Reliability Engineering

Kiran, D.R.

doi:10.1016/b978-0-12-811035-5.00027-1

Cited by 8 publications

(7 citation statements)

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“…Here two dimensions are considered: time and stress (e.g., temperature, humidity). 64 The challenge of stability for flexible sensors often stems from the use of organic and polymeric materials in their fabrication, which tend to degrade over time and whose properties are easily altered by environmental factors. Furthermore, wearable biosensors incorporating biological receptors face additional bio-instability.…”

Section: Sensing Performancementioning

confidence: 99%

Technology Roadmap for Flexible Sensors

et al. 2023

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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

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Section: Sensing Performancementioning

confidence: 99%

Technology Roadmap for Flexible Sensors

et al. 2023

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“…They can be statistically represented by a probability density and cumulative function. A probability density function may be described as a probability distribution which corresponds to the relative possibility for a random variable to take on a given value (51) . The Weibull distribution, which was created by the Swedish physicist Waloddi Weibull in the 1930s, provides information regarding the wind speed distribution resulting from these changes.…”

Section: Preliminaries On Mathematical Backgroundmentioning

confidence: 99%

Metaheuristic data fitting methods to estimate Weibull parameters for wind speed data: a case study of Hasan Polatkan Airport

Kaba

Suzer

2021

Aeronaut. j.

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Flight delays may be decreased in a predictable way if the Weibull wind speed parameters of a runway, which are an important aspect of safety during the take-off and landing phases of aircraft, can be determined. One aim of this work is to determine the wind profile of Hasan Polatkan Airport (HPA) as a case study. Numerical methods for Weibull parameter determination perform better when the average wind speed estimation is the main objective. In this paper, a novel objective function that minimises the root-mean-square error by employing the cumulative distribution function is proposed based on the genetic algorithm and particle swarm optimisation. The results are compared with well-known numerical methods, such as maximum-likelihood estimation, the empirical method, the graphical method and the equivalent energy method, as well as the available objective function. Various statistical tests in the literature are applied, such as R2, Root-Mean-Square Error (RMSE) and $\chi$ 2. In addition, the Mean Absolute Error (MAE) and total elapsed time calculated using the algorithms are compared. According to the results of the statistical tests, the proposed methods outperform others, achieving scores as high as 0.9789 and 0.9996 for the R2 test, as low as 0.0058 and 0.0057 for the RMSE test, 0.0036 and 0.0045 for the MAE test and 3.53 × 10−5 and 3.50 × 10−5 for the $\chi$ 2 test. In addition, the determination of the wind speed characteristics at HPA show that low wind speed characteristics and regimes throughout the year offer safer take-off and landing schedules for target aircraft. The principle aim of this paper is to help establish the correct orientation of new runways at HPA and maximise the capacity of the airport by minimising flight delays, which represent a significant impediment to air traffic flow.

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“…The system reliability engineering and reliability assessment are practical ways to manage risk and support decision-making for safe, reliable, and efficient operation of complex engineering systems [31]. According to [32], reliability engineering is an engineering discipline for applying scientific knowhow to a component, product, plant, or process in order to ensure that it performs its intended function, without failure, for the required time duration in a specified environment. Reliability engineering involves an iterative process of reliability assessment and improvement, and the relationship between the two processes [33].…”

Section: B Reliability Engineering For Uasmentioning

confidence: 99%