Mühendislik Fakültesi / Faculty of Engineering

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

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Subject: search.filters.subject.Decision support systems

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    Development of a decision support system to determine engineering student achievement levels based on individual program output during the accreditation process
    (2021) Yorulmaz, Muhammet; Ic, Yusuf Tansel; 0000-0001-9274-7467; AGE-3003-2022; C-7863-2018
    Accreditation studies and the number of programs that are accredited in engineering education are increasing day by day. In the auditing process, under the criteria of program outcomes, the level of individual students' achieving program outcomes is also considered as a sub-criterion. Failure to present a systematic approach to measuring the level of achievement of the program outcomes of the students who have reached the graduation stage in the evaluations or the use of questionnaires to measure them is considered insufficient evidence. In this study, a decision support system based on a multi-criteria decision-making model has been developed to determine the achievement levels of individual program outcomes (PO) of students who have reached the graduation stage of any engineering program. The MOORA (Multi- Objective Optimization on the basis of Ratio Analysis) method was used as a multi-criteria decision-making model, and the provision levels of POs were graded. In this way, the required evidence is created automatically by calculating the PO provision levels according to the compulsory and elective courses taken by the students at the graduation stage throughout their education life. We aimed to prevent the observed deficiencies and to set an example for the programs that will work the process. We developed a decision support system that can be used by engineering programs to determine whether their program satisfies accreditation requirements.
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    A knowledge-based material selection system for interactive pressure vessel design
    (2020) Yurdakul, Mustafa; Balci, Arif; Ic, Yusuf Tansel; AAI-1081-2020
    Continual introduction of new materials and improvements in existing materials increase the variety of materials that can be used for pressure vessel components. Among wide variety of materials, the most suitable one must be selected for a component by matching its functional requirements with various available materials' specifications. This study proposes an interactive knowledge-based decision support system for selecting the most suitable material for a given pressure vessel component and its working environment. The developed decision support system, namely Pressure Vessel SELection (PVSEL), consists of two separate phases. In the first elimination phase of PVSEL, the user obtains a feasible set of alternative materials by answering various questions and providing lower-limit values at materials' critical specifications. PVSEL, then, uses a ranking phase which uses ELECTRE, TOPSIS and VIKOR methods to rank the feasible materials. In the second phase, each alternative material's ranking is determined by combining its performance values at weighted critical specifications (selection criteria), which are considered as important in meeting the functional requirements of the component. Usage of PVSEL is illustrated in the paper and the results show that the proposed PVSEL is an effective selection tool and provides meaningful results for the designers.
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    An improved decision support system for ABC inventory classification
    (2020) Eraslan, Ergun; Ic, Yusuf Tansel
    In this study, an Improved Decision Support System (IDSS) is developed to help the decision makers in their inventory classification decisions. For the first time in this paper, the novel IDSS for ABC classification is developed. Certain new algorithms regarding the manufacturing company's features are applied in a framework of IDSS. The IDSS is developed as modular structure and provided the integrated modules of "Data-Base" and "ABC Analysis". In the developed IDSS, the appropriate ABC classification models are considered among Annual Dollar Usage (ADU), Analytic Hierarchy Process (AHP), Scoring (SCR), Fuzzy C-means Algorithm (FCM), and Analytic Network Process (ANP). Some issues and applicability of the IDSS are illustrated with real case problems in the paper. The proposed IDSS software is considerably decreased the time for the inventory classification. In the meantime it could be easily used in various sectors. Therefore, the proposed IDSS significantly contributed to obtaining more accurate and quickly modifiable ABC classification in real cases. Furthermore, the user friendly software can be updated readily according to recent developments in the market.