The failure mode and effects analysis (FMEA) is a qualitative, Inductive and effective method for detecting errors, faults, and failures in a system and fuzzy logic can improve that technique with more logical outputs. Moreover, the fault tree analysis (FTA) as a probabilistic risk assessment method is among the effective technique for calculating the probability of errors, faults, failures, reliability and safety integrity level (SIL) verification resulting in certain events at higher levels. The FTA also detects the main causes of events in complicated systems. Although this technique appears to be time-consuming in systems with many diverse components, it is considered a powerful tool. In this paper, the fuzzy FMEA analyzes the failure modes in a hypothetical system. After that, the process with the highest risk is selected as the input of an FTA. According to the qualitative and quantitative analysis of FTAs, a series of corrective actions will be proposed to reduce the failure probability. Manuscript profile

Since companies are inclined to implement lean production‎, ‎researchers have proposed a number of fundamental success factors to facilitate the implementation of this production approach‎. ‎This study analyzes the critical success factors (CSFs) in lean production extracted from 14 review studies‎. ‎The interpretive structural modeling approach is utilized to analyze the impact of these critical success factors on one another‎. ‎The aim is to enhance insights into lean production and facilitate informed decision-making‎. ‎In this article‎, ‎a seven-tiered model is presented‎. ‎According to the conceptual model of success factors in lean production‎, ‎leadership is positioned at the base of the model and serves as the origin for other factors‎. ‎It should be regarded as the foremost critical success factor in lean production‎. ‎When establishing lean production systems‎, ‎organizations and senior managers should focus on higher levels and critical success factors that underlie the model‎. ‎Subsequently‎, ‎nonfuzzy and fuzzy driving and dependence power analyses were conducted that the fuzzy matrix cross-reference multiplication applied to a classification (MICMAC) analysis provides deeper insights into the analysis of driving and dependence power‎. ‎The fuzzy matrix cross-reference multiplication applied to a classification analysis helped identify some key factors that are highly effective for successfully implementing lean manufacturing‎. Manuscript profile

The COVID-19 pandemic has affected many people around the globe. Europe, as one of the most seriously affected continents, has been struggling with the novel coronavirus for several months. Obviously, outbreak response management plays a critical role in the impact of the disease. Therefore, in this paper, Malmquist Productivity Index is used to evaluate the performance of the most severely affected European countries based on the average contagion rate. The results rank the countries and provides insight for the future. Manuscript profile