Mühendislik Fakültesi / Faculty of Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11727/1401

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search.filters.applied.f.rights: search.filters.rights.info:eu-repo/semantics/openAccessSubject: search.filters.subject.Design of experiment

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    A new DoE-MTOPSIS based prediction model suggestion to capture potential SARS-CoV-2 reactivated patients
    (2021) Tansel, Yusuf I. C.; 0000-0001-9274-7467; AGE-3003-2022
    Difficulties to use convenient data during the Severe Acute Respiratory Syndrome Coronavirus2 (SARS-CoV-2) pandemic outbreak and complexities of the problem attitude crucial challenges in infectious disease modelling studies. Motivated by the on-going reach to predict a potential reactivated SARS-CoV-2 (COVID-19), we suggest a prediction model that beyond the clinical characteristics based evaluation approaches. In particular, we developed a possibly available and more efficient prediction model to predict a potential reactivated SARS-CoV-2 (COVID-19) patient. Our paper aims to explore the applicability of a modified Technique for Order Preference by Similarity to Ideal Solutions (MTOPSIS) integrated Design of Experiment (DoE) method to predict a potential reactivated COVID-19 patient in real-time clinical or laboratory applications. The presented novel model may be of interest to the readers studying similar research areas. We illustrate MTOPSIS integrated DoE method by applying it to the COVID-19 pandemic real clinical cases from Wuhan/China-based data. Despite the small sample size, our study provides an encouraging preliminary model framework. Finally, a step by step algorithm is suggested in the study for future research perspectives.
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    Optimization of the Factors That are Critical in External Surface Grinding of Roller Followers Using Design of Experiments
    (2018) Ic, Yusuf Tansel; Gunay, Ezgi; Yurdakul, Mustafa; Mizrak, Haci Veli; Gunes, Serkan; AAI-1081-2020
    In this study, it is aimed to experimentally optimize the parameters of the grinding of external surface of the roller followers which are used in internal combustion engines to operate the inlet and exhaust valves. 2k factorial experimental design methodology is applied to optimize the grinding process such that after this last finishing operation the rollers' external surface quality and cycle time meets the customers' special and strict requirements. In the application of the experimental design methodology, the critical parameters that are important in the optimization of two different surface roughness values along with cycle time are first determined. Then, the values of critical parameters are calculated with the application of the multi-objective optimization of the two surface roughness measures and cycle time. As a result of the optimization, the surface roughness values that are important in the working of the roller followers and cycle time are improved.