Fuzzy Failure Mode Research Articles

Sustainable design modifications municipal solid waste management network and better optimization for risk reduction analyses

The staggering rate of waste generation due to industrialization, urbanization and population growth has raised a pressing problem regarding environmental damages and human health hazards, especially in developing nations. Severe environmental and social risks such as surface and groundwater pollution, soil and air contamination, serious human health hazards and damage to aesthetic aspects are some inappropriate waste management results. To overcome these burdens and move toward sustainable municipal solid waste management, effective and efficient practices are required. This study deals with a sustainable municipal solid waste network design problem under uncertainty. For this purpose, a multi-objective fuzzy robust programming model with the aim of minimizing the total costs of the network and environmental damages and optimizing social impacts is proposed. Different practical waste treatment practices are considered in the proposed network, including incineration, recycling, composting and sanitary landfilling. Also, a risk that is related to the population of facilities’ potential location is introduced and the Fuzzy Failure Mode and Effects Analysis is applied to determine the value of the mentioned risk. In order to tackle uncertain parameters of the proposed model, the Fuzzy Robust Optimization approach is applied. The proposed multi-objective model solves as a single-objective model using the Fuzzy Goal Programming approach with Different Importance and Priorities. The applicability of the model is demonstrated through a real case study of Minudasht’s municipal solid waste management system. The optimal location with the least risk and environmental impacts for each treatment facility with related technology and method is introduced. Furthermore, sensitivity analysis has done on some parameters to determine the effect of parameters’ changes on objective functions. The results showed the effectiveness and efficiency of the proposed model.

Risk assessment of workshops at Iran University of Science and Technology Using Fuzzy FMEA

Introduction: Many safety accidents in various industries are caused by poor safety culture of employees. Therefore, safety training can play an essential role in reducing workplace accidents and any damage to students. According to the importance of university workshops, the purpose of this study was to identify and assess the safety and health risks of the foundry and machinery workshops of Iran University of Science and Technology.
 Methods: This descriptive study was conducted at Iran University of Science and Technology in the 2018. After identifying risks, the Fuzzy Failure Modes and Effect Analysis (FMEA) technique was used to identify and assess the RPN number of risks which is calculated by multiplying of Severity x Occurrence x Detection and all risks were prioritized based on the calculated RPNs. Finally, corrective actions are presented to reduce injury risks.
 Results: The RPN range of 10 potential hazards in the machinery workshop calculated from 5.8 to 230.3, and the RPN range of 19 potential hazards in the foundry workshop calculated from 1.3 to 665.3. The danger of " throwing lathe chuck wrench " with RPN=230/33 in machinery workshop and "melt throwing due to air retention in metal parts " with RPN=665/33 in foundry workshop received the top priorities.
 Conclusion: Based on the calculated results, it is expected that the implementation of proposed corrective actions and the development of educational programs to promote students' safety culture can reduce the level of existing risks significantly.

Seaweed Supply Chain Risk Identification in Sabah Using Fuzzy Failure Mode and Effect Analysis

Kappaphycus sp. and Eucheuma sp. were cultivated in Sabah, Malaysia, mainly to extract a compound called carrageenan which used in various industries including human food, pet food, fertiliser, and pharmaceutical. As any agricultural activities, seaweed industry also full with risks and uncertainties. This study hence was conducted to identify risk sources along the supply chain (SC) of seaweed cultivated in Sabah, Malaysia. Data were collected using face-to-face, in-depth interview with Key Informants (KIs) (n = 33). Interviews were transcribed and analysed using thematic analysis using ATLAS.ti. The analysed data then were further analysed using FMEA (Failure Mode and Effect Analysis) in integration with Fuzzy set theory for risk prioritisation. The result has shown that farmers faced 19 unique risks, while intermediaries 13 risks, and 16 risks on the customers part. The analysis also showed that the three most critical risks for with the highest fuzzy RPN number is exchange rate fluctuations, highly volatile global seaweed price and followed by changes in government policy. This research has successfully identified, categorised and assessed 18 most important risk sources that have the probability of disrupting the seaweed supply chain in Sabah. Should stakeholders or policymakers like to ensure the sustainability of the industry, those are the risks that should be paid more attention to increase the resilience of the SC.

Fuzzy failure mode and effect analysis application to reduce risk level in a ready-mixed concrete plant: A fuzzy rule based system modelling approach

In this study, failure mode and effect analysis were applied to evaluate and eliminate potential failure modes in a Ready-Mixed Concrete Plant using a fuzzy-rule-base system. The questionnaires were specially prepared for each sub-department such as production plant, workshop and maintenance, dumping grounds, materials transportation and storage, utilities, administrative office, social facility, quality control laboratory and wastewater pool and recycling facilities. The questions were answered by the workers in each section. Risk Priority Numbers (RPNs) and Fuzzy Risk Priority Numbers (FRPN), which measure potential failure modes, were calculated using the risk parameters. High-risk areas were identified, and some suggestions were made to reduce accident risk at the Ready-Mixed Concrete Plant. Three questionnaires were prepared, based on these suggestions, and distributed to workers to determine whether the suggestions would reduce the risk or not. Based on conditions at the time the recommendations were implemented and improvement rates were calculated. The results showed that the fuzzy failure mode and effect analysis methodology were effective in identifying and eliminating potential failure modes at the Ready-Mixed Concrete Plant. The results can also be used by other ready-mixed concrete manufacturers who want to improve the safety of their operations.

Diagnosing and routing electronic service quality improvement of academic libraries with the FMEA approach in an intuitionistic fuzzy environment

PurposeIn this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic fuzzy environment. Assessment of electronic service quality (ESQ) of libraries is significantly important according to their major roles. It should be noted that the ESQ has a significant impact on customer satisfaction, which improves organizational performance. Accordingly, low ESQ means waste of organizational resources and poor user satisfaction. So, there is a dire need to reflect reasons inducing failure modes in academic library ESQ. Thus, investigation of failure modes affecting academic library ESQ is highly important. One solution in this area is utilization of the intuitionistic fuzzy (IF) failure mode and effects analysis (FMEA) as one of the widely used methods for prediction and identification of failure modes.Design/methodology/approachThe present study in terms of objective is applied and in terms of the type of method is descriptive-analytical. The research sample included four experts of Yazd academic Libraries (Iran). To collect data, three types of questionnaires were distributed among experts. The purpose of the first questionnaire was to identify and reach an agreement on e-library failure modes. Type II questionnaire was used to determine the importance of identified risk factors and Type III questionnaire was used to prioritize the factors.FindingsResults indicate that the difficulty of using websites, lack of provided information feedback to users and lack of links on the website to users' are the main priorities for improving ESQ in the studied academic libraries.Originality/valueIn this approach, the Intuitionistic fuzzy Elimination Et Choix Traduisant la REalité and technique for order of preference by similarity to ideal solution method were used to rank failure modes in academic library ESQ within the FMEA framework.]

Quality Control of the Continuous Hot Pressing Process of Medium Density Fiberboard Using Fuzzy Failure Mode and Effects Analysis

In this paper, a fuzzy failure mode and effects analysis (FMEA) method is proposed by combining fault theory and a failure analysis method. The method addresses the problem of board thickness control failure and the problem of thickness deviation defect blanking, which can occur during continuous hot pressing (CHP) process, which is one of the most important processes in the production of medium-density fiberboard (MDF). The method combines the fault analysis with the Hamming code method and using the Hamming code to calculate and represent the cylinder array of the continuous hot-pressed thickness control execution unit to analyze and process the potential fixed thickness failure modes in MDF hot press production, and then summarizes the decision rules for controlling the board thickness and the level of sheet deviation. By combining the fuzzy FMEA method of the Hamming code and the logical OR operation of the experimental analysis, the method of thickness deviation and recognition control fault information for the CHP of MDF, which is proposed in this paper, permits the increase of the number of error levels, which makes optimization for controller more convenient and improves the efficiency to recognize errors.

An empirical study on the model of aged home-care service process improvement for the elders

The purpose of this study is to develop a model for the improvement of aged home-care service. According to the literature, degenerated services can strongly affect the efficiency of a service system. However, most previous studies attempted to solve this problem tend to be of conceptual nature. In contrast, this study extends Yu and Shie (2017)’s study and proposes a service-oriented innovation model by SERVQUAL-Kano model, Fuzzy Failure Mode Effect Analyze (Fuzzy FMEA) and TRIZ methodology. An integrated SERVQUAL and KANO model is used to analyze the potential service failures in the service process. Then, FMEA is employed to diagnose the possible causes and effects of the service failure model. Finally, TRIZ is used to develop the innovative solution for improving the service process. A case study of an aged home-care service agency is conducted to demonstrate the applicability of the proposed model, and a Multiple-criteria decision-making method, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is used to evaluate the priority of the candidate innovative solution. A post-survey was conducted to assess the improvement of service process and the advantages of the proposed model and the implications are summarized at the end of this article.

Quality control of crude palm oil (CPO) using define, measure, analyze, improve, control (DMAIC) and fuzzy failure mode and effect analysis

In this case, the company Crude Palm Oil (CPO) is still not able to produce palm oil that meets the specifications that can be seen from the free fatty acid content reaches 3.51%. This can affect the quality of the products to be able to compete with a competitor. Therefore, this study aims to conduct quality control of Crude Palm Oil (CPO), to analyse the proportion of disability and ability in the production process, potential failures, to identify the root cause of the defect, and to calculate the value of the highest FRPN. The results of the study showed that the biggest problem faced by parts of machine settings and control machines that are not good due to less rigorous and disciplined operator in charge and has a value of FUZZY FMEA (FRPN) most high at 662.06 While the measurement results the sigma value of the company is 3,16. The results of the study showed that the biggest problem faced by parts of machine settings and control machines that are not good due to less rigorous and disciplined operator in charge and has a value of FUZZY FMEA (FRPN) most high at 662.06.

Causal effect analysis of logistics processes risks in manufacturing industries using sequential multi-stage fuzzy cognitive map: a case study

ABSTRACT Any shortage and deviation in the implementation of logistics processes can lead to a poor performance and losing the market share of the manufacturer. To overcome this problem, the identification of existing risks in all logistics sub-processes, and taking corrective/preventive measures, is of great importance. In this study, a risk prioritization approach is presented based on a sequential multi-stage fuzzy cognitive map (SMFCM) and process failure mode and effects analysis (PFMEA) to prioritize logistics processes risks. This approach, in addition to considering a process-oriented view, prioritizes the logistics risks according to the amount of each risk’s impact on other risks through the internal and external-stage causal relationships as well as the values of risk factors. The score obtained from this approach can create enough distinction among the priorities of different risks in comparison with conventional risk priority number (RPN). Also, the results based on this score have a lower dependency on experts’ opinions by applying the Extended Delta Rule (EDR) learning algorithm. In fact, the intelligent nature of this approach enables decision-makers to identify critical risks and examine the status of the system at any time. The results of the implementation of the SMFCM-PFMEA approach in a manufacturing company active in the automotive spare parts industry confirm the superiority of this compared with the conventional score.

An integrated fuzzy framework for analyzing barriers to the implementation of continuous improvement in manufacturing

PurposeDelivering premium services and quality products are critical strategies for success in manufacturing. Continuous improvement (CI), as an underlying foundation for quality management, is an ongoing effort allowing manufacturing companies to see beyond the present to create a bright future. We propose a novel integrated fuzzy framework for analyzing the barriers to the implementation of CI in manufacturing companies.Design/methodology/approachWe use the fuzzy failure mode and effect analysis (FMEA) and a fuzzy Shannon's entropy to identify and weigh the most significant barriers. We then use fuzzy multi-objective optimization based on ratio analysis (MOORA), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy simple additive weighting (SAW) methods for prioritizing and ranking the barriers with each method. Finally, we aggregate these results with Copeland's method and extract the main CI implementation barriers in manufacturing.FindingsWe show “low cooperation and integration of the team in CI activities” is the most important barrier in CI implementation. Other important barriers are “limited management support in CI activities,” “low employee involvement in CI activities,” “weak communication system in the organization,” and “lack of knowledge in the organization to implement CI projects.”Originality/valueWe initially identify the barriers to the implementation of CI through rigorous literature review and then apply a unique integrated fuzzy approach to identify the most important barriers based on the opinions of industry experts and academics.

Failure mode effect and criticality analysis using dempster shafer theory and its comparison with fuzzy failure mode effect and criticality analysis: A case study applied to LNG storage facility

Failure mode effects and criticality analysis (FMECA) is widely used, by developing a Risk Priority Number (RPN), to identify the failure modes and to prioritize them. But this has been extensively criticized due to several drawbacks in the literature. This issue can be solved partly by using Fuzzy FMECA (FFMECA) although Fuzzy logic itself has been criticized of having a direct bearing on subjectivity. This paper makes use of Dempster-Shafer Theory (DST) of evidence-a proper mathematical framework to deal with the epistemic uncertainty often affecting the input evaluations of risk parameters. DST based FMECA is capable of providing an appropriate, precise and fault-free, failure mode prioritization. Belief and Plausibility distributions are used to synthesize the obtainable information and to make them useful for the purpose. The results obtained from DST-FMECA is compared to the results drawn from the FFMECA applications (already conducted in the liquefied natural gas (LNG) storage facility) to validate FFMECA and vice versa. The comparative results presented in this paper establish the capabilities of both the approaches, especially in a complex system like the LNG storage and similar facilities where even a minor failure may lead to catastrophic effects.

Identification of institutional risks of SMEs supply chain using the fuzzy failure mode and effect analysis

Institutional problems experienced by SMEs pose institutional risks that may affect their supply chain. The variables include involved actor, relationship and institution. The actor as a variable poses the risks of technical and intellectual knowledge, and negotiation skills, not to mention the issues of commitment, communication and responsibility. The relationship as a variable revolves around the issues of trust, honesty and motivation to improve, frequent conflicts, and limited information. Other institutional variables pose the risks of under-developed business networks and insufficient government involvement and training, and fundings. These risks must be handled properly and correctly. This study was aimed to identify and to assess institutional risks in supply chains. The risk identification and assessment in this research employed the Fuzzy Failure Mode and Effect Analysis (Fuzzy FMEA). The result from analysing five randomly selected SMEs revealed that the prioritised risks for actor as a variable included the lack of intellectual knowledge and poor commitment level. The prioritised risk for relationship as a variable was the lack of motivation to improve together. The prioritised risk for other institutional variables was the limited funding from other institution.

The risk assessment analysis of corn chips supply chain using Fuzzy FMEA

Lembah Hijau is one of the SMEs which produces corn chips in Lamongan District. This SME cooperates with corn farmers and retailers who joined the supply chain of corn chips. The uncertainty of the maize cropping pattern, the production process that depends on weather conditions, and the demand for fluctuating corn chips are the factors that can trigger a variety of risks. The research objective was to identify and assess the risk of corn chips’ supply chain in Lembah Hijau and to mitigate the risks. The method used to assess the risk is Fuzzy Failure Mode Effect Analysis (FMEA) by using the questionnaires which were filled by five expert respondents. The raw material, production process and marketing are the variables that will be reviewed. The results showed that by identifying the risk of corn chip supply chain, 14 risks consisting of 3 risks in the raw material variable, 6 risks in the production process variable and 5 risks in the marketing variables were found. Based on the highest Fuzzy Risk Priority Number value of raw material variable, the risk found was the fluctuation of corn price. Meanwhile, the risk in the production process variable was the weather conditions that do not support the production process and the risk in the marketing variable was the return of corn chips product.

Risk analysis by integrated fuzzy expected value method and fuzzy failure mode and effect analysis for an elevated metro rail project of Ahmedabad, India

Risk identification and analysis for complex mega infrastructure projects has become an integral part of the present day project management process. This paper aims to develop an integrated Fuzzy Expected Value Method (FEVM) and Fuzzy Failure Mode and Effect Analysis (FFMEA) method for a complex infrastructure project such as the construction of an elevated corridor for metro rail in Ahmedabad, India. The design and methodology adopted in this research work was a primary data survey, where the major risky activities of an elevated metro rail infrastructure project were identified through interactions with experts, questionnaire surveys, and personal experience. The identified risks were analyzed for likelihood, impact, severity, detection, occurrence and risk priority numbers. Further computations of fuzzy risk severity (FRS), fuzzy risk priority score (FRPS), and risk rankings were carried out through the new application of integrated fuzzy EVM and fuzzy FMEA methods. It has been found that land acquisition, feasibility, tendering, segment erection, segment casting, obligatory span, construction planning, launching girder, road widening, piles and piers activities were highly risky and had very high fuzzy risk severity and FRPS values (0.605–0.775). Risk mitigation measures were proposed for all critical activities of the elevated metro project in Ahmedabad.

A novel fuzzy bi-objective vehicle routing and scheduling problem with time window constraint for a distribution system: A case study

In the process of hazardous material transportation, the risk is a significant factor that should be considered due to the potential severe consequence of an incident. Regardless of risks, time is a paramount concern that should be considered in hazardous material transportation. In this way, this paper introduces a bi-objective model for a vehicle routing and scheduling problem of hazardous material distribution problems under the fuzzy condition to minimize both total distribution time and risks. In the proposed model, the fuzzy inference system and fuzzy failure mode and effects analysis are applied to identify and calculate the high-level risks instead of the previous simple methods for the first time. Moreover, Jimenez method and fuzzy goal programming are respectively utilized to convert the fuzzy bi-objective model into the same crisp and single-objective one. Besides, to cope with the NP-hardness of the large-sized problems, two meta-heuristic algorithms namely invasive weeds optimization and genetic algorithm is used, and several sensitivity analyses are performed to prove the efficiency of the proposed approach. The performance of the proposed algorithms is also assessed through a comparative study. Finally, the proposed model is implemented to a real case study to prove the validity of the model.

Interactive scenario analysis of banking credit risks in intuitive fuzzy space

Purpose The purpose of the paper is to bring attention to documentary credits and the efforts to reduce debt obligations in credit history is recognized as an important source of uncommitted bank earnings. Credit risk has a significant impact on the stability of the banking system. This paper identifies the types of credit risk in the banking supply chain. Design/methodology/approach The authors model the types of credit risk using the intuitive fuzzy failure modes and effects analysis (IFMEA) and intuitive fuzzy cognitive mapping. The population of the study that is needed for the interviews and expert panels comprises senior managers and experts of a leading bank in Iran. The respondents are experienced in credit and banking risk and were selected through judgment sampling and snowballing. Findings The findings suggest that reducing the risks of the foreign letters of credit contracts can mitigate the risk in the agricultural sector, the specific risks of rent-to-own contracts, the risk of the long-term facilities and the specific risk of the domestic letter of credit contracts. Originality/value This research investigates Iran Tejart Bank’s credit risk, formulates a model of the types of credit risk present and analyzes them using the intuitive fuzzy failure modes and effects analysis and intuitive fuzzy cognitive map. Through this credit risk model, one can then facilitate risk management for better financial stability. Also, the model can be used to evaluate the risk indicators.

An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA

Failure mode and effect analysis (FMEA) is a proactive risk assessment technique, which has been widely used by engineers to meet the safety and reliability requirements of processes, products, structures, services, and systems. The major aim of the FMEA technique is to rank the failure modes according to their risk levels and subsequent actions are performed to eliminate/mitigate their consequences. In a typical FMEA, for each failure mode, three risk factors, namely severity (S), occurrence (O) and detection (D) are evaluated and a risk priority number (RPN) is estimated by multiplying these risk factors. In recent years a significant effort has been underway and different approaches have been proposed to improve FMEA, to overcome its several drawbacks. We notice that there is a significant amount of literature based on multi-criteria decision making (MCDM) methods, which have been solely aimed to improve the risk estimation process in FMEA by overcoming the drawbacks of the traditional FMEA technique. In this work, we propose a novel integrated MCDM approach by combining Fuzzy Analytical Hierarchy Process (FAHP) with the modified Fuzzy Multi-Attribute Ideal Real Comparative Analysis (modified FMAIRCA). At first, we calculate the fuzzy relative importance between the risk factors by using the FAHP method and then we use those importance values in our proposed modified FMAIRCA to rank the failure modes according to their risk level. Our modified FMAIRCA method is computationally inexpensive and is able to provide more viable decisions. We consider a benchmark example in FMEA domain to validate the ability of our integrated approach and highlight the usefulness of the same. Further, we compare the ranking result with other MCDM methods - FVIKOR, FCOPRAS, FMOORA, FMABAC, FTOPSIS and sensitivity analysis is also performed to highlight the robustness of the proposed approach.

Implementation of fuzzy-based integrated framework for sesame seed separator development

In the current scenario, mechatronics-based new product development requires a multi-disciplinary approach for the interaction of mechanics, electronics and software requirements in order to enhance the system effectiveness. This work aims in developing a strategic methodology for making decisions during mechatronics-based new product development. This methodology integrates six different stages of processes, namely identification of the need for new product; conceptual design and development of the new product through fuzzy Delphi method, fuzzy interpretive structural modeling, fuzzy analytical network process and fuzzy quality function deployment algorithms; development of detailed design using computer-aided design/computer-aided engineering and control system software; development of prototype model; analysis of the developed prototype model and finally provide recommendations for product commercialization. The proposed methodology is applied for the design and development of mechatronics-based new product, namely sesame seed separator for agricultural sector. The performance of the developed prototype model of sesame seed separator is analyzed for the potential failures using Fuzzy VIKOR-based fuzzy failure mode and effect analysis (FMEA). Based on the results of fuzzy FMEA, the developed prototype model is redesigned and then finally recommended for commercialization. The framework enhances the product development process and reduces repair and rework.

A decision support model for risk management of hazardous materials road transportation based on quality function deployment

Risk management of hazardous materials (hazmats) road transportation has long been a concern because of the potential hazards that poses to society and the environment. In this work, a systematic and semi-quantitative decision support framework for risk management of hazmats road transportation based on the combination of quality function deployment (QFD), fuzzy analytic hierarchy process (F-AHP), fuzzy failure mode and effect analysis (F-FMEA), and nonlinear goal programming is proposed. The QFD is used innovatively to construct the overall framework, which contains three main components of general risk management: risk identification, risk assessment, and risk control. The F-AHP is used to build a hierarchical risk assessment system and determine the importance rating of each risk factor. The F-FMEA is used to evaluate the potential risks of risk control measures and determine the risk adjustment coefficient of each risk measure, which is used subsequently to modify the fulfillment level of risk measure in the nonlinear goal programming model. To address the inherent vagueness and uncertainty contained in the risk management process, the fuzzy set theory is introduced as an effective tool. An empirical case on risk management of a hazmats transportation company is presented to demonstrate the effectiveness and feasibility of the proposed methodology. Some managerial implications on risk management of hazmats road transportation are provided based on the obtained findings.

Supplier Selection Model Based on Risk in an Indonesian Healthcare Service Industry

In Indonesia, healthcare services are a priority industry sector. In the last few periods, every health care provider began to evaluate and make a performance improvement of the entire supply chain. Supplier selection is one of supply chain business process that have some risks. Therefore, this research is conducted to identify and reduce various risks in supplier selection process. The method used is Fuzzy Failure Mode and Effect Analysis (FFMEA) with three main stages, i.e. fuzification, rule evaluation and difuzification. The result show that there are four criteria, i.e. price, communication, quality and delivery time used for supplier selection in an Indonesian healthcare industry. Each criterion has some supplier performance risks with a total of 10 failure modes. The integration of risk factors in supplier selection model have been successfully done with one best suppliers based on the lowest risk score.