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    A decision support system for dynamic job-shop scheduling using real-time data with simulation
    (MDPI AG, 2019) Turker A.K.; Aktepe A.; Inal A.F.; Ersoz O.O.; Das G.S.; Birgoren B.
    The wide usage of information technologies in production has led to the Fourth Industrial Revolution, which has enabled real data collection from production tools that are capable of communicating with each other through the Internet of Things (IoT). Real time data improves production control especially in dynamic production environments. This study proposes a decision support system (DSS) designed to increase the performance of dispatching rules in dynamic scheduling using real time data, hence an increase in the overall performance of the job-shop. The DSS can work with all dispatching rules. To analyze its effects, it is run with popular dispatching rules selected from the literature on a simulation model created in Arena®. When the number of jobs waiting in the queue of any workstation in the job-shop falls to a critical value, the DSS can change the order of schedules in its preceding workstations to feed the workstation as soon as possible. For this purpose, it first determines the jobs in the preceding workstations to be sent to the current workstation, then finds the job with the highest priority number according to the active dispatching rule, and lastly puts this job in the first position in its queue. The DSS is tested under low, normal, and high demand rate scenarios with respect to six performance criteria. It is observed that the DSS improves the system performance by increasing workstation utilization and decreasing both the number of tardy jobs and the amount of waiting time regardless of the employed dispatching rule. © 2019 by the authors.
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    Öğe
    An expert system approach for high school type selection
    (2011) Ersöz S.; Aktepe A.
    An expert system is a computer program that imitates the procedures by which experts solve problems. This paper describes an expert system application which provides advice to primary school students who are seeking assistance in determining high school type. The system gathers information about student grade point average (GPA), centralized exam score, personality type and socio-economic factors. It assesses student qualifications for seven different school types in Turkey. The expert system recommends a school type for the students and produces a short report explaining the reasons of recommendation. Student GPA and centralized exam score are considered as technical criteria. In addition, social and socio-economic factors such as personality type, parental involvement etc. affecting the decision process are also considered and included in the model.
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    Öğe
    A non-linear programming model with fuzzy evaluations for customer satisfaction index estimation
    (Computers and Industrial Engineering, 2014) Aktepe A.; Ersoz S.; Toklu B.
    Customer satisfaction index (CSI) is a cause-and-effect model of advanced customer satisfaction analysis. CSI models are used by several private and public institutions for developing key customer strategies throughout the world. Index values are based on predictions of customer evaluations. In the literature CSI is mostly modeled with linear statistical estimation methods. In a few of the studies, non-linear approach is used for estimation. Estimation of CSI with minimum error results in a more reliable and robust prediction. Therefore, in this study we propose a non-linear programming model for estimating CSI with fuzzy customer evaluations minimizing estimation errors. The estimation model brings significant contributions in this field of study. With the help of the model, we can find weights of measurement variables of a latent variable with minimized squared errors which is a key success factor in producing reliable indexes. In addition the model enables us to find coefficients of prediction equations that contribute to extend evaluation of index results. The model is also tested with data of a comprehensive survey application and application results are included.