Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.yasar.edu.tr/handle/123456789/11290

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Browsing Scopus İndeksli Yayınlar Koleksiyonu by Author "A. Tarkan Tekcan"

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    Article
    INCORPORATING PRODUCT ROBUSTNESS LEVEL IN FIELD RETURN RATE PREDICTIONS
    (POLISH MAINTENANCE SOC, 2012) A. Tarkan Tekcan; Gurmen Kahramanoglu; Mustafa Gunduzalp; Gündüzalp, Mustafa; Tekcan, A. Tarkan; Kahramanoǧlu, Gürmen
    Reliability and return rate prediction of products are traditionally achieved by using stress based standards and/or applying accelerated life tests. But frequently predicted reliability and return rate values by using these methods differ from the field values. The primary reason for this is that products do not only fail due to the stress factors mentioned in the standards and/or used in accelerated life tests. There are additional failure factors such as ESD thermal shocks voltage dips interruptions and variations quality factors etc. These factors should also be considered in some way when predictions are made during the R&D phase. Therefore a method should be used which considers such factors thus increasing the accuracy of the reliability and return rate prediction. In this paper we developed a parameter which we call Robustness Level Factor to incorporate such factors and then we combined this parameter with traditional reliability prediction methods. Specifically the approach takes into account qualitative reliability tests performed during the R&D stage and combines them with life tests by using Artificial Neural Networks (ANN). As a result the approach gives more accurate predictions compared with traditional prediction methods. With this prediction model we believe that analysts can determine the reliability and return rate of their products more accurately.
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    Article
    Incorporating product robustness level in field return rate predictions, Przewidywanie rzeczywistego wskaźnika zwrotów towaru z uwzględnieniem poziomu odporności produktu
    (Polish Academy of Sciences Branch Lublin, 2012) A. Tarkan Tekcan; Gürmen Kahramanoǧlu; Mustafa Gündüzalp
    Reliability and return rate prediction of products are traditionally achieved by using stress based standards and/or applying accelerated life tests. But frequently predicted reliability and return rate values by using these methods differ from the field values. The primary reason for this is that products do not only fail due to the stress factors mentioned in the standards and/or used in accelerated life tests. There are additional failure factors such as ESD thermal shocks voltage dips interruptions and variations quality factors etc. These factors should also be considered in some way when predictions are made during the R&D phase. Therefore a method should be used which considers such factors thus increasing the accuracy of the reliability and return rate prediction. In this paper we developed a parameter which we call Robustness Level Factor to incorporate such factors and then we combined this parameter with traditional reliability prediction methods. Specifically the approach takes into account qualitative reliability tests performed during the R&D stage and combines them with life tests by using Artificial Neural Networks (ANN). As a result the approach gives more accurate predictions compared with traditional prediction methods. With this prediction model we believe that analysts can determine the reliability and return rate of their products more accurately. © 2021 Elsevier B.V. All rights reserved.
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    Article
    Power board design optimization based on reliability focused test and analysis procedures
    (2013) Gürmen Kahramanoǧlu; A. Tarkan Tekcan; Mustafa Nevzat Yatir; Barbaros Kirişken; Mustafa Gündüzalp; Gündüzalp, Mustafa; Kirişken, Barbaros; Yatir, Mustafa Nevzat; Kahramanoǧlu, Gürmen; Tekcan, A. Tarkan
    After a deep investigation on the field returns of consumer electronics products especially LCD/LED TV sets, it is observed that power boards are the most critical subsystems of the products. Therefore manufacturers should optimize their power board design by applying reliability focused test and analysis methods to achieve highly reliable products. Reliability improvement increases sales reduces rework and service cost and obtains good brand reputation. In this paper reliability focused test and analysis procedures for power boards of consumer electronics products are given. The outcome of these test and analysis procedures can be used to increase the reliability of the power boards as well as the products. © 2013 American Scientific Publishers All rights reserved. © 2013 Elsevier B.V. All rights reserved.