Reliability engineering is the discipline of predicting and designing against failure — figuring out not just whether a component works, but how long it will keep working under real stress, age, and mission conditions before something breaks. You'll move between probability distributions (exponential, Weibull, normal), techniques like FMEA, fault tree analysis, and reliability block diagrams, and case studies grounded in aerospace and defense standards (MIL-HDBK-338B, MIL-STD-810), with homework, a project, and two midterms tying the statistics to actual hardware decisions. It's a natural senior-level bridge between your probability background and the design and manufacturing courses, and it's the toolkit anyone going into aerospace, automotive, or any safety-critical industry is expected to speak fluently.
→ STARS müfredatı (resmi syllabus)
Students are advised to consult their instructors regarding the use of Generative AI tools and their appropriateness in each course. Responsible use of GenAI is encouraged in accordance with Bilkent University's GenAI Guidelines. The Generative AI policy guideline of Bilkent University can be found here: https://w3.bilkent.edu.tr/bilkent/generative-artificial-intelligence-genai-guideline/
İlk dosyayı sen atarsan — not, slayt, geçmiş sınav, çözüm, cheat-sheet, ne varsa — defter ekibi öğrenci paylaşımlarından bu dersin notlarını yazar. Drive linki / PDF / ZIP, hepsi olur.
No requirements to Qualify for the Final