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1 – 10 of over 1000Ammar Chakhrit, Mohammed Bougofa, Islam Hadj Mohamed Guetarni, Abderraouf Bouafia, Rabeh Kharzi, Naima Nehal and Mohammed Chennoufi
This 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…
Abstract
Purpose
This 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/approach
To 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.
Findings
This 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/value
This 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.
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Patient safety is a top priority globally. A robust healthcare system requires strategic collaboration between research and development. The author analysed over 300 cases from…
Abstract
Purpose
Patient safety is a top priority globally. A robust healthcare system requires strategic collaboration between research and development. The author analysed over 300 cases from seven hospitals using the failure modes, effects, and criticality analysis (FMECA) tool to understand the underlying causes of medical errors.
Design/methodology/approach
The author studied seven hospitals and 300 cases using FMECA to prioritise activities. The findings showed that high-priority events occurred less frequently but had the potential to cause the most harm. Team members evaluated independently to ensure unbiased evaluations. This approach is useful for setting priorities or assessing difficulties.
Findings
Poor communication and lack of coordination among staff in a healthcare organisation caused misunderstandings, ineffective decision-making, delays in patient care, and medical errors. Implementation of effective communication and coordination protocols can help avoid these problems.
Practical implications
The study recommends using FMECA to identify and prioritise failures and conducting in-depth analyses to understand their root causes. It also highlights the importance of interdisciplinary knowledge and soft skills for healthcare staff.
Originality/value
This study reveals the significance of FMECA in healthcare risk management and benchmarking. FMECA helps identify system failures, develop prevention strategies, and evaluate effectiveness against industry benchmarks. It offers healthcare professionals a valuable tool to enhance patient safety and improve healthcare quality.
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Fatemeh Shaker, Arash Shahin and Saeed Jahanyan
This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal…
Abstract
Purpose
This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal relationships among failure modes and effects analysis elements.
Design/methodology/approach
A stock and flow diagram has been developed to simulate system behaviors during a timeframe. Some improvement scenarios regarding the most necessary CAs according to their strategic priority and the possibility of eliminating root causes of critical failure modes in a roller-transmission system have been simulated and analyzed to choose the most effective one(s) for the system availability. The proposed approach has been examined in a steel-manufacturing company.
Findings
Results indicated the most effective CAs to remove or diminish critical failure causes that led to the less reliability of the system. It illustrated the impacts of the selected CAs on eliminating or decreasing root causes of the critical failure modes, lessening the system’s failure rate and increasing the system availability more effectively.
Research limitations/implications
Results allow managers and decision-makers to consider different maintenance scenarios without wasting time and more cost, choosing the most appropriate option according to system conditions.
Originality/value
This study innovation would be the dynamic analysis of interactions among failure modes, effects and causes over time to predict the system behavior and improve availability by choosing the most effective CAs through improvement scenario simulation via VENSIM software.
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Bianca Arcifa de Resende, Franco Giuseppe Dedini, Jony Javorsky Eckert, Tiago F.A.C. Sigahi, Jefferson de Souza Pinto and Rosley Anholon
This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy…
Abstract
Purpose
This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.
Design/methodology/approach
Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.
Findings
The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.
Practical implications
This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.
Originality/value
This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.
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Xiao Yang and Xinbo Qian
Hydraulic slide valve failure often results from competing failure modes, termed competitive failure. To enhance prediction accuracy for hydraulic slide valve remaining useful…
Abstract
Purpose
Hydraulic slide valve failure often results from competing failure modes, termed competitive failure. To enhance prediction accuracy for hydraulic slide valve remaining useful life, the authors propose a method incorporating competitive failure and Monte Carlo simulation. This method allows for more accurate prediction of hydraulic slide valve remaining useful life.
Design/methodology/approach
In this paper, the competitive failure mode of the hydraulic slide valve is analyzed by studying the two failure modes of the hydraulic slide valve, and the prediction of the remaining useful life of the hydraulic slide valve is studied by using the sample set generated by Monte Carlo simulation and the competitive failure joint model.
Findings
The results show that the proposed prediction method based on competitive failure and Monte Carlo simulation is more accurate than the traditional Bayesian joint model prediction method when dealing with the failure mode competition phenomenon of hydraulic slide valve.
Originality/value
In this paper, the remaining useful life prediction of hydraulic slide valve with competitive failure characteristics is studied, which provides a new idea for the remaining useful life prediction method.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0361/
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Anwesa Kar and Rajiv Nandan Rai
The purpose of the study is to examine how risk factors contribute to the occurrence of defects in a process. By analyzing these risk factors in relation to process quality, the…
Abstract
Purpose
The purpose of the study is to examine how risk factors contribute to the occurrence of defects in a process. By analyzing these risk factors in relation to process quality, the study aims to help organizations prioritize their resources and efforts toward addressing the most significant risks. These challenges, integrated with the emerging concept of Quality 4.0, necessitate a comprehensive risk assessment technique.
Design/methodology/approach
Fuzzy logic integrated with an analytic network process is used in the process failure mode and effects analysis for conducting risk identification and assessment under uncertainty. Through a mathematical model, the linkage of risk with Six Sigma is established and, finally, a value–risk matrix is developed for illustrating and analysing risk impact on process quality.
Findings
A case study on fused filament fabrication demonstrates the proposed methodology’s applicability. The results show its effectiveness in assessing risk factors’ impact on Six Sigma metrics: defects per million opportunities/sigma level.
Practical implications
By integrating qualitative assessments and leveraging available data, this approach enables a more comprehensive understanding of risks and their utilization for an organization’s quality improvement initiatives.
Originality/value
This approach establishes a risk-centric Six Sigma assessment method in accordance with the requirement of ISO 9001:2015 and in the context of Quality 4.0.
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Temesgen Agazhie and Shalemu Sharew Hailemariam
This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.
Abstract
Purpose
This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.
Design/methodology/approach
We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.
Findings
These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.
Research limitations/implications
The research focuses on a case company and the result could not be generalized for the whole industry.
Practical implications
The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.
Originality/value
The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.
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Adel Ali Ahmed Qaid, Rosmaini Ahmad, Shaliza Azreen Mustafa and Badiea Abdullah Mohammed
This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred…
Abstract
Purpose
This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred maintenance (RCM) approach to minimise the high downtime of a production line, thus increasing its reliability and availability. A case study of a production line from the ghee and soap manufacturing industry in Taiz, Yemen, is presented for framework validation purposes. The framework provides a systematic process to identify the critical system(s) and guide further investigation for functional significant items (FSIs) based on quantitative and qualitative analyses before recommending appropriate maintenance strategies and specific tasks.
Design/methodology/approach
The proposed framework integrates conventional RCM procedure with the fuzzy computational process to improve FSIs criticality estimation, which is the main part of failure mode effect criticality analysis (FMECA) applications. The framework consists of four main implementation stages: identification of the critical system(s), technical analysis, Fuzzy-FMECA application for FSIs criticality estimation and maintenance strategy selection. Each stage has its objective(s) and related scientific techniques that are applied to systematically guide the framework implementation.
Findings
The proposed framework validation is summarised as follows. The first stage results demonstrate that the seaming system (top and bottom systems) caused 50% of the total production line downtime, indicating it is a critical system that requires further analysis. The outcomes of the second stage provide significant technical information on the subject (seaming system), helping team members to identify and understand the structure and functional complexities of the seaming system. This stage also provides a better understanding of how the seaming system functions and how it can fail. In stage 3, the application of FMECA with the fuzzy computation integration process presents a systematic way to analyse the failure mode, effect and cause of items (components of the seaming system). This stage also includes items’ criticality estimation and ranking assessment. Finally, stage four guides team members in recommending the appropriate countermeasures (maintenance strategies and task selection) based on their priority level.
Originality/value
This paper proposes an original maintenance strategies development framework based on the RCM approach for production system equipment. Specifically, it considers a fuzzy computational process based on the Gaussian function in the third stage of the proposed framework. Adopting the fuzzy computational process improves the risk priority number (RPN) estimation, resulting in better criticality ranking determination. Another significant contribution is introducing an extended item criticality ranking assessment process to provide maximum levels of criticality item ranking. Finally, the proposed RCM framework also provides detailed guidance on maintenance strategy selection based on criticality levels, unique functionality and failure characteristics of each FSI.
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Penghai Deng, Quansheng Liu and Haifeng Lu
The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil…
Abstract
Purpose
The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness.
Design/methodology/approach
Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes.
Findings
Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80°, respectively.
Originality/value
This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.
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Mohammad Hossein Hamzezadeh Nakhjavani, Faradjollah Askari and Orang Farzaneh
One of the primary challenges associated with excavation near buildings is the significant decrease in the bearing capacity of nearby foundations during the initial stages before…
Abstract
Purpose
One of the primary challenges associated with excavation near buildings is the significant decrease in the bearing capacity of nearby foundations during the initial stages before the stabilization of the excavation wall. This study aims to investigate the correlation between excavation height and foundation-bearing capacity under actual field conditions.
Design/methodology/approach
This paper uses a three-dimensional rotational failure mechanism to propose a novel method for estimating foundation-bearing capacity using the upper bound limit analysis approach.
Findings
The study delineates two distinct zones in the excavation height versus bearing capacity diagram. Initially, there is a significant reduction in foundation-bearing capacity at the onset of excavation, with decreases of up to 80% compared to its undisturbed state. Within a specific range of excavation heights, the bearing capacity remains relatively constant until reaching a critical height. Beyond this threshold, the entire soil mass behind the excavation wall becomes unstable. The critical excavation height is notably influenced by the soil's internal friction angle, excavation slope angle and soil cohesion parameter. Notably, when the ratio of excavation height to foundation width is less than 0.4, changes in slope angle have no significant impact on bearing capacity.
Originality/value
The bearing capacity estimates derived from the method proposed in this paper are deemed to reflect real-world scenarios closely compared to existing methodologies.
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