• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.751-758
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• 2021

Munitions must be analyzed to identify any risks for quality assurance in development and mass production. Risk identification for parts, compositions, and systems is carried out through failure mode effects analysis (FMEA) as one of the most reliable methods. FMEA is a design tool for the failure mode of risk identification and relies on the RPN (risk priority number). FMEA has disadvantages because its severity, occurrence, and detectability are rated at the same level. Fuzzy FMEA applies fuzzy logic to compensate for the shortcomings of FMEA. The fuzzy logic of Fuzzy FMEA is to express uncertainties about the phenomenon and provides quantitative values. In this paper, Fuzzy FMEA is applied to the failure mode of a rotorcraft landing system. The Fuzzy rule and membership functions were conducted in the Fuzzy model to study the RPN in the failure mode of a landing system. This method was selected to demonstrate crisp values of severity, occurrence, and detectability. In addition, the RPN was obtained. The results of Fuzzy FMEA for the landing system were analyzed for the RPN and ranking by fuzzy logic. Finally, Fuzzy FMEA confirmed that it could use the data in quality assurance activities for rotorcraft.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.162-167
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• 2008

FMEA (failure mode and effect analysis)is a widely used technique to assess or to improve reliability of product not only at early stage of design and development, but at the process and service phase during the product life cycle. In designing a service system, this study proposes a fuzzy service FMEA with the service blueprints as a tool which describes customer actions, onstage contact employees actions, backstage contact employees actions, support processes, and physical evidences, in order to analyse and inform service delivery system design. We fuzzified only two risk factors, occurrence and severity, to more effectively assess the potential failure modes in service. Proposed fuzzy risk grades are applied to Gaussian membership function, defuzzified into Fuzzy Inference System, and eventually identified the ranks on the potential fail points.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.9-17
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• 2023

In this study, we aimed to identify the important hazard factors and determine their criticality in causing serious accidents in vehicle-mounted mobile elevated work platforms (MEWPs). Fuzzy failure modes and effects analysis (FMEA)was performed using accident data and a survey of experts. To determine the hazard factors, the accident data for the last 10 years were used and a questionnaire survey was designed. The questionnaire survey was sent to four experts in the field of occupational safety to determine the severity, occurrence, and detectability of serious accidents in MEWPs. Furthermore, objective RPN scores and risk priority were obtained using fuzzy FMEA. Finally, the criticality of hazard factors in descending order was found to be overloading, non-installation or defective installation of outriggers, breakage due to wire rope aging, and illegal remodeling of vehicle structures. The results were verified by comparing the occurrence data of serious disasters.

• Transactions of the Korean hydrogen and new energy society
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• v.29 no.4
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• pp.307-316
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• 2018

In this study, the failure mode and effect analysis (FMEA) of hydrogen production process by using the Thermococcus onnurineus NA1 was conducted and advanced methodology to compensate the weakness of previous FMEA methodology was applied. To bring out more quantitative and precise FMEA result for bio-hydrogen production process, fuzzy logic and potential loss cost estimated from ASPEN Capital Cost Estimator (ACCE) was introduced. Consequently, risk for releasing the flammable gases via internal leakage of steam tube which to control the operating temperature of main reactor was caution status in FMEA result without applying the fuzzification and ACCE. Moreover, probability of the steam tube plugging caused by solid property like medium was still caution status. As to apply the fuzzy logic and potential loss cost estimated from ACCE, a couple of caution status was unexpectedly upgraded to high dangerous status since the potential loss cost of steam tube for main reactor and decrease in product gases are higher than expected.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.174-179
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• 2015

Failure Mode and Effects Analysis (FMEA) has been used by Dynamic Positioning (DP) system for risk and reliability analysis. However, there are limitations associated with its implementation in offshore project. 1) since the failure data measured from the SCADA system is missing or unreliable, assessments of Severity, Occurrence, Detection are based on expert's knowledge; 2) it is not easy for experts to precisely evaluate the three risk factors. The risk factors are often expressed in a linguistic way. 3) the relative importance among three risk factors are rarely even considered. To solve these problems and improve the effectiveness of the traditional FMEA, we suggest a Fuzzy-FMEA method for risk and failure mode analysis in Dynamic Positioning System of offshore. The information gathered from DP FMEA report and DP FMEA Proving Trials is expressed using fuzzy linguistic terms. The proposed method is applied to an offshore Dynamic Positioning system, and the results are compared with traditional FMEA.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.177-186
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• 2014

Failure mode and effect analysis (FMEA) is a systematic approach for identifying potential failures before they occur, with the intent to minimize the risk associated with them. It has been widely used in the various manufacturing industries as a solution to reliability problems. As the importance of the service sector is increasing, however, it has been recently extended to some applications in services. Despite these attempts, FMEA cannot be directly applied to the reliability problems in a service industry. Due to the heterogeneity and customer participation in service process, we cannot perfectly prevent service failures. For this reason, we suggest a new risk priority number with three input parameters that consist of severity, probability of occurrence, and recoverability. In this paper, we propose an approach for assessing service risk and service reliability using the service-oriented risk priority number (S-RPN). An example regarding a hypermarket service process is used to demonstrate the proposed approach.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.3
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• pp.133-141
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• 2012

Service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs and survive in today's competitive market environment. The value of services depends mainly on service reliability that is identified by satisfaction derived from the relationship between customer and service provider. In this paper, we extend concepts from the failure modes and effects analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using fuzzy failure mode effects analysis (FMEA) and grey theory. We define the failure mode of service as interaction ways that can be failed in a service delivery process. The fuzzy set theory is used to characterize service reliability based on linguistic terms during FMEA. Grey theory is employed to determine the degree of relation and ranking among risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1529-1532
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• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.