Abstract
Nowadays, because of the energy crisis, combined heat and power systems have notable benefits. One of the best devices is SOFC (Solid Oxide Fuel Cell) which joins heat and power frameworks. Some considerable failure modes arise that can affect these devices’ productivity. Generally, failure modes evaluations need an experts team to achieve uncertainties belongs to the risk assessment procedure. To improve the efficiency of the routine FMEA methodology and to represent a suitable hybrid fuzzy MCDM approach for FMEA, in this work, fully fuzzy best-worst method (FF-BWM) is employed to achieve the risk factors weights then fuzzy weighted aggregated sum product assessment (F-WASPAS) approach to detect the failure modes priorities is utilized. Ultimately, the sensitivity analyses demonstrate that the offered framework is verified and can make applicable data in risk management decision-making evaluation.
Highlights
The consistent improvement in industries causes a huge expansion in energy interest.In this way, expanding nature-accommodating devices with high proficiency is imperative to limit the adverse consequences of non-renewable energy sources [1]
Zavadskas et al [22] introduced the weighted aggregated sum product assessment (WASPAS) method to improve the accuracy of alternatives ranking
The main failure modes of a solid oxide fuel cell have been evaluated based on FMEA
Summary
The consistent improvement in industries causes a huge expansion in energy interest. In this way, expanding nature-accommodating devices with high proficiency is imperative to limit the adverse consequences of non-renewable energy sources [1]. Guk et al [5] expressed that for acquiring better knowledge into the SOFC efficiency, the most significant factor to consider is the electrode temperature dispensation In this way, to gauge the cathode and anode temperature dispensation from a functioning SOFC, they introduced a new cell-incorporated multi-intersection thermocouple cluster. An MCDM approach is made of several alternatives and objectives These methodologies can incorporate penalty function, weighted-aggregate, objective programming, and fuzzy methods [11]. Several MCDM methods introduced to evaluate the criteria weight or alternative ranking. Zavadskas et al [22] introduced the WASPAS method to improve the accuracy of alternatives ranking This method is a combination of the weighted sum model (WSM). The present work is an extended investigation of precise and hybrid fuzzy MCDM methods for risk evaluation by utilizing fully fuzzy BWM and fuzzy WASPAS to extract an appropriate risk ranking.
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