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Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the probability of system failure and achieve good product quality. The FMEA technique had applied in vest scopes which include aerospace, automatic, electronic, mechanic and service industry. The marking process is one of the back ends testing process that is the final process in semiconductor process. The marking process failure can cause bad final product quality and return although is not a primary process. So, how to improve the quality of marking process is one of important production job for semiconductor testing factory. This research firstly implements FMEA technique in laser marking process improvement on semiconductor testing factory and finds out which subsystem has priority failure risk. Secondly, a CCD position solution for priority failure risk subsystem is provided and evaluated. According analysis result, FMEA and CCD position implementation solution for laser marking process improvement can increase yield rate and reduce production cost. Implementation method of this research can provide semiconductor testing factory for reference in laser marking process improvement.

The purpose of this paper is to propose an integrative approach for improving failure modes and effects analysis (FMEA).

An extensive literature review on FMEA has been performed. Then, an integrative approach has been proposed based on literature review. The proposed approach is an integration of FMEA and quality function deployment (QFD). The proposed approach includes a two-phase QFD. In the first phase, failure modes are prioritized based on failure effects and in the second phase, failure causes are prioritized based on failure modes. The proposed approach has been examined in a case example at the blast furnace operation of a steel-manufacturing company.

Results of the case example indicated that stove shell crack in hot blast blower, pump failure in cooling water supply pump and bleeder valves failed to operate are the first three important failure modes. In addition, fire and explosion are the most important failure effects. Also, improper maintenance, over pressure and excess temperature are the most important failure causes. Findings also indicated that the proposed approach with the consideration of interrelationships among failure effects, failure mode and failure causes can influence and adjust risk priority number (RPN) in FMEA.

As manufacturing departments are mostly dealing with failure effects and modes of machinery and maintenance departments are mostly dealing with causes of failures, the proposed model can support better coordination and integration between the two departments. Such support seems to be more important in firms with continuous production lines wherein line interruption influences response to customers more seriously. A wide range of future study opportunities indicates the attractiveness and contribution of the subject to the knowledge of FMEA.

Although the literature indicates that in most of studies the outcomes of QFD were entered into FMEA and in some studies the RPN of FMEA was entered into QFD as importance rating, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.

This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes.

A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system.

Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes.

The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability.

The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently.

To ensure the service quality, it is very important and necessary for a company to systematically identify and prioritize the critical failure modes that result in disservice of quality, and take the required remedial actions before the service is delivered to customers. The purpose of this paper is to propose an approach to enhance perceived service quality by incorporating disservice analysis with failure modes and effects analysis (FMEA).

The approach, first, identifies the potential failure modes that might have explicit effects on the service quality. Subsequently, the risk priority number (RPN) is computed to identify the risk priority for each potential failure mode. Furthermore, a disservice index that represents the extent of composite adverse effect of service failures on quality perceptions is computed to recognize the disservice priority for each quality dimension. Based on which, vital quality dimensions are determined as those quality dimensions that have higher disservice indices. The critical failure modes are, then, confirmed as those failure modes that have higher RPNs in the vital quality dimensions. Finally, the effects and root‐causes of the critical failure modes are determined by thoroughly exploiting the service infrastructure, service design, and service encounter for the company to take effective remedial actions to enhance perceived service quality. A practical case regarding a hypermarket service was used to demonstrate the proposed approach. Managerial implications and suggestions are provided to the case company, the hypermarket industry, and other service industries. Possibilities for future research are also addressed.

The vital quality dimensions are determined as responsiveness and reliability for the hypermarket case. Six critical failure modes are confirmed, by the order of criticality, as “unstable supply of goods/merchandise,” “no goods/merchandise on designated shelf of the sales floor,” “slowness of cashier speed,” “tardiness of warranty/repair goods/merchandise,” “nonconforming quality of goods/merchandise,” and “unable to find first‐line server in the sales floor.” These critical failure modes should be eliminated or reduced in top priority to enhance perceived service quality. Note that the determination of vital quality dimensions and the confirmation of critical failure modes depend on the applicable company resources.

The proposed approach improves both the academic and the practical developments of service quality in five aspects: explicitly identifying potential mistakes or failures of the service system that might result in disservice of quality. Arousing notices and focuses on those failure modes that have higher risk priorities by performing FMEA. Identifying how seriously the service failures adversely affect each of the quality dimensions and determining what the vital quality dimensions are by carrying out disservice analysis. Confirming the critical failure modes as those failure modes that have higher risk priorities in the vital quality dimensions with higher disservice indices. Knowing what actions need to be taken in advance to enhance perceived service quality by identifying the root‐causes that result in those critical failure modes.

The purpose of this analysis was to attempt to improve the reliability of a rotor support system of a modern aircraft engine.

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

In increasing demand in the avionics sector, particularly in modern defence and civil aircraft, safety and reliability are the prime concerns to complete the mission successfully. Technocrats are made to rethink the safety of complete systems by adding redundancy to the critical activities. A rotor support system (RSS) is an integral part of a gas turbine engine used in any aircraft. As its name implies, the rotor support system shares the load of the rotating component of an engine, hence the rotor support system plays a vital role in any aircraft engine. It shares the load of compressor rotor and stator, turbine rotor and stator, inter‐casing, and exhaust system of a gas turbine engine. Any failure in such a system may make the entire aircraft fail. Therefore it is worth carrying out Failure Modes and Effects Analysis (FMEA) on such a critical system. FMEA is one of the effective reliability assessment tools, 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 is useful in carrying out the changes in the early phase of design. The analysis starts with the potential failure of the smallest component at the final indenture and goes up to the initial indenture level.

The paper adds insight into the reliability improvement of the rotor support system of modern aircraft.

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.

This paper aims to provide a cost effective failure mode and effects analysis tool to overcome the disadvantages of the traditional FMEA that the cost due to failure is not defined.

The method presented in this paper is based on the fuzzy utility theory. It uses utility theory and fuzzy membership functions for the assessment of severity, occurrence, and detection. The utility theory accounts for the nonlinear relationship between the cost due to failure and the ordinal ranking. The application of fuzzy membership functions better represents the team opinions. The Risk Priority Index (RPI) is developed for the prioritization of failure modes.

The advantages of the FUT‐based FMEA are demonstrated through cases studies. It shows that it can take the cost due to failure into account when prioritizing failure modes.

The FUT‐based FMEA presented in this paper provides a convenient cost‐effective tool for failure analysis. It improves the performance FMEA in the risk and failure analysis for product design and manufacturing/assembly process.

The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes.

A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes.

A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies.

The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method.

This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

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.

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.