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The purpose of this paper is to enhance the performance of maintenance in a solar power plant by implementing the proactive maintenance (PaM) strategy, measured by the availability and the total maintenance workload.

The prior maintenance strategy was reviewed, and then the strategy was adjusted to focus on PaM. Failure modes and effects analysis (FMEA) was a tool for analyzing the severity and occurrence of the failure modes and effects. Then, the Why‒Why analysis was used for investigating the root causes of failures. The countermeasures were drawn, and the preventive maintenance (PM) plan was revised and carried out. The total maintenance, the PaM and reactive maintenance workload, was obtained, and then the improvements were determined. The values of availability were also obtained.

Previously, the appeared maintenance strategy was not clearly defined. It seemed to have reactive maintenance coupled with PM; it was checked once a year, and corrective actions were made when something wrong was found. Then the management team observed an increase in the reactive maintenance workload, whereas the values of availability were not consistent and tended to drop. After implementing the new maintenance strategy, PaM, the total maintenance workload decreased 14 percent in one year. The average availability of the solar power plant improved from 0.9943 to 0.9969, and the values of availability had better consistency.

The PaM can be applied to solar power plant without limiting the prior maintenance strategy and the complexity of production or machinery. The solar power plant is a quite simple production, and most machines consist of electrical equipment and electrical circuits. The PaM supports to analyze the failure modes, the consequence of the failure events and failure effects, and to decide what should be done. Importantly, PaM can reduce total maintenance workload while the value of availability is higher and consistent.

This paper states how to successfully implement the PaM for the solar power plant. Previously, the plant did not have a clearly defined maintenance strategy; it was checked once a year, and it was corrected when abnormalities were detected. The PaM strategy provides tools and processes for failures and effects analysis. Although there was a more workload of PM, the total maintenance workload decreased, even in the first year.

The purpose of this paper is to introduce an integrated approach using failure modes and effects analysis (FMEA), multiple-criteria decision making (MCDM), mathematical modeling and quality function deployment (QFD) techniques, for risk assessment and service quality enhancement in coronary artery bypass grafting (CABG) as a treatment for cardiovascular diseases (CVDs).

First, the disruptions in the CABG process are identified and prioritized following FMEA instructions, using two MCDM techniques, called analytic hierarchy process (AHP) and TOPSIS. Consequently, several corrective activities are identified and weighted on the basis of QFD. Finally, a mathematical model is established to determine the most cost-effective activities for implementation. The approach is developed in a fuzzy environment to reflect the uncertainty and ambiguity of human reasoning.

Regarding the CABG process disruption, a total of 30 failure modes in four main categories were identified and prioritized. Moreover, eight corrective activities were devised and ranked according to their impact on the failure modes. Finally, considering a limited amount of budget, a sensitivity analysis on the mathematical model’s objective function indicated that using 30 percent of the total budget, required to implement all corrective activities, was enough to cover more than 70 percent of the effects of corrective activities on the failure modes.

This paper contributes to the quality risk assessment knowledge by introducing an integrated approach to evaluate and improve healthcare services quality. Also, the case study conducted on the CABG process has not been done by other related studies in the literature.

The purpose of this paper is to report a research in which fuzzy assessment of failure mode and effect analysis (FMEA) was examined on the design of rotary switches.

In the case study reported in this paper, fuzzy FMEA of a rotary switch was analysed, starting from its individual components to subsystems. Failure modes were identified and the effect of these modes was studied, then the results before and after taking actions were compared.

The usage of fuzzy FMEA enabled the reflection of real situation for determining the interdependencies among failure modes and effects of rotary switches with the incorporation of knowledge and expertise of experts.

The assessment has been attempted on a single rotary switch assembly. In future, this method can be applied in complex systems.

The paper shows that the method enabled the decision makers to share information from various working groups.

The case study has been conducted in a rotary switches manufacturing organisation and the results before and after improvement have been compared.

In 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.

The 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.

Results 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.

In 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.]

Assessing the severity of failure modes of critical industrial machinery is often considered as an onerous task and sometimes misinterpreted by shop-floor engineer/maintenance personnel. The purpose of this paper is to develop an improved FMECA method for prioritizing the failure modes as per their risk levels and validating the same through a real case study of induction motors used in a process plant.

This paper presents a novel hybrid multi-criteria decision-making (MCDM) approach to prioritize different failure modes according to their risk levels by combining analytical hierarchy process (AHP) with a newly introduced MCDM approach, election based on relative value distance (ERVD). AHP is incorporated in the proposed approach to determine the criteria weights, evaluated in linguistic terms by industrial expert. Furthermore, ERVD, which is based on the concept of prospect theory of human cognitive process, is applied to rank the potential failure modes.

It is found that the proposed FMECA approach provides better results in accordance with the actual industrial scenario and helps in effectively prioritizing the failure modes. A comparison is also made to highlight the differences of results between the proposed approach with TOPSIS and conventional FMECA.

This research paper proposes an improved FMECA method and, thus, provides a deep insight to maintenance managers for effectively prioritizing the failure modes. The correct prioritization of failure modes will help in effective maintenance planning, thus reducing the downtime and improving profit to the organization.

A real case of process plant induction motor has been introduced in the research paper to show the applicability of this decision-making approach, and the approach is found to be suitable in correct prioritization of the failure modes.

Severity has been decoupled into various factors affecting it, to make it more relevant as per actual industrial scenario. Then, a novel modified FMECA has been developed using a hybrid MCDM approach (AHP and ERVD). This hybrid method, as well as its application in FMECA, has not been developed by any previous researcher. Moreover, the same has been thoroughly explained by considering a real case of process plant induction motors and validated with cross-functional experts.

The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.

A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.

The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.

Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.

Describes a new technique for prioritizing failures for corrective actions in failure mode and effects analysis (FMEA). This technique extends the risk prioritization beyond the conventional risk priority number (RPN) method. A new scale has been defined. The ranks 1 through 1,000 are used to represent the increasing risk of the 1,000 possible severity‐occurrence‐detection combinations, called risk priority ranks (RPRs). The failures having a higher rank are given higher priority. This approach resolves some of the shortcomings in the traditional RPN technique. Traditionally, FMEA identifies the risk associated with a product failure through assignment of a standard RPN. A fundamental problem with FMEA is that it attempts to quantify risk without adequately quantifying the factors that contribute to risk. In particular cases, RPNs can be misleading. This deficiency can be eliminated by using the new technique. A methodology combining the benefits of matrix FMEA and the new technique as stated above is presented.

Companies in diverse branches offer a variety of service alternatives that typically differ in terms of the degree to which customers are actively involved in service delivery processes. The purpose of this paper is to explore potential differences in consumers’ reactions to service failures across services provided by a service employee (i.e. full-services) and services that require customers’ active involvement (i.e. self-services).

Two 2 (full-service vs self-service) × 2 (no service failure vs service failure) scenario-based experiments in technological and non-technological contexts (i.e. ticket purchase and furniture assembly) were conducted.

Study results reveal that although service failures have a similar negative impact on satisfaction across both full-services and self-services, in the self-service context, the negative effect on the willingness to use the same service delivery mode again is attenuated.

By emphasizing the role of customers’ active involvement in the service delivery process, the study extends previous knowledge regarding customer response to service failures in different service settings.

By highlighting that self-service customers’ future behavioral intentions are less severely affected by service failures, the authors present an additional feature of customer involvement in service delivery processes that goes beyond the previously recognized advantages.

Despite the abundance of research on the effects of failure attributions, previous studies have predominantly examined main effects of attributions on customer responses, such that insights into potential moderating effects of failure attributions on established relationships – as investigated in this study – are still scarce.

The purpose of this paper is to present issues and challenges of scheduled maintenance task development within the maintenance review board (MRB) process, and to find potential areas of improvement in the application of the MSG‐3 methodology for aircraft systems.

The issues and challenges as well as potential areas of improvement have been identified through a constructive review that consists of two parts. The first part is a benchmarking between the Maintenance Steering Group (MSG‐3) methodology and other established and documented versions of reliability‐centred maintenance (RCM). This benchmarking focuses on the MSG‐3 methodology and compares it with some RCM standards to identify differences and thereby find ways to facilitate the application of MSG‐3. The second part includes a discussion about methodologies and tools that can support different steps of the MSG‐3 methodology within the framework of the MRB process.

The MSG‐3 methodology is closely related to the RCM methodology, in which the anticipated consequences of failure are considered for risk evaluation. However, MSG‐3 considers neither environmental effects of failures nor operational consequences of hidden failures. Furthermore, in MSG‐3, the operational check (failure‐finding inspection) is given priority before all other tasks, whereas in RCM it is considered as a default action, where there is no other applicable and effective option. While RCM allows cost‐effectiveness analysis for all failures that have no safety consequences, MSG‐3 just allows it for failures with economic consequences. A maintenance program that is established through the MRB process fulfils the requirements of continuous airworthiness, but there is no foundation to claim that it is the optimal or the most effective program from an operator's point‐of‐view. The major challenge when striving to achieve a more effective maintenance program within the MRB process is to acquire supporting methodologies and tools for adequate risk analysis, for optimal interval assignments, and for selection of the most effective maintenance task.

The paper presents a critical review of existing aircraft scheduled maintenance program development methodologies, and demonstrates the differences between MSG‐3 and other RCM methodologies.

To permit the system safety and reliability analysts to evaluate the criticality or risk associated with item failure modes.

The factors considered in traditional failure mode and effect analysis (FMEA) for risk assessment are frequency of occurrence (S_f), severity (S) and detectability (S_d) of an item failure mode. Because of the subjective and qualitative nature of the information and to make the analysis more consistent and logical, an approach using fuzzy logic is proposed. In the proposed approach, these parameters are represented as members of a fuzzy set fuzzified by using appropriate membership functions and are evaluated in fuzzy inference engine, which makes use of well‐defined rule base and fuzzy logic operations to determine the criticality/riskiness level of the failure. The fuzzy conclusion is then defuzzified to get risk priority number. The higher the value of RPN, the greater will be the risk and lower the value of RPN, and the lesser will be the risk. The fuzzy linguistic assessment model was developed using toolbox platform of MATLAB 6.5 R.13.

The applicability of the proposed approach is investigated with the help of an illustrative case study from the paper industry. Fuzzy risk assessment is carried out for prioritizing failure causes of the hydraulic system, a primary element of the feeding system. The results provide an alternate ranking to that obtained by the traditional method. It is concluded from the study that the fuzzy logic‐based approach not only resolves the limitations associated with traditional methodology for RPN evaluation but also permits the experts to combine probability of occurrence (S_f), severity (S) and detectability (S_d) of failure modes in a more flexible and realistic manner by using their judgement, experience and expertise.

The paper integrates the use of fuzzy logic and expert database with FMEA and may prove helpful to system safety and reliability analysts while conducting failure mode and effect analysis to prioritize failures for taking corrective or remedial actions.