Search Results (269)

This study proposes a barrier-oriented application of conventional failure mode and effects analysis (FMEA) and fuzzy weighted geometric mean (FWGM)-based fuzzy-FMEA for laboratory-scale solvent-based electrospinning. The process was decomposed into 14 sequential steps, and one representative failure mode was defined for each step. Severity, occurrence, and detection were rated by a five-member expert panel, and hazard-type-specific weights were assigned to chemical-dominant, electrical-dominant, fire/static-dominant, and combined-dominant hazards. Conventional FMEA identified material review/approval, equipment setup, pre-start inspection, and response to abnormalities as the highest-risk steps (RPN = 60). FWGM-based fuzzy-FMEA re-ranked tied RPN groups and identified response to abnormalities and equipment setup as the joint highest-FRPN failure modes (FRPN = 79.35), followed by pre-start inspection (77.39) and material review/approval (75.89). Barrier-oriented interpretation revealed four dominant mechanisms: upstream information-based hazards, direct high-voltage access, pre-start combined hazards, and intervention under abnormal or residual-energy states. Scenario-based post-control analysis showed that grounded enclosures, interlocks, de-energize-discharge-verify procedures, pre-start checklists, and bonding/grounding measures reduced FRPN by 25.88–43.79% for prioritized failure modes. The proposed framework supports SOP development, equipment improvement, training prioritization, and laboratory risk-assessment documentation for solvent-based nanofiber manufacturing. Full article

Failure Mode and Effects Analysis (FMEA) remains a fundamental risk management methodology in the automotive industry. This review provides a structured comparative analysis of the classical AIAG FMEA (4th edition, 2008) and the harmonized AIAG & VDA FMEA (1st edition, 2019) across Design (DFMEA), Process (PFMEA), and System (SFMEA) levels. Unlike conventional descriptive reviews, this study presents an integrative analytical synthesis that systematically evaluates methodological differences, decision-making logic, and structural transformations between the two frameworks. The analysis focuses on key developments, including the transition from Risk Priority Number (RPN) to Action Priority (AP), the introduction of a mandatory seven-step methodology, the formalization of structure–function–failure relationships, and enhanced traceability to downstream quality documentation such as Control Plans. The findings demonstrate that the harmonized framework represents a conceptual shift from a primarily scoring-based approach to a structured systems engineering methodology, improving consistency, completeness, and auditability of risk analysis. Particular emphasis is placed on the implications of AP-based prioritization, which alters traditional decision logic by preventing the suppression of safety-critical risks. The paper contributes to the literature by providing a comprehensive cross-level comparison (DFMEA–PFMEA–SFMEA) within a single analytical framework, identifying both strengths and limitations of the harmonized approach, and outlining its practical implications for industrial implementation. Future research directions include quantitative validation, application-based case studies, and integration with digital and AI-driven FMEA systems. Full article

Table olive processing comprises multiple stages in which physical, chemical, and biological hazards may occur. Although risk assessment is a core element of Hazard Analysis and Critical Control Points (HACCP) systems, the selection of assessment tools remains insufficiently standardized. This study compared a 4 × 4 risk matrix and Failure Mode and Effects Analysis (FMEA) for hazard evaluation in Spanish-style and Californian-style table olive processing. Hazards were assessed across 41 processing stages for Spanish-style olives and selected key stages for Californian-style olives using probability × severity in the 4 × 4 matrix and severity × occurrence × detection in FMEA. Significant hazards were further evaluated using the Codex Alimentarius decision tree to identify critical control points (CCPs) and strengthened prerequisite programs (PRPs). Both tools identified similar significant hazards, including biological hazards associated with fermentation, brine management, storage, container sealing, and heat treatment, as well as physical hazards from foreign bodies and chemical hazards related to heavy metals, pesticide residues, mycotoxins, and food-contact material migration. FMEA provided greater analytical detail through the detection parameter, whereas the 4 × 4 matrix was simpler and more practical for complex flow diagrams. Overall, both tools were suitable for HACCP-based risk assessment in table olive processing. Full article

LNG storage tanks are essential facilities for large-scale storage and transportation of cryogenic energy. Because of the flammable, explosive, and ultra-low-temperature characteristics of liquefied natural gas, failures in such systems may result in serious consequences for operational safety and the surrounding environment. Effective identification and prioritization of potential failure modes are therefore crucial for safe operation. Failure mode and effects analysis (FMEA) has been widely applied in risk assessment, yet conventional FMEA methods still show limited capability in describing uncertain linguistic evaluation information, reflecting the reliability of expert judgments, and representing high-order coupling relationships among failure modes. To address these issues, this study develops a modified FMEA framework that integrates confidence-enhanced probabilistic linguistic modeling with weighted hypergraph propagation for LNG storage tank risk assessment. In the proposed framework, confidence-enhanced probabilistic linguistic term sets are employed to represent the fuzziness, probabilistic preference, and reliability differences contained in expert assessments. A confidence-adaptive scoring function is further constructed to strengthen the discrimination of risk quantification by capturing structural differences in probability distributions without introducing externally specified parameters. Meanwhile, the importance of risk factors is determined through a combined subjective–objective weighting strategy, and a weighted hypergraph propagation mechanism is established to characterize high-order structural associations among failure modes and to revise baseline risk levels through a node–hyperedge–node transmission process. A case study of a large LNG storage tank system in Tangshan, China, is carried out to examine the applicability and effectiveness of the proposed framework. The results demonstrate that the proposed method can effectively integrate complex expert evaluation information with structural coupling effects, while sensitivity and comparative analyses further confirm its robustness and suitability for failure risk prioritization in LNG storage tanks. Full article

Tofu wastewater (TWW), characterized as a high-strength organic effluent with elevated chemical oxygen demand (COD) and low pH, presents significant environmental challenges, including eutrophication, soil degradation, and greenhouse gas emissions. Conventional disposal methods have proven inadequate in mitigating these risks; however, thermophilic anaerobic digestion (TAD) has emerged as a viable technology for bioenergy recovery. Nonetheless, TAD is impeded by rapid acidification, ammonia and hydrogen sulfide inhibition, and the accumulation of volatile fatty acids (VFAs). This review introduces nano-calcium-peroxide-modified biochar (nano-CaO₂/BC) as a multifunctional additive designed to establish an integrated framework for intervention, risk mitigation, and resource recovery. The proposed amendment synergistically combines the adsorptive and microbial-supportive properties of biochar with the controlled oxidative and alkaline characteristics of nano-CaO₂. Under thermophilic conditions, the slow hydrolysis of nano-CaO₂ generates transient microaerobic zones that enhance polymer hydrolysis, suppress ammonia (NH₃) and hydrogen sulfide (H₂S) formation, and facilitate the oxidation of inhibitory VFAs, concurrently releasing calcium hydroxide (Ca(OH)₂) for sustained pH buffering. Utilizing failure mode and effects analysis (FMEA) as a semi-quantitative assessment tool, the results indicate that the composite significantly reduces risk priority numbers associated with acidification, ammonia toxicity, and sulfide inhibition when compared with conventional TAD methods. The resultant digestates, which are enriched in nutrients and recalcitrant carbon, possess the potential to serve as valuable soil amendments, thereby contributing to a circular bioeconomy. A techno-economic assessment grounded in unit cost analysis suggests that positive net benefits may be realized through enhanced biogas recovery and the mitigation of environmental penalties. However, empirical validation at the pilot scale is essential to substantiate the projected performance. This review underscores critical knowledge gaps and proposes a systematic experimental framework aimed at translating the conceptual risk mitigation strategy into practical applications. Full article

Photovoltaic (PV) installations require maintenance prioritization models capable of ranking technically diverse failure modes under operational, safety, and serviceability constraints. Conventional Failure Mode and Effects Analysis (FMEA) approaches often cannot integrate downtime, cost, safety, and detectability into a single transparent workflow. This study develops a hybrid Particle Swarm Optimization (PSO)-FMEA-VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) framework for maintenance prioritization of eight representative PV failure modes. Classical FMEA was used as a diagnostic baseline, a seven-criterion maintenance matrix was constructed, PSO calibrated criteria weights, and a criticality-oriented VIKOR compromise-ranking procedure generated the final ordering. Semi-empirical operational and service log evidence was used only to anchor the interpretation of occurrence, direct cost, and downtime; it was not treated as a real-time fault-detection dataset. The results identified inverter overvoltage shutdown/grid incompatibility, cable insulation degradation, and junction box overheating as the highest maintenance priorities. Their ordering differed from classical Risk Priority Number (RPN) results, showing that frequency alone does not adequately represent maintenance urgency. Sensitivity analysis confirmed the stability of the two leading alternatives under different VIKOR strategy parameters. The framework provides a discriminative decision support tool for inspection planning, service scheduling, and corrective-action targeting in grid-connected PV systems, while further validation on larger Supervisory Control and Data Acquisition (SCADA)- or inverter-log-based datasets remains necessary. Full article

Scaffold-related falls remain a major safety concern in demolition projects, where temporary access systems are frequently erected, modified, used, and dismantled under changing structural and site conditions. These characteristics complicate risk prioritization because scaffold failures may involve interacting human, technical, organizational, and environmental factors. This study develops an expert-based risk prioritization framework for scaffold-related fall risks in demolition projects by integrating Failure Mode and Effects Analysis (FMEA), interval neutrosophic fuzzy (INF) theory, Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Multi-Attributive Border Approximation Area Comparison (MABAC). Using the 4M1E perspective, namely Man, Machine, Material, Method, and Environment, 37 demolition-specific failure modes were identified through literature review and expert elicitation. Ten experts evaluated these failure modes using the SODE criteria, namely Severity, Occurrence, Detection difficulty, and Expected Cost impact. INF theory was used to represent uncertainty, hesitation, and judgmental variation in expert assessments. INF-DEMATEL was applied to examine interrelationships among the SODE criteria and derive interdependence-aware criterion weights, while INF-MABAC was used to rank the failure modes according to their distance from the Border Approximation Area. The framework was illustrated through an empirical application in Taiwan’s demolition industry. The results identified Severity as the most influential criterion. The highest-priority failure modes were insufficient safety awareness, improper scaffold-to-structure anchoring, and inadequate scaffold maintenance and inspection governance. Comparison with risk priority number (RPN)-based methods and sensitivity analyses using expert exclusion and Severity-weight variation showed that the ranking was generally consistent and reasonably stable under the tested conditions. The proposed framework provides a structured, uncertainty-aware decision-support procedure for identifying prevention priorities in demolition scaffold operations. Full article

The operation of medical cyclotrons for PET radiopharmaceutical production presents significant radiological and environmental challenges that require systematic risk assessment and evidence-based mitigation strategies. In this study, an integrated framework combining Failure Mode and Effects Analysis (FMEA) with a quantitative Defense Effectiveness Factor (DEF) approach to evaluate and reduce residual risk in a real urban cyclotron facility. High-criticality failure modes (Risk Priority Number $\ge 120$) affecting HVAC systems, stack exhaust, and power supply were identified and validated through a Delphi expert consensus process. These modes were addressed with multi-layered defense-in-depth strategies: redundant systems (occurrence reduction, 60–80% effectiveness), real-time monitoring (detection reduction, 40–50% effectiveness), and design robustness (severity reduction, 70–85% effectiveness). The combined DEF yielded a 96–97% risk reduction. One-way sensitivity analysis confirmed the robustness of these results, with residual annual effective dose to the representative person remaining between 50–88 μSv/year (well below the IAEA 1 mSv/year public dose constraint) even under pessimistic scenarios. Primary exposure pathways were inhalation and cloud gamma from ¹⁸F and ⁴¹Ar during the early-morning production window, while secondary pathways were negligible due to the short half-lives of the radionuclides. These findings demonstrate that the integration of FMEA with DEF-based defense-in-depth and Gaussian plume modeling provides a transparent, robust, and regulatory-compliant framework for managing radioactive atmospheric emissions in urban medical cyclotron facilities. Full article

Heavy industrial vehicles operating in aluminum smelters are exposed to severe thermal, mechanical, and environmental stresses, which increase the likelihood of failure and unplanned downtime. This study proposes an Economic Risk Priority Number (ERPN) framework to address the limitations of the conventional Risk Priority Number (RPN) used in Failure Mode and Effects Analysis (FMEA). A five-year maintenance dataset (2019–2024), comprising 2303 corrective work orders from 58 heavy equipment units, was analyzed. The classical RPN approach prioritized failure modes mainly according to occurrence and detectability, identifying the wheel and hydraulic subsystems as the most critical. In contrast, the proposed ERPN framework integrates economic impact through maintenance cost, manpower cost, and production loss, resulting in the engine subsystem being ranked as the most critical. The most severe engine failure caused an estimated financial loss of approximately USD 1.92 million due to extended downtime and repair costs. Root cause analysis identified coolant loss, low oil pressure, and excessive vibration as the main contributors to catastrophic engine failure, supported by diagnostic evidence and repeated alarm patterns. Statistical validation performed using the Kruskal–Wallis test confirmed significant differences among subsystem risk distributions for both RPN (χ² = 846.07, df = 4, p < 0.0001) and ERPN (χ² = 131.69, df = 4, p < 0.0001). The findings demonstrate that ERPN provides a more economically meaningful framework for maintenance prioritization and offers a practical decision-support tool for reducing operational risk in aluminum smelter fleets. Full article

Autonomous navigation technologies have been widely adopted in the automotive and aviation sectors, significantly reducing human-error-induced accidents and operational costs. However, their application to maritime systems remains limited due to the complexity of conventional propulsion systems. Electric propulsion ships, with well-defined system boundaries and accessible operational data, offer a promising platform for autonomous navigation. In this study, we propose an FMEA-guided selective multi-fidelity digital twin framework for fault detection, where model fidelity is adaptively selected between low- and high-fidelity models based on risk priority numbers derived from failure mode and effects analysis. This approach enables selective execution of computationally expensive models only under high-risk conditions, thereby improving computational efficiency. In addition, a sliding window-based algebraic aggregation method is employed to achieve lightweight and real-time fault diagnosis. The proposed framework is validated using operational sensor data from a 100 kW electric propulsion ship under multiple fault scenarios, including power supply faults and signal anomalies. Experimental results show that the proposed method reduces computational cost while maintaining stable real-time performance, compared to conventional data-driven AI-based approaches. These results demonstrate that the proposed framework provides an effective and efficient solution for enhancing the reliability and safety of autonomous ship systems. Full article

The study aimed to develop a mucoadhesive thermosensitive buccal gel capable of forming an artificial clot after application in the extraction socket and providing prolonged release for metronidazole (MZ) and ibuprofen (IB). The critical quality attributes of the product were systematically evaluated using Ishikawa (cause–effect) diagrams as a risk assessment tool, considering the factors related to the formulation, process, and methodology. Subsequently, Failure Mode and Effects Analysis (FMEA) was used to identify the critical parameters of the formulation and process characterized by a high probability of occurrence and a significant impact on product performance. The influence of qualitative and quantitative formulation variables was further investigated using two experimental designs, applied for both screening and optimization purposes. The rheological, adhesion, and in vitro release properties of the drugs were studied, and the optimized formulation for these characteristics contains Poloxamer 407 20.99% and HPMC K100M:K4M 1:1, 0.74%. The release of MZ and IB was prolonged over 8 h and followed Peppas’s kinetics. The optimized formula had an appropriate pH and an acceptable ex vivo mucoadhesion time. Stability studies revealed the preservation of mechanical properties and a recovery coefficient for MZ and IB of over 90%, after 12 months of storage. The optimized formula may be a potential candidate for the prevention of alveolar osteitis. Full article

This study presents a comparative Failure Modes and Effects Analysis (FMEA) of electro-hydraulic braking (EHB) and electro-mechanical braking (EMB) systems within brake-by-wire architectures. The analysis integrates both the conventional Risk Priority Number (RPN) approach and the AIAG–VDA Action Priority (AP) methodology, enabling a structured comparison of risk prioritization strategies applied to identical failure modes. A consistent system-level framework is developed to harmonize severity (S), occurrence (O), and detection (D) assessments across both architectures, allowing direct evaluation of methodological differences. The results demonstrate systematic divergences between RPN and AP approaches, particularly in high-severity scenarios, where AP provides more safety-oriented prioritization. The study further identifies key limitations of traditional RPN-based evaluation in safety-critical systems and highlights the advantages of rule-based prioritization frameworks. In addition, corrective measures are proposed and their impact on occurrence and detection ratings is quantified, illustrating practical pathways for risk reduction. Beyond methodological comparison, the work introduces a novel integration of reliability engineering with advanced manufacturing strategies, demonstrating how laser and plasma-based surface engineering can mitigate failure mechanisms by reducing occurrence and improving system robustness. The proposed approach establishes a conceptual and physically grounded bridge between system-level risk assessment and material-level optimization, contributing to the development of more reliable next-generation brake-by-wire systems. Full article

This study provides a practical and replicable improvement model for productivity and inspection reliability improvement in resource-constrained food logistics environments. This study presents an engineering-based optimization of productivity and process reliability in an agro-industrial post-harvest processing system for canned young green jackfruit using an integrated Define–Measure–Analyze–Improve–Control (DMAIC) and Failure Mode and Effects Analysis (FMEA) framework. The case-study production system experienced high raw-material loss, prolonged blanching cycles, and low inter-operator inspection agreement, which reduced process yield and logistics throughput. Root causes were identified through process mapping and fishbone analysis and prioritized using FMEA Risk Priority Number (RPN) scoring. Key improvement actions included optimizing blanching time, standardizing supplier grading to reduce material variability, and strengthening inspection decisions through Attribute Gage Repeatability and Reproducibility (Gage R&R)-based training and criteria alignment. After implementation, productivity increased by 2.31%, raw-material loss decreased by 1.90%, and inter-operator inspection agreement improved by 16%, exceeding the benchmark. Blanching time was reduced from 3 to 1 min at ≥90 °C, shortening cycle time by 67% and generating an estimated annual cost saving of USD 7200 without major capital investment. The results demonstrate that structured, risk-based improvement combined with validated measurement systems can enhance workforce consistency, process stability, and logistics flow efficiency in agro-industrial food processing environments, providing a replicable improvement model for agro-industrial processing small and medium-sized enterprises (SMEs). Full article

Rotary kiln-based activated carbon production combines high-temperature operation with flammable/reducing gases, carbonaceous dust, and downstream off-gas treatment and acid/base washing, creating complex escalation pathways. This study prioritizes safety improvements by applying classical failure modes and effects analysis (FMEA) and a transparent Fuzzy-FMEA framework to 18 representative failure modes (six each for kiln/activation, acid/base handling, and atmosphere/control). Five experts evaluated Severity, Occurrence, and Detection on a 10-point scale. The fuzzy model used triangular membership functions (L/M/H), a monotonic 27-rule base, Mamdani max–min inference, and centroid defuzzification to compute a continuous fuzzy risk priority number (FRPN, 0–10). Classical FMEA identified dust explosion (RPN = 405), temperature control failure (RPN = 378), and off-gas leakage (RPN = 324) as the highest-ranked risks. Fuzzy-FMEA preserved the top-risk group while more strongly highlighting barrier-related risks, placing off-gas leakage, instrumentation/interlock failure, and electrostatic ignition control alongside dust explosion (FRPN 9.221–9.332). The rankings were strongly correlated (Spearman ρ = 0.871; Kendall τ = 0.752), yet mid-risk items were rearranged (mean |Δrank| = 2.06; max = 5), improving discrimination within tied RPN clusters. The five highest-priority scenarios were reconstructed into actionable engineering packages, including dust and ignition control, off-gas integrity linked to shutdown logic, interlock proof testing and bypass management, and independent protection layers for kiln temperature control. Full article

It is inconceivable that an unsafe mode of transport could be sustainable. Therefore, in this century, where sustainability is at the forefront, occupational health and safety is more important than ever. However, the most used traditional risk analysis methods cannot be applied to every area due to their shortcomings. In this study, a new proposal of interval-valued intuitionistic fuzzy failure mode and effects analysis (IVIF FMEA) within the framework of fuzzy logic overcomes the inadequacies of the traditional method, particularly in uncertainty assessment. In this proposed IVIF FMEA method, the effects of historical incident data are incorporated to improve risk prioritization through static decision-maker weighting and dynamic risk parameter weighting. Then, this novel method is implemented for the operational risks of the underground stations within a metropolitan city in Türkiye. When the proposed method is compared with traditional FMEA and classical IVIF FMEA, failure modes (FMs) related to platform surveillance, working at height, and chemical handling are identified as requiring priority action. To ensure safer and more sustainable transport operations, the prioritization of safety measures is as important as their implementation. The obtained results further offer a transferable and methodologically robust basis for advancing sustainability-oriented safety governance by enabling more evidence-based risk prioritization within urban transportation systems. Full article