Mühendislik Fakültesi / Faculty of Engineering

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

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    A Dss Development Study For Document Distribution Networks For Preparing Autonomous Vehicle-Integrated Distribution Systems
    (DECISION, 2024-12) Derya, Tusan; Ic, Yusuf Tansel; Erbay, Mehmet Dogan; Konuk, Kubra; Fidan, Nihal
    We propose a decision support system (DSS) to complete the tours of the routes of the traveler in charge of document distribution in the least amount of time for the document distribution task of a university to prepare autonomous vehicle-integrated distribution systems. A mathematical model-based decision support system is developed to determine distribution routes that optimize the total distance to target locations and obtain optimal system conditions for use in the migration of autonomous distribution systems. The purpose is to find the shortest-cost tours to cover all or subsets of edges in a network. Documents are shared and distributed by travelers to other related locations. Soon after, travelers will be replaced by autonomous vehicles. There are many application areas, such as newspapers and mail delivery systems. Therefore, the proposed model can be easily extended to other application areas, such as newspaper, cargo, and mail delivery systems, to construct autonomous vehicle-based systems.
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    The New Fuzzy Bottleneck Model to Improve The Axle Manufacturing System Performance
    (INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2024) Sari, Haci; Ic, Yusuf Tansel
    Axles are the crucial undercarriage part of vehicles and affect the total number of manufactured vehicles. Therefore, they are essential parts since they directly affect the production quantity. Some uncertainties arise in the lead times of the machining process in the manufacturing system due to the variability in factors, such as human, machine, and material properties. In this study, the efficiency of the axle manufacturing process is investigated, and performance in the machining unit of an automotive spare part manufacturer company is improved. This study aims to increase the production capacity of the company by using a fuzzy logic-based bottleneck analysis. In this study, a new model is proposed by integrating fuzzy logic the Solberg's bottleneck model, and the performance of the manufacturing system is improved by applying the developed model in the machining unit of the company. At the end of the study, the increase in production rate and the benefit to the company is obtained.