Wos İndeksli Açık & Kapalı Erişimli Yayınlar
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Item A novel aggregated multiple criteria decision-making approach to evaluate the physical workload of workers(2021) Ekinci, Elmas Burcu Mamak; Can, Gulin Feryal; AAE-4242-2020Physical workload (PWL) is a measure of the physical resources consumed by a worker while performing a task. Analyzing the PWL of workers can aid experts in identifying workers whose working conditions should be improved. Identifying workers who are exposed to the highest PWL is essential for task continuity and occupational health. In this study, a new approach is proposed to prioritize workers according to their PWL levels. In the proposed approach, multiple criteria decision-making techniques are used because different factors can affect PWL levels. Eight criteria, that is, standard time, frequency of working posture, heart rate, the risk level of posture, noise level, lighting intensity, rest period, and perceived workload level are considered. In the evaluation process, criteria weights are computed using entropy considering measurements of the eight criteria for each worker. Using these weights in multiobjective optimization by simple ratio analysis, multiobjective optimization by ratio analysis, and multiattributive ideal-real comparative analysis methods, workers are ranked according to their PWL levels. The final order of workers is determined by aggregating different rankings obtained from these three methods, using the technique of precise order preference method. This study presents original research that can potentially contribute to the literature by considering different perspectives offered by various methods for PWL evaluation. It focuses on several different criteria by performing real measurements and subsequently ranking workers based on the aggregation of these measurements.Item 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-7863-2018Accreditation 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.Item A new approach for ergonomic risk assessment integrating KEMIRA, best-worst and MCDM methods(2020) Delice, Elif Kilic; Can, Gulin FeryalIn this study, a new three-phase ergonomic risk assessment approach was proposed for manual lifting tasks to determine which worker has the highest ergonomic risk level considering two criteria sets as lifting-related criteria and human-related criteria. In the first phase, Modified Kemeny Median Indicator Ranks Accordance (KEMIRA-M) and a novel two-dimensional best-worst method (BWM) integration were proposed for weighting ergonomic risk criteria in two sets. In this way, weighting procedure of KEMIRA-M was advanced by the proposed two-dimensional BWM in a consistent manner and subjectivity in determining the best and the worst criteria in traditional BMW was prevented by using KEMIRA-M. Thus, the weaknesses of both methods have been developed. In the second phase, the rankings of workers were determined via utilizing multi-objective optimization on the basis of simple ratio analysis, multi-objective optimization by ratio analysis (MOORA) ratio, MOORA reference point and complex proportional assessment to see how worker rankings differ despite using the same advanced weighting approach based on KEMIRA-M and two-dimensional BWM integration. Finally, to aggregate these different ranking results, technique of precise order preference was applied. In this way, different viewpoints of each ranking approach can be reflected on a single worker's priority. The applicability of the proposed ergonomic risk assessment approach was demonstrated with a real application in tube manufacturing.