Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Edebiyat Fakültesi, İstatistik Bölümü, Türkiye
Tezin Onay Tarihi: 2017
Öğrenci: YILMAZ KOÇ
Eş Danışman: BARIŞ SÜRÜCÜ, HÜSEYİN NAFİZ ALEMDAROĞLU
Özet:To design cost effective and reliable products are considered to be important to be competitive in the Aerospace Industry. Reliability is therefore, taken as an integral part of the design process. Reliability, which is a kind of design parameter that affects cost and system safety, shall be taken into account in early phases of design process due to difficulties facing during changes in design at the later phases. Reliability of Tactical UAVs can be evaluated by reliability testing but these tests are very expensive and difficult. Because of the difficulties in reliability testing, in early design phases reliability can be evaluated by using reliability methods. In the scope of this thesis work, simulation study is performed to make reliability prediction for METU Tactical UAV. Two different approaches are used to calculate reliability characteristics for systems of METU Tactical UAV. The approaches applied during simulation study are; firstly, items failure characteristics (i.e. failure rate) are taken as a constant and thus exponential distribution is used as probability distribution model. Second approach was that simulated time to failure data having Weibull distribution characteristic is derived and it is determined to show how predicted reliability changes if it is assumed to be exponentially distributed. Within the context of this simulation study, graphical methods i.e. Quantile-Quantile plotting and probability-probability plotting were conducted to find the best distribution model. Three-parameter Weibull distribution is taken as primary model to assess simulated data and unknown parameters of Weibull distribution for which Goodness - of - Fit Tests have been applied is estimated by using Maximum Likelihood and Least Square Estimation. This simulation study is conducted to emphasis the effect of assumption on distribution model, which represent the simulated data.