Mühendislik Fakültesi / Faculty of Engineering

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

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Subject: search.filters.subject.MULTIOBJECTIVE OPTIMIZATION

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    Optimization Of The Redundancy Allocation Problem: Genetic Algorithm And Monte Carlo Simulation With Discrete Events
    (JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, 2023-09-26) Sahin, Merve Uzuner; Dengiz, Orha; Dengiz, Berna
    The reliability optimization of a system with various problem-specific constraints is an important problem. The Redundancy Allocation Problem (RAP) is the design of new systems with higher reliability using redundant components in parallel arrangement. While improving the system's reliability, the cost is also on the upswing. It has been ensured that system designs with higher reliability at lower costs, where failure and repair are considered, can be obtained (Table A). The reliability of the system with nonrepairable components is lower than the reliability of the system with repairable components. Furthermore, the cost of the system with nonrepairable components is higher than the cost of the system with repairable components.Purpose:The aims of this study are modeling the dynamic behavior of a system considering increasing failure and repair rates, and finding the optimal repairable system design.Theory and Methods:This paper presents a Discrete Event Simulation (DES) model to estimate the system reliability considering increasing failure and repair rates, and a Genetic Algorithm (GA) to find the optimal repairable system design.Results:According to the results, system designs with higher reliability at lower costs, where failure and repair are considered, can be obtained. It has been found that systems with repairable components are more reliable and cheaper than systems with nonrepairable components. Conclusion:It is obtained that the optimal repairable system design with higher reliability at lower cost than the nonrepairable system design.
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    Minimisation of Carbon Emission Regarding Surface Roughness and Processing Time During Turning Process of Medium Carbon Steel and Stainless Steel Materials
    (AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING, 2024) Tansel A A, Yusuf; Saraloglu Guler, Ebru; Sasmaz, Turgut
    Low carbon manufacturing has gathered attention since wide range of the emission sources belong to industrial activities. The present work analysed five turning parameters which are spindle speed, cutting speed, depth of cut, type of tool material and working material to obtain minimum carbon emission together with high surface quality and minimum processing time. Two different cases are investigated depending on the material families. AISI 1040, AISI 4140 and grade St37 carbon steels are examined in the first case whereas AISI 304, AISI 303 and AISI 316 grade stainless steels are studied as working material without changing the other four parameters. The minimum carbon emission by optimisation was found 14.84 and 24.30 kg carbon dioxide (CO2) for stainless steel and carbon steel, respectively. Furthermore, the best candidate was selected as grade St37 among carbon steel working materials and either AISI 303 or AISI 316 stainless steel was proposed according to the optimisation study.