Search results

This study aims to develop a risk prioritization process using failure mode and effect analysis (FMEA) in association with composition of probabilistic preferences (CPP) and weighting the risk analysis criteria. It seeks to develop decision-making considering the fast response necessary to achieve project objectives in complex scenarios, such as the pandemic of COrona VIrus Disease 19 (COVID-19).

After identifying the risks, the prioritization process was applied to a project in the oil and gas area, in which a focus group assessed these risks. This evaluation took place employing traditional FMEA, FMEA with CPP by axes considering four points of view and FMEA with CPP by weighted sum with the use of a multicriteria method to weight the criteria. These approaches were compared to understand their differences and benefits, with a flow chart being developed, consolidating the procedure.

The methodologies that showed the greatest benefits were FMEA with CPP by axes PO (progressive-optimistic) and by weighted sum. Essentially, this was mainly related to the interrelationship between risks and to the importance of prioritization.

This procedure can consider company's views on what is critical and the interrelationship between risks. It provides a clear segmentation of what should and should not be prioritized. It was also developed in a practical case, showing a possible alternative to support fast responses in decision-making.

This paper aims to identify and reduce possible process failures occurred in warehouse.

This research used risk analysis method FMEA combined with fuzzy-analytical hierarchy process (AHP). Design FMEA will direct the failure mode or failure of components into levels and will use it to analyze the product before it used in manufacturing processes. Design FMEA has a major point on the failure mode that caused inefficiency in the design while fuzzy-AHP used to reduce subjectivity in the weighting process.

The results show that high inventory is the dominant factor that must be controlled by the company to prevent the risk of failure processes in the warehouse, followed by the number of stocks that do not match with existing records, and misplacement of machines and/or materials.

This research used risk analysis method FMEA combined with fuzzy-AHP to identify and reduce the possible process failures in warehousing.

The tightening operations are one of the most critical operations in automotive assembly lines because of its direct impact on customer safety. This study aims to evaluate the major complexity drivers for manual tightening operations, correlate with real tightening failure data and propose mitigations to improve the complexity.

In the first stage, the complexity drivers for manual tightening operations were identified. Then, the relative importance of the risk attributes was defined by using pairwise comparisons questionnaire. Further, failure mode effect analysis–analytic hierarchy process (FMEA–AHP) and AHP ratings methods were applied to 20 manual tightening operations in automotive assembly lines. Finally, the similarities between the revealed results and the real failure rates of a Turkish automotive factory were examined and a sensitivity analysis was conducted.

The correlation between the proposed methods and manual tightening failure data was calculated as 83%–86%. On the other hand, the correlation between FMEA–AHP and AHP ratings was found as 92%. Poor ergonomics, operator competency and training, operator concentration-loose attention fatigue, manual mouthing before the tightening operation, frequent task changes, critical tightening sequence, positioning of the part and/or directional assembly were found relatively critical for the selected 20 tightening operations.

This is a unique study for the evaluation of the attributes for manual tightening complexity in automotive assembly lines. The output of this study can be used to improve manual tightening failures in manual assembly lines and to create low complexity assembly lines in new model launches.

The purpose of this paper is to primarily focus on labor in maintenance areas, addressing human rights issues, labor standards and safety standards. The main issue is to investigate how these factors are considered to drive the prioritization of maintenance interventions within maintenance plans. In particular, a method for criticality analysis of production equipment is proposed considering specific labor issues like age and gender, which can be useful to steer maintenance plans toward a more social perspective.

The authors focus on the two main social issues of SA 8000 norms, age and gender, exploring how these issues may drive the selection of maintenance policies and the relative maintenance plans. The research is conducted through fuzzy analytical hierarchy process (AHP) implemented within a failure mode effects analysis (FMEA).

The research is conducted through fuzzy AHP implemented within a FMEA. The maintenance plans resulting from the FMEA driven by social issues are evaluated by a benchmark of three different scenarios. The results obtained allowed the firm to evaluate maintenance plans, considering the impact on workers’ health and safety, the environment, social issues like gender and age.

One of the main limitation of this research is that it should also encompass maintenance costs under social and safety perspective. The method developed should be extended by further study of maintenance planning decisions subject to budget constraints. Moreover, it would be worth evaluating the effect of adopting more proactive maintenance policies aimed at improving plant maintainability in view of what emerged during the test case in the presence of an aged workforce and the subsequent need to prevent and/or protect people from hidden risks.

With reference to the results obtained from the two models of this scenario, the authors observed an increase of equipment criticality, from B class to the A class, and similarly from C class to B class. No equipment has reduced its criticality. This depends on the particular context and the relative weights of drivers indicated in its AHP matrixes.

The paper addressed the main social implication as well as other social issues represented by age and gender factors, which are normally neglected. The Action Research (AR) proved the effects resulted from considering either gender factor or gender and age factors at the same time for maintenance policy selection. All in all, an increase of criticality is evident even if “people” is a driver with less importance than “environment” and “structures.”

The present work focussed on a new definition of a criticality ranking model to assign a maintenance policy to each component based on workers’ know-how and on their status. The approach is conceived by the application of a fuzzy logic structure and AHP to overcome uncertainties, which can rise during a decision process when there is a need to evaluate many criteria, ranging from economic to environmental and social dimensions.

The purpose of this study is to address supplier evaluation and selection in a constrained environment of advance purchasing. The study presents the potential solutions to supplier evaluation and selection issues in the Indian automobile sector where advance purchases are carried out to fulfill the supply chain demand.

Based on the literature review and expert elicitation, nine major factors which are responsible for the successful implementation of supplier selection in a constrained environment of advance purchasing are identified. This paper explores supplier selection in constrained environment issues based on an integrated method based on Shannon entropy, analytic hierarchy process (AHP) techniques and failure mode effects analysis (FMEA).

Analysis of the results of the study suggests that traditional suppliers are not suitable in advance purchasing scenarios; hence, criteria developed in this paper to accommodate the requirement of advance purchasing with possible risk considerations are of high importance. This research paper is an original attempt to develop supplier selection criteria for advance purchasing with special identification of deliverability, flexibility, innovation and productivity factors through a case demonstration.

This study uses data from secondary sources, literature reviews and expert opinions. It formalizes the important factors of successful supplier selection in the constrained environment of advance purchasing in the automotive industry context.

The paper shows how the engagement of suppliers through advance purchasing helps automotive companies in developing a competitive advantage. The integrated approach of Shannon entropy, AHP techniques and FMEA is an effective and useful method that can be applied to the supplier selection process.

The proposed FMEA-AHP method integrated with Shannon entropy used for evaluation represents a useful tool to embrace the suitable functioning tactics for efficient supplier selection. The study is unique as supplier evaluation and selection in a constrained environment of advance purchasing is not investigated much and has good industry applicability.

The purpose of this paper is to classify the main barriers related to the implementation of lean supply chain management (LSCM) and prioritize its main practices. A case study approach was conducted to obtain values for the intensity of the relationship between LSCM practices and barriers to mitigate or even anticipate difficulties in its implementation.

The case study in a company in southern Brazil that is in lean implementation is used for conducting this research. The methodology was structured in three steps, namely, classification of the main barriers through risk analysis, selection of LSCM practices appropriate to the company context and ranking and prioritization of the main practices of LSCM related to the barriers to lean implementation.

As a result, with the combination of two approaches, failure mode and effect analysis (FMEA) and analytical hierarchical process (AHP), it was possible to obtain values for the intensity of the relationship between LSCM practices and barriers. From the 12 barriers, 5 reached a high-risk degree that can be mitigated, and among the 18 practices found, 7 have the potential to be implemented.

This research allows direct efforts to continuously improve the supply chain to mitigate or even anticipate difficulties in its implementation. The proposed methodology, combining FMEA and AHP is easy to apply and understand, allowing managers and professionals to replicate it in the context of their supply chain and verify results similar and comparable to those obtained here.

Due to the warming at the automotive market in the last years and consequently the growth of vehicle production has been moved and placed emphasis on the segment. In recent years, some have known, for example, as the earthquake that struck Japan in 2011 was able to disrupt the suppliers of the country. Due to these events, supply chain risk management has become essential to the supply chain operations success. The purpose of this paper is to evaluate the supplier’s systematic selection at the automotive industry compared with the identified models in the literature.

A case study applied at the automotive to propose a method for selecting suppliers considering the risk management.

These results indicate that the organization has established criteria for suppliers selection, this systematic aims to identify the potential risks in the supply chain before the supplier award the project but it’s also the current practice can be improved using as reference the comparative method as applied in this study.

The risk management, a few discussed topic but on the rise among researches, show that the companies, especially those inserted in the automotive segment has been used different techniques for selecting suppliers to focus in a better supply chain control. Establish criteria for selecting suppliers means identifying in advanced the potential risks that the suppliers may offer to the organization during the supply to avoid any interruptions to supply.

Given the critical role of project prioritization and selection process in Six Sigma efforts, this study aims to analyse the relevant literature to answer this question: What types of project prioritization and selection methods have been used in Six Sigma research?

The study implemented the systematic literature review (SLR) method to identify and review all relevant previous studies.

The study revealed that 59 articles focused on the topic used 111 methods, analytic hierarchy process appeared as the most frequently used method with 12 articles (20%) and one-third of the methods used in the current Six Sigma project selection literature contained multi-criteria decision-making methods. In total, 61% of 59 articles were not published in the journals ranked by the ABDC’s list. Only 17% of the articles reviewed in this study were published in journals ranked as B category and 12% of the articles were published in A category journals.

The findings of this literature review may help Six Sigma practitioners and researchers accurately identify project prioritization and selection methods, considering that qualitative and quantitative scientific methods guarantee to make better decisions than “gut feelings” of the decision makers in this process.

Although a variety of studies focused on the topic, an SLR is lacking in the area of Six Sigma project prioritization and selection. Therefore, this study was constructed using the SLR method to analyse the topic.

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.

The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation.

Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the prospect-theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their risk priority numbers (RPNs). In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts.

The results are very much in line with prospect theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm's attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure and operator failure, respectively.

The originality of this paper consists in integrating prospect theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA's RPNs.