scholarly journals Risk Assessment of Express Delivery Service Failures in China: An Improved Failure Mode and Effects Analysis Approach

2021 ◽  
Vol 16 (6) ◽  
pp. 2490-2514
Author(s):  
Hongmei Shan ◽  
Qiaoqiao Tong ◽  
Jing Shi ◽  
Qian Zhang
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Failure Modes ◽  
Service Failure ◽  
Cloud Model ◽  
Topsis Method ◽  
Delivery Service ◽  
Service Failures ◽  
Uncertainty Environment ◽  
Express Delivery

With the rapid growth of express delivery industry, service failure has become an increasingly pressing issue. However, there is a lack of research on express service failure risk assessment within the Failure Mode and Effects Analysis (FMEA) framework. To address the research gap, we propose an improved FMEA approach based on integrating the uncertainty reasoning cloud model and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The cloud model describing randomness and fuzziness in uncertainty environment is adopted to achieve the transformation between the qualitative semantic evaluation of occurrence (O), severity (S), and detection (D) risk factors of FMEA and the quantitative instantiation and set up the comprehensive cloud of risk assessment matrix for express delivery service failure (EDSF). The TOPSIS method calculates and ranks the relative closeness coefficients of EDSF mode. Finally, the rationality and applicability of the proposed method are demonstrated by an empirical study for the express delivery service in China. It is found that among 18 express delivery service failure modes, six service failure modes with high risk are mainly located in the processing and delivery stages, while six service failures with the relatively low risk are involved in the picking-up and transportation stages. This study provides insight on how to explore the risk evaluation of express delivery service failure, and it helps express delivery firms to identify the key service failure points, develop the corresponding service remedy measures, reduce the loss from service failures, and improve the service quality.

Benchmarking the risk assessment in green supply chain using fuzzy approach to FMEA

2018 ◽  
Vol 25 (8) ◽  
pp. 2660-2687 ◽  
Author(s):  
Sachin Kumar Mangla ◽  
Sunil Luthra ◽  
Suresh Jakhar
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Failure Mode ◽  
Failure Modes ◽  
Research Work ◽  
Evaluation Framework ◽  
Green Supply Chain ◽  
Content Type ◽  
Efficient Management ◽  
Fmea Analysis

PurposeThe 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.Design/methodology/approachInitially, 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.FindingsResults 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.Originality/valueThe 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.

scholarly journals A Proactive Risk Assessment Through Healthcare Failure Mode and Effect Analysis in Pediatric Surgery Department

2020 ◽  
Vol 11 (3) ◽  
Author(s):  
Yasamin Molavi-Taleghani ◽  
Hossein Ebrahimpour ◽  
Hojjat Sheikhbardsiri
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Pediatric Surgery ◽  
Failure Modes ◽  
Cross Sectional Study ◽  
Related Factors ◽  
Cross Sectional ◽  
Effect Analysis ◽  
Acceptable Risks ◽  
Surgery Department

Background: Patient safety is the first step to improve the quality of care. Objectives: Therefore, the present study aimed to examine the risk assessment of processes in a pediatric surgery department using the Health Failure Mode and Effect Analysis (HFMEA) in 2017 - 2018. Methods: In this research, a mixed-method design (qualitative action and quantitative descriptive cross-sectional study) was used to analyze failure mode and their effects. The nursing errors in the clinical management model were used to classify failure modes, and the theory of inventive problem solving was used to determine a solution for improvement. Results: According to the five procedures selected by the voting method and their rating, 25 processes, 48 sub-processes, and 218 failure modes were identified with HEMEA. Eight risk modes (3.6%) were found as non-acceptable risks and were transferred to the decision tree. The main root causes (hazard score ≥ 4) were as follows: Technical-related factors (14.34%), organizational-related factors (31.9%), human-related factors (45.3%), and other factors (7.6%). Conclusions: The HFMEA method is very effective in identifying the possible failure of treatment procedures, determining the cause of each failure mode, and proposing improvement strategies.

A failure mode and risk assessment method based on cloud model

2019 ◽  
Vol 31 (6) ◽  
pp. 1339-1352 ◽  
Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang ◽  
Yan He
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Cloud Model ◽  
Assessment Method ◽  
Risk Assessment Method

scholarly journals Agricultural Risk Management Using Fuzzy TOPSIS Analytical Hierarchy Process (AHP) and Failure Mode and Effects Analysis (FMEA)

Agriculture ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 504
Author(s):  
Peyman Zandi ◽  
Mohammad Rahmani ◽  
Mojtaba Khanian ◽  
Amir Mosavi
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Failure Mode ◽  
Analytical Hierarchy Process ◽  
Failure Modes ◽  
Fuzzy Topsis ◽  
Control Measures ◽  
Management Tool ◽  
Agricultural Risk ◽  
Hierarchy Process

Failure mode and effects analysis (FMEA) is a popular technique in reliability analyses. In a typical FMEA, there are three risk factors for each failure modes: Severity (S), occurrence (O), and detectability (D). These will be included in calculating a risk priority number (RPN) multiplying the three aforementioned factors. The literature review reveals some noticeable efforts to overcome the shortcomings of the traditional FMEA. The objective of this paper is to extend the application of FMEA to risk management for agricultural projects. For this aim, the factor of severity in traditional FMEA is broken down into three sub-factors that include severity on cost, the severity on time, and severity on the quality of the project. Moreover, in this study, a fuzzy technique for order preference by similarity to ideal solution (TOPSIS) integrated with a fuzzy analytical hierarchy process (AHP) was used to address the limitations of the traditional FMEA. A sensitivity analysis was done by weighing the risk assessment factors. The results confirm the capability of this Hybrid-FMEA in addressing several drawbacks of the traditional FMEA application. The risk assessment factors changed the risk priority between the different projects by affecting the weights. The risk of water and energy supplies and climate fluctuations and pests were the most critical risk in agricultural projects. Risk control measures should be applied according to the severity of each risk. Some of this research’s contributions can be abstracted as identifying and classifying the risks of investment in agricultural projects and implementing the extended FMEA and multicriteria decision-making methods for analyzing the risks in the agriculture domain for the first time. As a management tool, the proposed model can be used in similar fields for risk management of various investment projects.

scholarly journals Risk Assessment for Failure Mode and Effects Analysis Using the Bonferroni Mean and TODIM Method

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 536 ◽  
Author(s):  
Jianghong Zhu ◽  
Bin Shuai ◽  
Rui Wang ◽  
Kwai-Sang Chin
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Failure Modes ◽  
Bonferroni Mean ◽  
Psychological Behavior ◽  
Analysis Technique ◽  
Safety And Reliability ◽  
Preference Interdependence ◽  
Fmea Method ◽  
Grey Relational

As a safety and reliability analysis technique, failure mode and effects analysis (FMEA) has been used extensively in several industries for the identification and elimination of known and potential failures. However, some shortcomings associated with the FMEA method have limited its applicability. This study aims at presenting a comprehensive FMEA model that could efficiently handle the preference interdependence and psychological behavior of experts in the process of failure modes ranking. In this model, a linguistic variable expressed by the interval-valued Pythagorean fuzzy number (IVPFN) is utilized by experts to provide preference information with regard to failure modes’ evaluation and risk factors’ weight. Then, to depict the interdependent relationships between experts’ preferences, the Bonferroni mean operator is extended to IVPFN to aggregate the experts’ preference. Subsequently, an extended TODIM approach in which the dominance degree of failure modes is calculated by grey relational analysis is utilized to determine the risk priority of failure modes. Finally, a practical example concerning the risk assessment of a nuclear reheat valve system is provided to demonstrate the effectiveness and feasibility of the presented method. In addition, a sensitivity analysis and comparison analysis are conducted, and the results show that the preference interdependence and psychological behavior of experts have an important effect on the risk priority of failure modes.

The Adhesion Failure Mode in Stainless Steel Trim Spring Operated Pressure Relief Valves

2012 ◽  
Author(s):  
Julia V. Bukowski ◽  
Robert E. Gross ◽  
William M. Goble
Keyword(s):  
Stainless Steel ◽  
Failure Mode ◽  
Failure Rate ◽  
Failure Modes ◽  
Service Failure ◽  
Failure Rates ◽  
Pressure Relief ◽  
Safety Integrity Level ◽  
Adhesion Failure ◽  
Pressure Relief Valves

This paper addresses dangerous failures of stainless steel (SS) trim spring operated pressure relief valves (SOPRV) due to a particular failure mode (SS-to-SS adhesion) which is not currently being included in SOPRV failure rates. As a result, current methods for estimating or predicting failure rates for SS trim SOPRV significantly underestimate these failure rates and, consequently, overestimate the safety provided by the SOPRV as measured by its average probability of failure on demand (PFDavg) or its corresponding safety integrity level (SIL). The paper also illustrates the critical importance of root cause analysis (RCA) of dangerous SOPRV failures in understanding the impacts of various failure modes. Over 1300 proof test results for both new and used SS trim SOPRV from the Savannah River Site (SRS) were identified. RCA was used on the failed valves to classify those failed due to SS-to-SS adhesions. Statistical analysis of the data convincingly demonstrates adhesions, previously assumed to be only an in-storage failure phenomenon, are also an in-service failure mode which needs to be included in SOPRV failure rates. The paper discusses the factors which potentially influence the adhesion failure mode and suggests a possible approach to including this mode in failure rate predictions. An example illustrates how current failure rate models overestimate SS trim SOPRV safety by one or two orders of magnitude.

scholarly journals A Comprehensive Failure Risk Assessment Method of Machining Center Component Based on Topology Analysis

2022 ◽  
Vol 12 (1) ◽  
pp. 423
Author(s):  
Liming Mu ◽  
Yingzhi Zhang ◽  
Guiming Guo
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Failure Modes ◽  
Assessment Method ◽  
Topology Analysis ◽  
Propagation Failure ◽  
Machining Center ◽  
Failure Risk ◽  
Risk Assessment Method ◽  
Influence Degree

The risk assessment of the failure mode of the traditional machining center component rarely considers the topological characteristics of the system and the influence of propagation risks, which makes the failure risk assessment results biased. Therefore, this paper proposes a comprehensive failure risk assessment method of a machining center component based on topology analysis. On the basis of failure mode and cause analysis, considering the correlation of failure modes, Analytic Network Process (ANP) is used to calculate the influence degree of failure modes, and it is combined with component failure mode frequency ratio and failure rate function to calculate independent failure risk. The ANP model of the machining center is transformed into a topological model, and the centrality measurement of network theory is used to analyze the topology of the machining center. The weight of the topological structure index is measured by subjective and objective weighting methods, and then the importance degree of the machining center component is calculated. In this paper, the coupling degree function is introduced to calculate the importance of the connection edge, which is combined with the failure probability to calculate the failure propagation influence degree, and the component propagation failure risk is calculated based on this. Finally, the independent failure risk and the propagation failure risk of the component are integrated to realize the failure risk assessment of the component. Taking a certain type of machining center as an example to illustrate the application, compared with the traditional assessment method, the effectiveness and advancement of the method proposed in this paper have been verified.

A Service Failure Modes Identifying Method to Realize Highly Reliable Services

2012 ◽  
Author(s):  
Yusuke Kurita ◽  
Koji Kimita ◽  
Yoshiki Shimomura
Keyword(s):  
Failure Modes ◽  
Service Providers ◽  
Service Failure ◽  
Effective Means ◽  
Support Service ◽  
Target Market ◽  
Practical Case ◽  
Service Engineering ◽  
Service Failures

Recently, service has been recognized as an effective means to enhance customer satisfaction. The importance of service is widely accepted. According to this background, the authors of this paper have carried out conceptual research on service design from the engineering viewpoint. The series of this research is called “Service Engineering.” In order to achieve a successful service, service providers should maintain the quality of their service and always satisfy their customers. Namely, the provision of highly reliable service is essential for service providers to survive in the target market. In order to realize highly reliable products or services, in general, it is an effective approach to prevent failures from occurring in use phase. In this study, we aim to support service failure analysis in order to minimize the occurrence of failures. This paper proposes a method for identifying the states of service failures. Specifically, we define service failure and propose a procedure to identify the states of service failures with models that are proposed in Service Engineering. The proposed method is verified through its application to a practical case.

The Adhesion Failure Mode in Stainless Steel Trim Spring-Operated Pressure Relief Valves

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
Julia V. Bukowski ◽  
Robert E. Gross ◽  
William M. Goble
Keyword(s):  
Stainless Steel ◽  
Failure Mode ◽  
Failure Rate ◽  
Failure Modes ◽  
Service Failure ◽  
Failure Rates ◽  
Pressure Relief ◽  
Safety Integrity Level ◽  
Adhesion Failure ◽  
Pressure Relief Valves

This paper addresses dangerous failures of stainless steel (SS) trim spring-operated pressure relief valves (SOPRV) due to a particular failure mode (SS-to-SS adhesion), which is not currently being included in SOPRV failure rates. As a result, current methods for estimating or predicting failure rates for SS trim SOPRV significantly underestimate these failure rates and, consequently, overestimate the safety provided by the SOPRV as measured by its average probability of failure on demand (PFDavg) or its corresponding safety integrity level (SIL). The paper also illustrates the critical importance of root cause analysis (RCA) of dangerous SOPRV failures in understanding the impacts of various failure modes. Over 1300 proof test results for both new and used SS trim SOPRV from the Savannah River Site (SRS) were identified. RCA was used on the failed valves to classify those failed due to SS-to-SS adhesions. Statistical analysis of the data convincingly demonstrates adhesions, previously assumed to be only an in-storage failure phenomenon, are also an in-service failure mode, which needs to be included in SOPRV failure rates. The paper discusses the factors which potentially influence the adhesion failure mode, and suggests a possible approach to including this mode in failure rate predictions. An example illustrates how current failure rate models overestimate SS trim SOPRV safety by 1 or 2 orders of magnitude.

Sign in / Sign up

Export Citation Format

Share Document