An Innovative Fuzzy Modeling Technique For Transformer's Failure Modes And Effects Analysis

Singh, Amita; Patil, Atul Jaysing; Sharma, Rajiv Kumar; Jarial, R. K.

doi:10.1109/ice348803.2020.9122822

Cited by 9 publications

(1 citation statement)

References 5 publications

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“…Several extensions of ordinary fuzzy sets such as type-2, intervalvalued fuzzy sets, intuitionistic fuzzy sets, hesitant fuzzy sets, pythagorean fuzzy sets, neutrophic sets and spherical fuzzy numbers have been developed over the years by the researchers. In literature, fuzzy FMEA is also a widely used method due to the easiness to reach the input data of the analyses via the experts [15][16][17]. In this study the high level of uncertainty in the risk assessment performed with expert judgments has been employed with the triangular fuzzy sets due to easiness of the representation and calculation.…”

Section: Risk Analysis Of Tech Startups With Fuzzy Fmeamentioning

confidence: 99%

Risk Analysis for the Tech Startup Projects with Fuzzy Logic

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Temur

2021

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation

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Nowadays; technological (Tech) startups are fast-growing businesses that target to meet the demands of the marketplace by developing innovative products, services, or platforms. Many factors have become prominent regarding the success and sustainability of the product or service offered by the startup: Investment, experience, and education of the team, leadership of the management, creativity, innovation, technological breakthroughs, surrounding community, future perspective, target marketing strategy, location and the analysis of the market, etc. Therefore, startups contend under considerable uncertainty. Considering the high failure rates of the startups, it is inevitable to examine them in terms of risk analysis. Defining the important risk factors is crucial to develop the right strategies for successful startups. In literature, there is a great effort to find out the key factors for successful and sustainable business models including intensive technology. In this study, a risk analysis for the failure of startup projects under the framework of business model canvas has been performed using Fuzzy Failure Mode and Effect Analysis (FMEA) with the field experts. While fuzzy logic provides to define the quantitative parameters of the risk analysis, the FMEA provides to present the main reasons which cause the failure of the startup projects with their priority numbers. The findings have theoretical and practical contributions to success in startup projects by showing the effects of the factors that cause startup projects to fail. The results are discussed to provide managerial strategies for mitigating the failure risks of the startup projects.

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Section: Risk Analysis Of Tech Startups With Fuzzy Fmeamentioning

confidence: 99%