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Field expertise in industry is often poorly recorded and unexploited. The purpose of this paper is to introduce a methodology and tool that incorporates a knowledge validation loop to leverage upon human-contributed field observations in industrial maintenance management. Starting from a failure mode, effects and criticality analysis (FMECA) model, it defines a collaborative process that links FMECA knowledge with field maintenance practice.

A metadata management system is designed to encourage staff involvement in enriching knowledge with field observations. The process supports easy feedback and collaborative annotation and is pilot tested via an industrial case study.

Streamlining FMECA validation is welcomed by maintenance staff, empowering them to exert more control over the management, usage and versioning of reference knowledge.

The methodology for metadata management in industrial maintenance enables staff participation in a collaborative knowledge enrichment process. Metadata management is a pre-cursor and therefore an important step to drive future analytics.

Industry personnel are more inclined to contribute to organisational knowledge if the process is based on reference knowledge and requires minimal interaction.

Facilitating individual contribution to collective knowledge strengthens the sense that each staff member can have organisational impact.

The paper introduces a methodology and tool to stimulate human-contributed knowledge in industrial maintenance, strengthening collaborative organisation knowledge flows.

The paper presents an efficient methodology that was developed for the reliability prediction and the failure mode effects and criticality analysis (FMECA) of electronic devices using fuzzy logic.

The reliability prediction is based on the general features and characteristics of the MIL‐HDBK‐217FN2 technical document and a derating plan for the system design is developed in order to maintain low components’ failure rates. These failure rates are used in the FMECA, which uses fuzzy sets to represent the respective parameters. A fuzzy failure mode risk index is introduced that gives priority to the criticality of the components for the system operation, while a knowledge base is developed to identify the rules governing the fuzzy inputs and output. The fuzzy inference module is Mamdani type and uses the min‐max implication‐aggregation.

A typical power electronic device such as a switched mode power supply was analyzed and the appropriate reliability indices were estimated using the stress factors of the derating plan. The fuzzy failure mode risk indices were calculated and compared with the respective indices calculated by the conventional FMECA.

Further research efforts are needed for the application of fuzzy modeling techniques in the area of reliability assessment of electronic devices. These research efforts can be concentrated in certain applications that have practical value.

Practical applications can use a fuzzy FMECA modeling instead of the classical FMECA one, in order to obtain a more accurate analysis.

Fuzzy modeling of FMECA is described which can calculate fuzzy failure mode risk indices.

Assessing the severity of failure modes of critical industrial machinery is often considered as an onerous task and sometimes misinterpreted by shop-floor engineer/maintenance personnel. The purpose of this paper is to develop an improved FMECA method for prioritizing the failure modes as per their risk levels and validating the same through a real case study of induction motors used in a process plant.

This paper presents a novel hybrid multi-criteria decision-making (MCDM) approach to prioritize different failure modes according to their risk levels by combining analytical hierarchy process (AHP) with a newly introduced MCDM approach, election based on relative value distance (ERVD). AHP is incorporated in the proposed approach to determine the criteria weights, evaluated in linguistic terms by industrial expert. Furthermore, ERVD, which is based on the concept of prospect theory of human cognitive process, is applied to rank the potential failure modes.

It is found that the proposed FMECA approach provides better results in accordance with the actual industrial scenario and helps in effectively prioritizing the failure modes. A comparison is also made to highlight the differences of results between the proposed approach with TOPSIS and conventional FMECA.

This research paper proposes an improved FMECA method and, thus, provides a deep insight to maintenance managers for effectively prioritizing the failure modes. The correct prioritization of failure modes will help in effective maintenance planning, thus reducing the downtime and improving profit to the organization.

A real case of process plant induction motor has been introduced in the research paper to show the applicability of this decision-making approach, and the approach is found to be suitable in correct prioritization of the failure modes.

Severity has been decoupled into various factors affecting it, to make it more relevant as per actual industrial scenario. Then, a novel modified FMECA has been developed using a hybrid MCDM approach (AHP and ERVD). This hybrid method, as well as its application in FMECA, has not been developed by any previous researcher. Moreover, the same has been thoroughly explained by considering a real case of process plant induction motors and validated with cross-functional experts.

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.

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.

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.

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.

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.

This study aims at introducing a method based on the failure mode, effects and criticality analysis (FMECA) to aid in selecting the most suitable formwork system with the minimum overall cost.

The research includes a review of the literature around formwork selection and analysis of data collected from the building construction industry to understand material failure modes. An FMECA-based model that estimates the total cost of a formwork system is developed by conducting a two-phased semi-structured interview and regression and statistical analyses. The model comprises material, manpower and failure mode costs. A case study of fifteen buildings is analysed using data collected from construction projects in the UAE to validate the model.

Results obtained indicate an average accuracy of 89% in predicting the total formwork cost using the proposed method. Moreover, results show that the costs incurred by failure modes account for 11% of the total cost on average.

The analysis is limited to direct costs and costs associated with risks; other costs and risk factors are excluded. The proposed framework serves as a guide to construction project managers to enhance decision-making by addressing the indirect cost of failure modes.

The research proposes a novel formwork system selection method that improves upon the subjective conventional selection process by incorporating the risks and uncertainties associated with the failure modes of formwork systems into the decision-making process.

The purpose of this paper is to develop a novel risk analysis method named fuzzy critical risk analysis (FCRA) for assessing the infrastructure risks from a risk-community network perspective. The basis of this new FCRA method is the integration of existing risk magnitude analysis with the novel risk impact propagation analysis performed in specific infrastructure systems to assess the criticality of risk within specific social-infrastructure interrelated network boundary.

The FCRA uses a number of scientific methods such as failure mode effect and criticality analysis (FMECA), social network analysis (SNA) and fuzzy-set theory to facilitate the building of risk evaluation associated with the infrastructure and the community. The proposed FCRA approach has been developed by integrating the fuzzy-based social network analysis (FSNA) method with conventional fuzzy FMECA method to analyse the most critical risk based on risk decision factors and risk impact propagation generated by various stakeholder perceptions.

The application of FSNA is considered to be highly relevant for investigating the risk impact propagation mechanism based on various stakeholder perceptions within the infrastructure risk interrelation and community networks. Although conventional FMECA methods have the potential for resulting in a reasonable risk ranking based on its magnitude value within the traditional risk assessment method, the lack of considering the domino effect of the infrastructure risk impact, the various degrees of community dependencies and the uncertainty of various stakeholder perceptions made such methods grossly ineffective in the decision-making of risk prevention (and mitigation) and resilience context.

The validation of the model is currently based on a hypothetical case which in the future should be applied empirically based on a real case study.

Effective functioning of the infrastructure systems for seamless operation of the society is highly crucial. Yet, extreme events resulted in failure scenarios often undermine the efficient operations and consequently affect the community at multiple levels. Current risk analysis methodologies lack to address issues related to diverse impacts on communities and propagation of risks impact within the infrastructure system based on multi-stakeholders’ perspectives. The FCRA developed in this research has been validated in a hypothetical case of infrastructure context. The proposed method will potentially assist the decision-making regarding risk governance, managing the vulnerability of the infrastructure and increasing both the infrastructure and community resilience.

The new approach developed in this research addresses several infrastructure risks assessment challenges by taking into consideration of not only the risk events associated with the infrastructure systems but also the dependencies of various type communities and cascading effect of risks within the specific risk-community networks. Such a risk-community network analysis provides a good basis for community-based risk management in the context of mitigation of disaster risks and building better community resilient.

The novelty of proposed FCRA method is realized due to its ability for improving the estimation accuracy and decision-making based on multi-stakeholder perceptions. The process of assessment of the most critical risks in the hypothetical case project demonstrated an eminent performance of FCRA method as compared to the results in conventional risk analysis method. This research contributes to the literature in several ways. First, based on a comprehensive literature review, this work established a benchmark for development of a new risk analysis method within the infrastructure and community networks. Second, this study validates the effectiveness of the model by integrating fuzzy-based FMECA with FSNA. The approach is considered useful from a methodological advancement when prioritizing similar or competing risk criticality values.

The aim of this paper is to develop a new tool for reliability and failure mode analysis by integrating the conventional aspects of the popular failure mode and criticality analysis (FMECA) procedure with economic considerations. Here FMECA is approached as a multi‐criteria decision making technique which integrates four different factors: chance of failure, chance of non‐detection, severity, and expected cost. To aid the analyst to formulate an efficient and effective priority ranking of the possible causes of failure, the analytic hierarchy process technique is adopted. With this technique, factors and alternative causes of failure are arranged in a hierarchic structure and evaluated only through the use of a series of pairwise judgements. With this new approach to failure investigation, the critical FMECA problem concerning the (direct) evaluation of failure factors is also by‐passed. The principles of the theory and an actual application in an Italian refrigerator manufacturing company are reported in the paper.

This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios.

To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method.

This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method.

This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

The paper aims to develop a new methodology for reliability modelling able to use the data collected in an FMECA analysis to simulate the reliability behaviour of a complex system and the effects of different maintenance policies.

A new methodology has been developed, that combines the FMECA analysis with the Petri nets, oriented graphs able to simulate the behaviour of complex systems with concurrent events. This approach was tested on a case study in API oil refinery in Falconara Marittima (AN, Italy).

By using data collected during an FMECA analysis as input for a Petri net, it is possible to obtain important reliability parameters that describe the behaviour of the system, such as MTTR, MTBF, availability of the plant/machine. It is possible to perform what‐if analysis observing how the reliability parameters change depending on changes in preventive maintenance policies.

In the case study proposed it was not necessary to simulate on condition maintenance. Even if the approach here described is able to do that, it would be interesting to evaluate the methodology presented also in other case studies. The approach described can be used as a starting point to develop techniques of optimization of preventive and on condition maintenance.

The application of the methodology of a case study demonstrated its practical effectiveness, obtaining data very close to experimental ones. This approach is able to provide useful data that help maintenance managers in scheduling maintenance activities and assessing their effect on the behaviour of the whole system.

The methodology presented shows a new solution for reliability modelling of complex industrial systems and represents the first combination of Petri nets with FMECA technique.

The objective of this paper is to suggest a methodological approach of eco‐conception by presenting the eco‐conception stakes of a firm, its organisation modes with regard to this new approach and how one could insert the environmental data in the classical conception process.

In this paper, an eco‐conception methodology is developed. It is about an approach integrating the concepts: quality, safety and environment (QSE). The taking into account simultaneously of these concepts, in the frame of our approach, allows us to conceive clean and durable products. The failure modes effects and criticality analysis (FMECA) was used in a case study to validate our approach.

This paper is a development of an approach with results obligation. Owing to our eco‐conception approach of products, the respect of environment is taken into consideration at the stage of product design. From regulation point of view, we put into reflection the approach with results obligation, i.e. approach by objectives of QSE.

A better definition of products implying functional specifications (products performance) strengthened by others of environmental type. As expected from this full definition of products, we cite the minimisation of products effects by unifying man at work (safety of person and goods), man as manager (quality, availability and reliability), as resident (safety in the vicinity of industrial sites) and as citizen (safeguarding environment).

Taking into account the triptych QSE at the product design stage. Our suggestion necessitates the implication of all the actors. Therefore, efforts must be concentrated on the dynamic and progressive integration of these actors. Our work is a source of information and knowledge. It is a source of information, as it allows to supply necessary data for better definition and conception of products. It is, in the same time, a source of knowledge in the sense where it presents specific methods (FMECA), that allow to put into existence the interest or rather the necessity of merger of the three concepts QSE.