtificial intelligencePharmaceutical standard requirementsAir compressor (Oil free)Industrial diagnosis and prognostic
TOPICS
ABSTRACT
This paper presents a new approach of diagnosis and prognostic in real-time of strategic equipment of pharmaceutical industry. This approach is developed using Bayesian network (BN) which consider industrial data and feedback experience. The objective is to detect, locate and prevent any malfunction of the air compressor (oil-free) without air contamination, dedicated to pharmaceutical industry, BEKER Laboratories (Dar El Beida-Algeria). The study is based on the functional analysis of the air compressor to obtain the fault tree (FT). This FT is transformed into BN to diagnose automatically the compressor and prevent any malfunctioning.
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