Utility Priority Number Evaluation for FMEA

Traditionally, decisions on how to improve an operation are based on risk priority number (RPN) in the failure mode and effects analysis (FMEA). Many scholars questioned the RPN method and proposed some new methods to improve the decision process, but these methods are only measuring from the risks viewpoint while ignoring the importance of corrective actions. The corrective actions may be interdependent; hence, if the implementation of corrective actions is in proper order, selection may maximize the improvement effect, bring favorable results in the shortest times, and provide the lowest cost. This study aims to evaluate the structure of hierarchy and interdependence of corrective action by interpretive structural model (ISM), then to calculate the weight of a corrective action through the analytic network process (ANP), then to combine the utility of corrective actions and make a decision on improvement priority order of FMEA by utility priority number (UPN). Finally, it verifies the feasibility and effectiveness of this method by application to a case study. An erratum to this article can be found at     

医疗设备使用风险评估中的FMECA新方法

基于FMECA的风险分析方法可以帮助医疗机构更加有效地评估、控制医疗设备的使用风险。根据医疗设备的使用特点,利用模糊数学与灰色关联理论对方法进行改进,可更为客观地得出各风险模式的模糊评价结果和优先控制顺序。新方法以C臂机的风险分析为实例,说明其改进和应用过程。新方法扩展了FMECA的应用领域,为医疗设备的科学管理提供了依据。     

Fuzzy smart failure modes and effects analysis to improve safety performance of system: Case study of an aircraft landing system

Failure modes and effects analysis (FMEA) is a safety and reliability technique that is widely used to evaluate, design, and process a system against diverse possible ways through which the potential failure has a tendency to occur. In conventional FMEA, the risk evaluation is determined by risk priority number (RPN) obtained by multiplying of three risk factors—severity, occurrence, and detection. However, because of many shortages in conventional FMEA, the RPN scores have been widely criticized along issues bothering on ambiguity and vagueness, scoring, appraising, evaluating, and selecting corrective actions. In this paper, we propose a new integrated fuzzy smart FMEA framework where the combination of fuzzy set theory, analytical hierarchy process (AHP), and data envelopment analysis (DEA) is used, respectively, to handle uncertainty and to increase the reliability of the risk assessment. These are achieved by employing a heterogeneous group of experts and determining the efficiency of FMEA mode with adequate priority and corrective actions using RPN, time, and cost as indicators. A numerical example (aircraft landing system) is provided to exemplify the feasibility and effectiveness of the proposed model. The outputs of the proposed model compared with the conventional risk assessment technique results show its effectiveness, reliability, and propensity for real applications.     

An Extended FMECA Method and Its Fuzzy Assessment Model for Equipment Maintenance Management Optimization

Journal of Failure Analysis and Prevention - The failure mode, effect and criticality analysis (FMECA) is a famous bottom-up analytical method for quantifying and ranking critical failures of a...     

Risk Failure Deployment: A novel integrated tool to prioritize corrective actions in failure mode and effects analysis

In this paper, a novel integrated tool for failure mode and effects analysis (FMEA), opportunely named Risk Failure Deployment (RFD), which is able to evaluate the most critical failure modes and provide analyst with a practical and step-by-step guidance by selecting the most effective corrective actions for removal/mitigation process of root causes, is presented. Thanks to the modification of the framework of the Manufacturing cost deployment (MCD) and to its well-structured use of matrices, the novel RFD is able both to handle the dependencies and interactions between different and numerous failures and to evaluate the most critical ones on the basis of the risk priority number (RPN). Thereafter, the logical relationship between root causes and failure modes is assessed. Successively, the prioritization of corrective actions that are the most suitable for root causes is executed using not only the RPN but also other criteria, such as the economic aspect and the ease of implementation, that are unavoidable to execute a rational and effective selection of improvement activities. The effectiveness and usefulness in practice of the original tool for the prioritization of corrective actions to mitigate the risks due to failure modes collected during FMEA are presented in a case study.     

An interval probability-based FMEA model for risk assessment: A real-world case

Failure mode and effect analysis (FMEA) is an effective quality tool to eliminate the risks and enhance the stability and safety in the fields of manufacturing and service industry. Nevertheless, the conventional FMEA has been criticized for its drawbacks in the evaluation process of risk factors or the determination of risk priority number (RPN), which may lead to inaccurate evaluation results. Therefore, in this paper, we develop a novel FMEA method based on rough set and interval probability theories. The rough set theory is adopted to manipulate the subjectivity and uncertainty of experts' assessment and convert the evaluation values of risk factors into interval numbers. Meanwhile, the interval exponential RPN (ERPN) is used to replace the traditional RPN due to its superior properties, eg, solving the problems of duplicate numbers and discontinuity of RPN values. Furthermore, an interval probability comparison method is proposed to rank the risk priority of each failure mode for avoiding the information loss in the calculation process of RPN. Finally, a real case study is presented, and the comparison analysis among different FMEA methods is conducted to demonstrate the reliability and effectiveness of the proposed FMEA method.     

Applying UGF Concept to Enhance the Assessment Capability of FMEA

The purpose of this paper is to propose a modified version of Failure Mode and Effects Analysis (FMEA) to alleviate its drawbacks. FMEA is an important tool in risk evaluation and finding the priority of potential failure modes for corrective actions. In the proposed method, the Universal Generating Function (UGF) approach has been used to improve the assessment capability of the conventional Risk Priority Number (RPN) in ranking. The new method is named as URPN. It generates the most number of unique values in comparison with the previous methods and considers relative importance for the parameters while it is easy to compute. More unique numbers help to avoid from having the same priority level for different failure modes which represent various risk levels. A case study has been employed to demonstrate that the URPN not only can improve the shortcomings but also is able to provide accurate values for risk assessment. Copyright © 2015 John Wiley & Sons, Ltd.     

The Demon–Angel method in systematic safety assessment

Since ‘design for safety' of large engineering systems with a high level of innovation requires an exhaustive safety analysis and since a subsequent corrective action may become a very large bottleneck in improving such a system, fundamental knowledge in designing safe systems is essential. The lack of any ‘rule of thumb' makes such knowledge a matter of personal experience rather than the subject of an academic course. This paper proposes a new method for the theoretical safety study of different system configurations independently of any particular application. This method aims to help the construction of a ‘rule of thumb' for what is a safe system and what is not. The Demon and Angel ideas are explained and the schematic presentation of these elements is introduced. Four representative case studies demonstrate the use of this method.     

Reliability analysis techniques for mechanical systems

This paper discusses the application of known system reliability analysis techniques and identifies problems encountered in the practical implementation of these methods, revealing that no single technique is sufficient or even feasible in the case of complex mechanical systems. A new functional analysis method as well as a (new) criticality quantitative approach and failure mechanism analysis are presented and used to analyse an aircraft fuel system. A rigorous and detailed FMECA is still required. Besides its main function it will supply much of the valuable information for many other techniques.     

Design of a hinge kit system in a Kimchi refrigerator receiving repetitive stresses

Based on field data and a tailored set of accelerated life tests, the hinge kit system of a closing door in a Kimchi refrigerator was redesigned. Using a force and moment balance analysis, the simple mechanical loads from the closing of the door were evaluated. The failure modes and mechanisms found experimentally were similar to those of the failed sample in the field. Failure analysis, accelerated life tests and corrective action plans were used to identify the key control parameters and level for the mechanical hinge kit system. The missing controllable design parameters of the hinge kit system in the design phase included the corner rounding and rib of the housing hinge kit, the oil sealing method of the oil damper, and the material of the cover housing. After a tailored series of accelerated life tests with corrective action plans, the B₁ life of the new hinge kit design is now guaranteed to be over 10 years with a yearly failure rate of 0.1%.