Speed E Gas Minto – A review of thermally activated building systems (TABS) as an alternative to improve the indoor environment of buildings
Open Access Policy Institutional Open Access Program Special Issues Guidelines Editorial Process Research and Publication Ethics Article Processing Fees Awards References
Speed E Gas Minto
All articles he publishes are immediately available worldwide under an open access license. No special permission is required to reuse all or part of an article published by , including figures and tables. For articles published under the Creative Commons CC BY open access license, any part of the article may be reused without permission, provided the original article is clearly cited.
Pdf) Three Dimensional Two Phase Flow Simulations Of Water Braking Phenomena For High Speed Test Track Sled
The articles represent state-of-the-art research with significant potential for major impact in the field. Articles are submitted by individual invitation or recommendation of scientific editors and are peer-reviewed before publication.
A feature can be either an original scientific article, a significant new scientific study, often involving several techniques or approaches, or a comprehensive review with concise and accurate updates of the latest advances in the field that systematically reviews the most exciting advances in the scientific literature. This type of work provides perspective on future research directions or possible applications.
Editor’s Choice articles are based on recommendations from scientific journal editors from around the world. The editors select a small number of articles recently published in the journal that they believe will be of particular interest to the authors or important to the field. The aim is to provide a brief overview of some of the most exciting developments published in the various research areas of the journal.
Received: 28 July 2022 / Revised: 17 August 2022 / Accepted: 20 August 2022 / Published: 25 August 2022
Utilizing The Natural Composition Of Brown Seaweed For The Preparation Of Hybrid Ink For 3d Printing Of Hydrogels
FMEA has been a widely used tool for decades and is used as an industry standard. However, there are two major flaws in this analysis that are pointed out from the outset. The first is risk prioritization, which is expressed by the risk priority number (RPN). The RPN is the product of three factors of equal weight: severity (S), occurrence (O) and detection (D), which can lead to the same risk priority for different combinations of S, O and D. Other uncertainties are caused by conversion of linguistic terms in quantitative data. The basic data used in FMEA largely depends on the subjective opinions, knowledge and experience of experts. Over the decades, various attempts have been made to overcome these weaknesses not only by academia but also by industry. The Automotive Industry Action Group (AIAG) and the Verband der Automobilindustrie (VDA) have produced FMEA guidance that assigns an action priority (AP) depending on a combination of severity, occurrence and number of detections. This study presents an alternative to risk prioritization in FMEA based on the failure of the tasks performed by the analyzed systems. The main factors S, O and D are redefined in such a way as to minimize the uncertainties. The proposed method is implemented in a flow control valve and can be easily implemented in mechanical engineering applications.
Fluid power systems are not the latest development in engineering, but they are still widely used in industrial power systems. In some cases, they cannot be replaced by other systems because of their unique characteristics that other systems cannot achieve. Widespread use, mainly in high-demand applications where safety is a priority, requires increased reliability. Damage to fluid drive components is complex in nature due to the interaction of the high pressure fluid with solid and chemical contaminants and structural parts. The reasons given and the relative movement of the elements make the probability of failure of the fluid component high. Failure and reliability studies of fluid power systems or their components are performed using a variety of tools and methods. Ref. [1] presents work on the monitoring and modeling of gradual failure of a typical fluid power system. Y. Lee et al. [2] investigated a hydraulic system failure that resulted in a wind turbine fire. Ref. [3, 4, 5] deal with the failure of hydraulic pumps. Failure studies, their analysis and their impact on system performance are also performed for fluid drive components [6, 7, 8]. Watton J. [9] prepared a complete collection of fluid power system failure analyses, while [10] focused on the reliability of mechanical parts, including fluid power system components, and derived a baseline failure rate.
The reliability of fluid power components can be increased by any number of methods, including failure mode and effects analysis (FMEA) [11, 12], fault tree analysis (FTA) [13], root cause analysis (RCA) [14] and their extensions or modifications. FMEA is one of the most widely used tools for system quality improvement; however, risk assessment has been criticized [15] and identified as a weakness of the method. A traditional FMEA uses a Risk Priority Number (RPN), which is the product of Severity (S), Occurrence (O), and Detection (D). Equal weighting of these factors can produce the same results for different combinations and can be very confusing in terms of safety. Although traditional FMEA was formally defined in industry standards in the early 1960s [16], later [17] the industry also noted a weakness in risk assessment. The 2008 FMEA guidance [18] states that RPN should no longer be the recommended practice for determining the need for action. It also says that for failure modes with a severity number of 9 or 10, the risk must be adequately addressed. The latest edition [19] introduced an action priority (AP) rating table, in which AP depends on the combination of S, O, and D, where weight plays a dominant role. Table 1 shows the AP classification table. Failure modes are classified into three AP categories: high risk (H), medium risk (M), and low risk (L) for the design or process FMEA.
It appears to be a step up from the previous version as it removes the subjectivity of risk assessment. However, even for the highest severity values (S 9-10), the risk is defined as medium (M) for detection (D 5-6) and occurrence (O 2-3) or low (L) for detection ( D 1–3) and appearance (O 1-3).
Just Bee Bold Cinnamon Mint
Other disadvantages are the conversion of linguistic expressions into quantitative data and the uncertainty associated with the subjective opinions, experience and knowledge of the experts evaluating the systems.
Various methods and tools are used to overcome the aforementioned weaknesses. Traditional risk assessment can be extended with additional factors [20] or corresponding weights [21]. Another approach is to apply other risk perspectives, such as the user perspective [22] or the maintenance perspective [23].
There are numerous methods used to reduce the uncertainty of the FMEA process. The most common approaches are gray set theory [24], linguistic theory [25], fuzzy sets [26] and reasoning theory [27].
Liu et al. [28], in [28] prepared a complex and methodical literature review on the methods and tools currently used in FMEA in risk assessment and uncertainty removal. Recent studies to overcome the shortcomings of traditional FMEA have focused on applying new methods or combining those mentioned earlier. Ref. [29] presents an FMEA approach where failure modes are classified based on a combination of risk factors in pairs: S and O, S and D and O and D. The results of a pair of risk factors are analyzed using ratio analysis the gray. Yu et al. [30] apply cloud model theory to minimize linguistic uncertainties and use the VIKOR model for risk prioritization. The authors in [31] modified the FMEA framework for IT as recommended by the relevant literature review. Ref. [32] used a cloud model to improve FMEA. Yelda and others. proposed a three-level fuzzy risk assessment based on FMEA. [33]. In op. [34] the authors proposed an approach where the FMEA method was modified by integrating fuzzy rule base (FRB) and gray relation theory (GRT) to overcome the shortcomings of traditional FMEA methods. The uncertainty associated with different expert knowledge is presented in [35], where probability theory is applied. Another approach to converting linguistic terms into quantitative data is found in [36]. Fuzzy numbers and traditional measurement of alternatives and trade-off ranking (MARCOS) methods were used. Meanwhile, Shi et al. [37] proposed the integration of fluctuating linguistic preferences (HLPRs) and an extended dynamic consensus model in FMEA. Another approach to FMEA modification is to consider the influence of the failure mode and the damping effect of such influences in the system [38].
Modeling Population Trajectory And Probability Of Decline In Northern Hudson Bay Narwhals (monodon Monoceros)
Despite the wide selection of implemented methods and tools, risk assessment in FMEA is still problematic. The approaches available in the literature are too complex or too computationally expensive to be used in an industrial standard. The recent practical application of FMEA by AIAG and VDA is helpful in eliminating subjective decisions in risk assessment. However, the introduced risk ranking may lead to incorrectly assessed failure modes from a safety perspective. Uncertainty related to expert subjectivity
