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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.

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.

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.

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.

The purpose of this paper is to provide a structured methodology for performing build‐in reliability (BIR) investigation during a new product development cycle.

The methodology in this paper represents an extension of the Quality Functional Deployment/House of Quality (QFD/HoQ) concepts to reliability studies. It is able to translate the reliability requisites of customers into functional requirements for the product in a structured manner based on a Failure Mode And Effect Analysis (FMEA). Besides, it then allows it to build a completely new operative tool, named House of Reliability (HoR), that enhances standard analyses, introducing the most significant correlations among failure modes. Using the results from HoR, a cost‐worth analysis can be easily performed, making it possible to analyse and to evaluate the economical consequences of a failure.

The paper finds that the application of the proposed approach allows users to identify and control the design requisites affecting reliability. The methodology enhances the reliability analysis introducing and managing the correlations among failure modes, splitting the severity into a detailed series of basic severity aspects, performing also cost/worth assessments.

It is shown that the methodology enables users to finely analyse failure modes by splitting severity according to the product typology and the importance of each Severity criterion according to laws or international standards. Moreover the methodology is able to consider the “domino effects” and so to estimate the impact of the correlation between the causes of failure. Finally a cost/worth analysis evaluates the economical consequences of a failure with respect to the incurred costs to improve the final reliability level of the product.

The paper proposes a completely new approach, robust, structured and useful in practice, for reliability analysis. The methodology, within an integrated approach, overcomes some of the largely known limits of standard FMECA: it takes into account multiple criteria, differently weighted, it analyses the product considering not only the direct consequence of a failure, but also the reaction chain originated by a starting failure.

Discusses the implementation of failure mode and effects analysis (FMEA) for both product design and process control. FMEA is implemented in two ways to ensure that the reliability requirements are met for the production of an airbag inflator. Design FMEA is performed to generate a process control plan, visual aids, and a process verification list. Design FMEA and process FMEA are integrated through reliability prediction and supplier PPM reports. The supplier PPM reports contain the information that can be employed to update the probabilities used in design FMEA. The results of reliability predictions are fed back to eliminate the design weakness. Demonstrates the integrated procedure of the FMEA approach and discusses the relationships among useful tools.

The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited.

Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations.

It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system.

This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

This paper presents a tool for reliability and failure mode analysis based on an advanced version of the popular failure mode, effects and criticality analysis (FMECA) procedure. To help the analyst formulating efficiently effective criticality assessments of the possible causes of failure, the fuzzy logic technique is adopted. Particular attention has been devoted to support the maintenance staff with a fuzzy criticality assessment model easy to implement and design. To test the proposed methodology, an actual application concerning a process plant in milling field for human consumption flour is showed in the paper.

The purpose of this paper is to facilitate green supply chain (GSC) managers and planners to model and access GSC risks and probable failures. This paper proposes to use the fuzzy failure mode and effects analysis (FMEA) approach for assessing the risks associated with GSC for benchmarking the performance in terms of effective GSC management adoption and sustainable production.

Initially, different failure modes are defined using FMEA analysis, and in order to decide the risk priority, the risk priority number (RPN) is determined. Such priority numbers are typically acquired from the judgment decisions of experts that could contain the element of vagueness and imperfection due to human biases, and it may lead to inaccuracy in the process of risk assessment in GSC. In this study, fuzzy logic is applied to conventional FMEA to overcome the issues in assigning RPNs. A plastic manufacturer GSC case exemplar of the proposed model is illustrated to present the authenticity of this method of risk assessment.

Results indicate that the failure modes, given as improper green operating procedure, i.e. process, operations, etc. (R6), and green issues while closing the loop of GSC (R14) hold the highest RPN and FRPN scores in classical as well as fuzzy FMEA analysis.

The present research work attempts to propose an evaluation framework for risk assessment in GSC. This paper explores both sustainable developments and risks related to efficient management of GSC initiatives in a plastic industry supply chain context. From a managerial perspective, suggestions are also provided with respect to each failure mode.

Through this analysis an attempt has been made to improve the reliability of an ESDS used in the cockpit.

The process used for carrying out FMEA is specified by MIL‐STD‐1629A procedure for carrying out failure mode, effects and criticality analysis.

In an increasing demand in avionics sector, particularly in modern defence and civil aircraft, safety and reliability are the prime concern to complete the mission successfully. This made technocrats to rethink over the safety of complete system by adding redundancy to the critical activities or what else not? The electronic stand by display system (ESDS), being an avionics unit and fitted in the cockpit for displaying very important navigation and engine parameters to pilot whenever main display unit fail to perform it primary functions. So even standby system need to have high reliability to serve the purpose by providing important flight parameters for the safe landing of pilot and crew. Failure modes and effect analysis (FMEA) is one of the effective reliability assessment tool, which evaluate systematically and document the potential failure modes of a system or equipment and their causes. It helps in grading the severity of all potential failure modes and useful in carrying out the changes in early phase of design. The analysis starts with the potential failure of a smallest component at the final indenture and goes up to the initial indenture level.

The paper adds insight into the reliability improvement of electronics standby display systems of modern aircraft.

Research carried out to develop and advance the application of design and process failure mode and effects analysis (FMEA) at Garrett Automotive Ltd, Skelmersdale, is described. The work has been undertaken under the umbrella of the UMIST Total Quality Management Multi‐company Teaching Programme. From an analysis of the present methods of preparing and using FMEAs, procedural changes have been made which have resulted in more effective use of the technique. The findings include the reluctance of product engineering and manufacturing engineering personnel to take a leading role in the preparation of design and process FMEAs, respectively. The main reasons for this relate to a perceived lack of time or lack of understanding of the technique′s potential. It is also pointed out that, in the past, FMEAs have mainly been used to satisfy the demands of major customers and it takes some considerable effort to ensure that FMEAs are prepared and used in the correct manner.

This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.

The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR.

The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty.

Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.

The purpose of this paper is to propose a practical method of performing maintenance in the offshore industry where engineers have to manage problems such as the high cost of operations, assuring an high availability of the plant, safety on board and environmental protection. Indeed an efficient maintenance method it is necessary in order to offer methods and criteria to select the rights maintenance strategies keeping in to account the environmental, safety and production constrains.

The paper provides an overview of reliability centered maintenance (RCM) and reliability, availability, maintainability methodologies and an integration of the two methodologies in a particular case study in the oil and gas sector.

This paper suggests an improvement of the well-established RCM methodology applicable to industries with high priority level. It is proposed an integration between a reliability analysis and an availability analysis and an application on the offshore oil and gas industry.

The methodology provides an excellent tool that can be utilized in industries, where safety, regulations and the availability of the plant play a fundamental role.

The proposed methodology provides a practical method for selecting the best maintenance strategy considering the equipment redundancy and sparing, the asset’s performance over long time scales, and the system uptime, downtime and slowdowns.