Conventional Failure Mode Research Articles

A hybrid failure analysis model design for marine engineering systems: A case study on alternative propulsion system

Marine engineering systems have a fundamental role in ensuring the efficiency, safety, and sustainability of maritime transportation. The performance and reliability of these systems, particularly propulsion systems, are of paramount importance. This paper introduces a pioneering hybrid failure analysis model that integrate the Variable Weighted Synthesis Analytic Hierarchy Process (VWS-AHP) with the conventional Failure Mode and Effect Analysis (FMEA) methodology. The primary objective is to enhance the comprehension of failure modes within marine engineering systems, particularly focusing on alternative propulsion systems. While conventional FMEA is a widely employed methodology for analysis of failure modes, its capacity and effectiveness can be further augmented by integrating complementary techniques. The proposed hybrid model combines the robustness of FMEA in identifying failure modes with the VWS-AHP method’s ability to handle complex decision-making scenarios involving multiple criteria and varying levels of importance. This integration affords a comprehensive framework to assess failure risks, prioritize critical failure pathways, and evaluate the potential impacts of failures in marine engineering systems. To demonstrate the applicability of the proposed model, we conduct a case study on an alternative propulsion system. The outcomes of the case study showcase the efficacy of the hybrid model in enhancing FMEA.

Degradation behavior of yttria-stabilized zirconia in thermal barrier coatings under reducing environments after short-term heat treatment

The gradual transition of hydrogen as a fuel for land-based gas turbines has resulted in direct changes to the combustion environment. The inadequate combustion of hydrogen fuel can lead to a transition from an oxidizing environment to a partially reducing environment, and further introduces a new potential failure mode for existing thermal barrier coating materials. In this study, tests were conducted on thermal barrier coating samples at 1000 °C in Ar + 5 % O2 and Ar + 5 % H2 environments, in addition to samples subjected to heat-treatment in pure argon and air environments to provide a comparison against low oxygen partial pressure and conventional failure modes. The results demonstrated that the degree of sintering of the top coat decreased gradually with a decreasing oxygen partial pressure, and was significantly inhibited in a reducing environment. Faster cooling rates led to the expansion of vertical cracks in the top coat toward the interface, which was accompanied by the generation of numerous transverse cracks in the reducing environment. In contrast, the structure of the top coat remained intact in the other three environments. Furthermore, effective methods for improving the coating durability in reducing environments are discussed. This study therefore contributes to a comprehensive understanding of the failure behavior of thermal barrier coatings in reducing environments, providing new insights into enhancing the stability under such conditions.

A hybrid integrated multi-criteria decision-making approach for risk assessment: a study of automotive parts industry

PurposeThis paper aims to enable the analysts of reliability and safety systems to evaluate the risk and prioritize failure modes ideally to prefer measures for reducing the risk of undesired events.Design/methodology/approachTo address the constraints considered in the conventional failure mode and effects analysis (FMEA) method for criticality assessment, the authors propose a new hybrid model combining different multi-criteria decision-making (MCDM) methods. The analytical hierarchy process (AHP) is used to construct a criticality matrix and calculate the weights of different criteria based on five criticalities: personnel, equipment, time, cost and quality. In addition, a preference ranking organization method for enrichment evaluation (PROMETHEE) method is used to improve the prioritization of the failure modes. A comparative work in which the robust data envelopment analysis (RDEA)-FMEA approach was used to evaluate the validity and effectiveness of the suggested approach and simplify the comparative analysis.FindingsThis work aims to highlight the real case study of the automotive parts industry. Using this analysis enables assessing the risk efficiently and gives an alternative ranking to that acquired by the traditional FMEA method. The obtained findings offer that combining of two multi-criteria decision approaches and integrating their outcomes allow for instilling confidence in decision-makers concerning the risk assessment and the ranking of the different failure modes.Originality/valueThis research gives encouraging outcomes concerning the risk assessment and failure modes ranking in order to reduce the frequency of occurrence and gravity of the undesired events by handling different forms of uncertainty and divergent judgments of experts.

Experimental and numerical investigation of the relationship between material defects and elastoplasticity behavior of 3D-printed carbon-fiber-reinforced thermoplastics under compressive loading

In this study, the compressive properties of 3D-printed carbon-fiber-reinforced thermoplastics (3DP-CFRTPs) were experimentally and analytically investigated. Non-hole compression (NHC) and cross-ply open-hole compression (OHC) experiments were conducted to investigate their material properties and damage initiation and propagation. The results of OHC tests at different open hole diameters were divided into "delamination buckling," a conventional failure mode, and "layer buckling," a failure mode that does not lead to complete rupture. In the numerical analysis, a novel periodic cell (PUC) model was developed that considers fiber waviness and voids to analyze nonlinear behavior, including elastoplasticity. The PUC analysis results for the 45° and 90° samples predicted the equivalent stiffness with high accuracy and reproduced the nonlinear behavior well. Sensitivity analysis with material defects (fiber waviness and voids) as variables showed that the voids decreased the elastic modulus and promoted plastic deformation. In contrast, fiber waviness significantly decreased the elastic modulus in the fiber direction, slightly increased the shear properties, and suppressed plastic deformation. Moreover, sensitivity analysis of the mesoscale analysis suggested that "layer buckling" occurs when fiber waviness and voids are considered, which may be a unique failure mode for 3DP-CFRTPs.

An integrated fuzzy-FMEA risk assessment approach for reinforced concrete structures in oil and gas industry

The oil and gas industry is one of the harshest environments on reinforced concrete structures. Enhancing the reliability of these industries has been identified as a critical goal to meet anticipated production targets and maintain competitiveness. The purpose of this paper is to rank and prioritize risk factors on reinforced concrete structural systems in the oil and gas industry to reduce failures and improve system reliability. The risk factors influencing reinforced concrete systems are identified based on the experts interviewed who specialized in risk analysis. In this paper, a risk assessment approach based on a hybrid fuzzy failure mode and effect analysis is developed in order to rank the factors and improve the process of reinforced concrete maintenance prioritization. The developed approach is also compared with the other two methods; namely, conventional failure mode and effect analysis (FMEA) and grey rational analysis (GRA) integrated with FMEA. The three developed approaches are designed to acquire the highest risk priority number (RPN) values; conventional RPN, GRA-FMEA RPN, and Fuzzy-FMEA RPN. These values will be utilized as the focus of improvements to reduce the possibility of some kind of failure occurring a second time and improve the deteriorated reinforced concrete structure to minimize the likelihood of failures. The results revealed that high-risk systems include the compression train, steam turbine, and combustion gas turbine generator, while the majority require maintenance of the supporting concrete foundation as soon as second-degree deterioration occurs. Furthermore, the results indicated that the Fuzzy FMEA approach was appropriate for assessing deteriorated reinforced concrete structures.. This work represents a step forward in the development of a tool that can be used to assess the risk of degraded concrete structures and improve their integrity through proper monitoring and maintenance.

Updating the FMEA Approach with Mitigation Assessment Capabilities—A Case Study of Aircraft Maintenance Repairs

This paper proposes a qualitative model to overcome the limitations of conventional failure mode and effects analysis (FMEA), which does not consider risk mitigation capabilities when prioritizing risks. Failure to consider these capabilities can lead to unrealistic risk estimates, especially when the level of uncertainty is high. In the proposed model, the original applicability of conventional FMEA was retained along with the three conventional risk variables, namely, severity, occurrence, and detectability. In addition, a fourth variable was added to account for risk mitigation capabilities. A case study in the project selection of aircraft repairs was used to demonstrate the implementation of the model and its applicability. The results show that the inclusion of mitigation options leads to more realistic risk scenarios, suggesting that the original FMEA approach may lead to non-conservative risk estimates.

Predicting failure modes of 3D-printed multi-material polymer sandwich structures from process parameters

The emergence of additive manufacturing (AM) technologies, such as fused deposition modeling (FDM), have enabled the realization of structures with superior mechanical performance through lightweighting and multi-material architectures. However, the complexity associated with the internal geometric features and potential material configurations have also presented new challenges in designing these structures to optimize mechanical performance. In particular, the failure mechanisms and their relationship to the load bearing capacity of the structures may vary compared to analogous structures designed using conventional manufacturing techniques. In this work, we investigate failure modes of 3 D-printed (3DP) multi-material polymer sandwich beam structures manufactured from acrylonitrile butadiene styrene (ABS) and polycarbonate (PC) materials and subjected to three-point bend loading. Digital Image Correlation (DIC) is utilized to understand the effects of different process parameters on the mechanical response of the 3DP structures. ABS and PC dogbone tensile specimens were printed to establish the baseline properties in tension with varying raster angles and infill patterns. Multi-material sandwich beam structures were then printed with honeycomb cores using different processing and architectural parameters, and the failure modes and loads of these structures were compared with predications from a failure model for sandwich structures that accounts for the following conventional failure modes: (1) indentation, (2) face sheet bending, (3) core bending, and (4) core shear. With minor changes in the processing and geometric parameters, failure modes could be shifted from the face sheets to core bending and core shear, as evidenced by the DIC strain field measurements, and the corresponding max load-to-weight ratios could be increased. Estimations of the tensile properties of the face sheets and core were found to be sufficiently accurate when combining classical lamination theory (CLT) and rule-of-mixtures (ROM) models, while the failure model also predicted the load bearing capacity and failure mode in three-point bending with reasonable accuracy.

Fuzzy FMECA for CNC machine tool spindle system

The spindle systems of the state-of-the-art computer numeric controlled (CNC) machine tools are increasingly important than ever, for that the even distinguished demand of higher efficiency, reliability, and productivity of today’s manufacturing industry lead to the aforementioned system works under higher rotational speed and higher cutting performance. This paper extended the conventional failure modes, effect and criticality analysis by integrating which with fuzzy theory to finitizing a failure analysis of an electric spindle system of a CNC machine tool aims to avoid unwanted failures of the system and achieve safe and reliable operation of the device. Critical components, critical failure modes of the spindle system that call for special attention are ascertained. Root causes of the critical failure modes as well as recommendations e.g. periodical inspection of the bearings as well as robust design for electrical and electronical complements for avoiding their occurrence are obtained.

Influence of central and peripheral dentin on micro-tensile bond strength estimated using a competing risk model

The bonding performance of dental adhesives is most frequently evaluated using the micro-tensile bond strength (μTBS) test. Despite lacking evidence, peripheral specimens are often discarded to avoid regional variability. This study, therefore, examined whether μTBS to central and peripheral dentin differed. Dentin surfaces of extracted human molars were bonded with various self-etch adhesives, built up with a resin composite, cut into beams, and stressed in tension. Failure mode was classified as adhesive, cohesive in dentin, or other using scanning electron microscopy. Since cohesive failures in dentin were frequent and could confound μTBS results, the data from central/peripheral dentin were analyzed using a Weibull competing risk (CR) model distinguishing failure modes, and its outcomes were compared to a conventional failure mode non-distinguishing Weibull model. Based on the strength data of cohesively failed specimens, the CR model also estimated the strength of dentin. For comparison, the ultimate tensile strength (UTS) of dentin was measured in both regions. The conventional model suggested that peripheral μTBS was higher than central μTBS. Conversely, the CR model disclosed no significant difference in μTBS between the regions but indicated a higher strength of peripheral dentin. This finding was confirmed by UTS measurements, and further supported by the significantly higher incidence of cohesive failures in central dentin. Therefore, peripheral specimens can be used in the μTBS test as well as central ones, but a CR model should be used for statistical analysis if cohesive failures in dentin are frequent, as the strength of peripheral dentin is higher.

Proposal of a Validation Method of Failure Mode Analyses based on the Stress-Strength Model with a Support Vector Machine

This study aims at developing a validation method for the rational association between the design deviations, possible damage/fracture modes, and the eventual failure modes using SVM. Product failures due to damage/fracture modes of materials have recently increased, which suggests the importance of proactive prevention by failure modes analyses. Conventional Failure Modes and Effects Analyses (FMEA) lacks a specific process in determination of possible damage/fracture of component’ s materials. A modified Design Review Based on Failure Modes (DRBFM) or Design Deviation Method (DDM) were proposed to determine failure modes induced by damage/fracture modes of materials by possible associations from deviations in design/environmental factors to the deteriorations in stress-strength model. These methods still remain the possible errors in selection of rational damage/fracture modes to complicated patterns of design deviations, which suggests the importance of validation on the result of failure modes analyses. The procedure of DDM was formulated using sparse matrix and then analyzed using multi-class determination by Support Vector Machine(SVM). A case study of failure modes analyses to a laser-irradiation device using FMEA, DRBFM, the proposed DDM were conducted by individual three groups which had same number of 7 participants. The participants in the DDM group could predict more failure mechanisms by damage/fracture modes of materials than those by the DRBFM and FMEA groups. Furthermore, SVM showed higher precision rate from 77% to 100%, which evaluated the validity of specific failure modes. The SVM could determine the rational associations among the design deviations, the deviations in the SSM, and the corresponding damage/fracture modes.

A competing risk model for bond strength data analysis

ObjectivesA competing risk (CR) model distinguishing adhesive, cohesive and mixed failures as competing events was used for the analysis of micro-tensile bond strength (μTBS) data and compared with a conventional failure mode non-distinguishing survival model. MethodsFifty human molars were bonded using five universal adhesives (n = 10) and subdivided according to aging conditions (24-h water storage, thermocycling). After μTBS to dentin was tested, a fractographic analysis was performed using scanning electron microscopy. Survival analyses of the μTBS data were performed using both a failure mode distinguishing Weibull CR model, and a conventional failure mode non-distinguishing Weibull model. Weibull shape (m) and scale (σθ) parameters were calculated for both models using the maximum likelihood estimation method, and strength at 10 % probability of failure, σ0.10, was estimated. Groups were compared using 95 % confidence intervals. ResultsCR-model estimates of σθ and σ0.10 for adhesive failures were higher than those of the conventional model, more markedly in groups with lower percentages of adhesive failures. CR-model strength estimates for cohesive failures were similar in all groups regardless of their bond strengths and failure mode distributions. SignificanceMerging all bond-strength data into one dataset irrespective of the failure mode may result in a severe underestimation of bond strength, especially in groups with low incidence of adhesive failures. Bond-strength data analysis using a CR model could provide more accurate estimates of bond strength, and strength estimates for cohesive failures which were apparently independent of bond strength could serve as an internal validity indicator of the CR model.

A developed failure mode and effect analysis for floating offshore wind turbine support structures

This paper extends the conventional failure mode and effect analysis methodology by introducing weights of its indices that are severity, occurrence, and detection as a basis to analyze the failures of the support structure of a generic floating offshore wind turbine. Critical failure causes, failure modes, as well as systems of the support structure of the floating offshore wind turbine are ascertained. Moreover, based on the analysis, recommendations on corrections and preventive actions are suggested aiming at ensuring the safe and economic operations of the support structure. The validation of the proposed technique is finalized by a comparison study between the results of conventional failure mode and effect analysis methodology and that of the proposed method. The comparison indicates that the proposed technique is more in line with practice and flexible for use and has the merit in removing the limitations of conventional failure mode and effect analysis methodology that different failure causes generate the same risk priority number.

A Method for Determining Failure Modes Associated with Damage/Fracture of Materials in Early Design Stages

This study aims at developing an analysis method for failure mode relating to material properties by considering simulated design specifications of a functional model. The proposed method contains the following procedures: (1) developing a simulated design specification of a functional model, (2) performing failure mode analyses by inserting deviation patterns into the design specifications and (3) identifying failure modes and root cause analysis to identify failure causes relating to material properties. The proposed procedure was applied in a pilot study using a simplified laser irradiation machine. The group who used the proposed model, which is based on design review based on failure modes, showed a higher rate of success in people detecting material-relating causes, compared with the group who used conventional failure mode and effect analysis. Therefore, the proposed model effectively supports users to identify causes of failure modes regarding material properties for functional materials.

Applying an improved failure mode effect analysis method to evaluate the safety of a three‐in‐one machine tool

AbstractStraighteners are commonly used in the field of plate straightening. With the shortage of industrial land, an increasing number of straightener manufacturers integrate uncoilers, straighteners, and feeders, which represent a three‐in‐one machine tool. The tool's functions are complex; many factors affect its reliability and performance, including the problems of equipment itself and human errors. To improve the reliability of this machine, it is necessary to identify the main failure modes and causes. The risk assessment of using the conventional failure mode and effects analysis (FMEA) presents several issues. Thus, multiple methods have been proposed to improve the robustness and applicability of the FMEA. Herein, an improved FMEA, which combines fuzzy set and entropy evaluations is utilized to assess the three‐in‐one machine tool. In the method, the fuzzy set method is used to quantify the evaluation index. The information entropy and expert evaluation method are used to determine the weight between the indexes. From this study, human operation errors accounted for over 55% of the risks of machine malfunctions. By evaluating failure modes, a few countermeasures to reduce human operation errors can be proposed. By improving the human machine interface design and ergonomic job design and providing adequate training, human errors can be reduced and the reliability of three‐in‐one machine tools can be improved.

An EMI-Based Clustering for Structural Health Monitoring of NSM FRP Strengthening Systems.

The use of fiber-reinforced polymers (FRP) in civil construction applications with the near-surface mounted (NSM) method has gained considerable popularity worldwide and can produce confident strengthening and repairing systems for existing concrete structures. By using this technique, the FRP reinforcement is installed into slits cut into the concrete cover using cement mortar or epoxy as bonding materials, yielding an attractive method to strengthen concrete structures as an advantageous alternative to the external bonding of FRP sheets. However, in addition to the two conventional failure modes of concrete beams, sudden and brittle debonding failures are still likely to happen. Due to this, a damage identification technology able to identify anomalies at early stages is needed. In this work, some relevant cluster-based methods and their adaptation to electromechanical impedance (EMI)-based damage detection in NSM-FRP strengthened structures are developed and validated with experimental tests. The performance of the proposed clustering approaches and their evaluation in comparison with the experimental observations have shown a strong potential of these techniques as damage identification methodology in an especially complex problem such as NSM-FRP strengthened concrete structures.

An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures

Identification and prioritization of failure modes in a system and planning for corrective actions are among the most important components of risk management in any organization. Meanwhile, conventional Failure Mode and Effects Analysis (FMEA) is one of the most commonly used methods for prioritization of the failures. Despite the widespread applications of this method in various industries, FMEA is associated with some shortcomings that can lead to unrealistic results. In this study, a proposed approach is presented in three phases to cover some of the shortcomings of the FMEA technique. In the first phase, FMEA is used to identify the failure modes and assign values to the Risk Priority Number (RPN) determinant factors. In the second phase, the Fuzzy Best-Worst Method (FBWM) based on the experts’ opinions is used to measure the weights of these factors. In the third phase, the outputs of the previous phases are used as a basis to prioritize the failures using the proposed Multi-Objective Optimization by Ratio Analysis based on the Z-number theory (Z-MOORA). In addition to assigning different weights to the RPN determinant factors and considering uncertainties of them, the Z-number theory is used in this approach to cover reliability in different failure modes. The proposed approach was implemented in the automotive spare parts industry, and the results indicate a full prioritization of the failures in comparison with other conventional methods such as FMEA and fuzzy MOORA.

Dynamic prioritization of equipment and critical failure modes

PurposeThe purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW).Design/methodology/approachTo realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated.FindingsTo prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.Originality/valueIn this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu.

Multicriteria risk assessment framework for components' risk ranking: Case study of a complex oil and gas support structure

AbstractThis paper develops and applies a methodology for multicriteria risk assessment aiming to overcome the limitations of the conventional failure mode and effect analysis where risk evaluation is performed at the higher level consideration of occurrence, severity, and detection. Breaking down these higher level criteria into a set of parameters and variables makes it possible to analyse in greater detail the physical, environmental, and process conditions of the components in response to the activities of factors of biological, chemical, and mechanical stresses. By adopting a framework comprising multicriteria decision analysis, Delphi method, nominal group technique, and technique for order of preference by similarity to ideal solution, the fidelity, transparency, and repeatability of the assessment are ensured. The highlight of the paper is the demonstration of the capability of the model for time dependent assessment, which allows the comparison between different states of the asset's conditions through alteration in the risk profiles. The analysis conducted shows the efficient applicability of the method for the reference case study of an offshore oil and gas support structure, proving its relevance for systems of similar class.

A comprehensive reliability allocation method for series systems based on failure mode and effects analysis transformed functions

In order to address the reliability allocation problem of the series system, a comprehensive reliability allocation method based on a transformed function of the failure mode and effects analysis is introduced. First, considering multiple factors that affect the reliability allocation, an allocation matrix is established by employing significance factors. Subsequently, to overcome the limitations of the conventional failure mode and effects analysis–based allocation method, non-linear transform laws of failure severity and occurrence, known as transformed functions, are established. The reliability allocation results could be adjusted appropriately by choosing transform coefficients according to the desired allocation results of the system. Then, the transformed failure mode and effects analysis and the comprehensive allocation matrix are combined to give an allocation vector. Finally, a computerized numerical controlled lathe and a spindle system are used as examples. The allocation results of the transformed method, the conventional failure mode and effects analysis method and those in the correlated references are compared to emphasize the significance of the proposed allocation method in engineering practice.

An improved FMEA method based on the linguistic weighted geometric operator and fuzzy priority

ABSTRACTUsing the group linguistic information aggregation method, this research improved upon conventional failure mode and effect analysis (FMEA), which had the problems of the inevitable subjectivity of expert evaluations, and of the difficulty of determining the weights of experts' evaluations. First, this research treated the three risk factors of FMEA evaluation as linguistic variables and introduced a linguistic weighted geometric (LWG) operator to implement algebraic operations on the results of expert evaluations. This treatment overcame the disadvantage of fuzzy theory-based methods in which decision-making information could be lost due to the twice conversion process. Second, the weights of experts' evaluations were calculated based on the consistency of experts' ranking using a fuzzy priority method. This method placed a lower weight for the experts whose evaluation departed from group consensus, and therefore decreased the impact of the unfairness of experts on evaluation results. Finally, this article demonstrated the effectiveness and applicability of this method by an example of failure-mode analysis on the grinding wheel system of a numerical control machine.