Composite Hybrid Framework for Through-Life Multi-Objective Failure Analysis and Optimisation

Abstract

Complex engineering systems include several subsystems that interact in a stochastic and multifaceted manner with multiple failure modes (FMs). The dynamic nature of FMs introduces uncertainties that negatively impact the reliability, risk, and maintenance of complex systems. Traditional approaches of adopting standalone techniques for managing FMs independently at various stages of the asset life cycle pose challenges related to utilisation, costs, availability, and in some cases, accidents. Therefore, this paper proposes a composite hybrid framework comprising four independent hybrid models for comprehensive through-life failure management and optimisation. The first hybrid model entails failure mode, effects, and criticality analysis (FMECA) and fault tree analysis (FTA) to identify critical FMs and overall subsystem failure rates. The second hybrid model analyses FMs caused by multiple subsystems using hybrid dynamic Bayesian discretisation. The third hybrid model adopts a hybrid Gaussian process regression machine learning technique to evaluate wear loss. The fourth hybrid model evaluates the overall risk using a Bayesian factorisation and elimination method based on multiple failure causes. Finally, a decision-making step is used to evaluate the results of the previous four steps to decide an appropriate maintenance strategy. The proposed method is verified through a case study of a UK-based train operator's pantograph system. The results show that the maintenance inspection intervals and strategy obtained using the proposed framework strike a good balance between safety and fleet availability.

Optimization of surface roughness in milling of EN 24 steel with WC-Coated inserts using response surface methodology: analysis using surface integrity microstructural characterizations

“…The contour plot is a 2D depiction of the response plotted against numeric factors and mixed component combinations (Appoh and Yunusa-kaltungo, 2021;Yang et al, 2023a;Balali et al, 2023). It can illustrate the link between responses, mixture components, and numerical variables.…”

“…The EN 24 steel is widely employed in numerous engineering uses whereby components need the ability to sustain substantial loads and demonstrate resilience against wear, fatigue, damage, and strain (Appoh and Yunusa-kaltungo, 2021;Wu et al, 2022;Tang et al, 2023). The investigation concentrates around the optimisation of surface roughness in the machining process of EN 24 steel, that's a material extensively employed across several sectors.…”

Development of a New Risk Assessment Methodology for Light Goods Vehicles on Two-Lane Road Sections

“…The findings of these studies are limited by drivers' behavior, the quality of the infrastructure present, and the characteristics of the traffic. In practice, risk management is the basis for eliminating a potential adverse event [18][19][20][21][22].…”

Assessment of safety climate perception of maintenance workers during major overhauls, outages, shutdowns or turnarounds (MoOSTs)

“…), which heighten risks of accidents 24 and costs. [25][26][27] Additionally, MoOSTs are often performed over very short time frames thereby necessitating parallel implementation of several activities by different organisations (e.g., client, regulators for statutory inspections, contractors, sub-contractors, original equipment manufacturers, vendors, etc.) that often have different perceptions of safety as well as possess different safety cultures.…”

“…MoOSTs are significant integrations of regular maintenance activities (e.g., design, planned preventive maintenance, condition based maintenance, plant expansions, reactive maintenance, derating, decommissioning, renewal, upgrades, etc. ), which heighten risks of accidents 24 and costs 25–27 . Additionally, MoOSTs are often performed over very short time frames thereby necessitating parallel implementation of several activities by different organisations (e.g., client, regulators for statutory inspections, contractors, sub‐contractors, original equipment manufacturers, vendors, etc.)…”