Keywords :
comparative functional dynamics; energy-based maintenance; functional-productiveness; hydraulic systems; machine learning; predictive maintenance; Energy utilization; Hydraulic machinery; Machine learning; Comparative functional dynamic; Dynamic process; Energy-based; Energy-based maintenance; Energy-consumption; Functional-productiveness; Hydraulic system; Maintenance paradigms; Maintenance practices; Predictive maintenance; Maintenance
Abstract :
[en] As a consequence of accepting the Green Deal initiative, sustainable maintenance attracted significant attention. However, observation of low market intelligence and lack of sustainable goal-oriented practice has been reported. The article proposes the Energy-Based Maintenance (EBM) paradigm to fulfil the needs of sustainable manufacturing philosophy. The EBM implicitly consists of two concepts: Functional Productiveness (FPC) and Comparative Functional Dynamics (CFD). Namely, the core of FPC is to propose a new view in understanding the nature of functionality by delineating static (maintenance) events (e.g., total failure, stoppage, etc.) from dynamic (process) events (e.g., quasi-faults, leakage, degradation). The CFD uses FPC and dynamic (process) events and acts as a catalyst in reducing noise in feature extraction by comparing system dynamics and energy consumption. Demonstration on a case study of proposed EBM practice is conducted and used as a measure of comparison with traditional maintenance practices (policies). However, the results show a reduction in oil waste and energy consumption at the cost of increasing inspection and stoppages. © 2021 IEEE.
Scopus citations®
without self-citations
2