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Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Defense Sciences / Savunma Bilmleri Dergisi is the property of Turkish Military Academy Defense Sciences Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In a production environment, scheduling decides job and machine allocations and the operation sequence. In a job shop production system, the wide variety of jobs, complex routes, and real-life events becomes challenging for scheduling activities. New, unexpected events disrupt the production schedule and require dynamic scheduling updates to the production schedule on an event-based basis. To solve the dynamic scheduling problem, we propose a multi-agent system with reinforcement learning aimed at the minimization of tardiness and flow time to improve the dynamic scheduling techniques. The performance of the proposed multi-agent system is compared with the first-in–first-out, shortest processing time, and earliest due date dispatching rules in terms of the minimization of tardy jobs, mean tardiness, maximum tardiness, mean earliness, maximum earliness, mean flow time, maximum flow time, work in process, and makespan. Five scenarios are generated with different arrival intervals of the jobs to the job shop production system. The results of the experiments, performed for the 3 × 3, 5 × 5, and 10 × 10 problem sizes, show that our multi-agent system overperforms compared to the dispatching rules as the workload of the job shop increases. Under a heavy workload, the proposed multi-agent system gives the best results for five performance criteria, which are the proportion of tardy jobs, mean tardiness, maximum tardiness, mean flow time, and maximum flow time. [ABSTRACT FROM AUTHOR]

In today's understanding, the universities are considered as service providers besides their institutional functions. Because the universities shape the future of the country via the services they provide, it is a necessity that their service quality must be assessed by using scientific analyses, and their service quality must be improved based on such scientific findings. The Generation Z, whose members are currently receiving university education carries unique features that distinguish them from the previous generations. When this fact is considered, it is understood that the constant research and monitoring of the learning environment of the Generation Z is important. In this study, as a result of a detailed literature search, a scale consisting of 7 dimensions and 36 indicators was developed in order to measure the higher education service quality of the Z generation. The validity and reliability tests of this scale are completed via the convergent and divergent validity analyses, Exploratory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA). Because the answers provided to the surveys reflect the personal evaluation of the participants, the Fuzzy Logic is employed, and the study is conducted by using the fuzzy modelling and fuzzy ranking. As a result of this study, the General Satisfaction Index is created, and improving recommendations are carried out based on the scores. [ABSTRACT FROM AUTHOR]

With the rapid progress of network technologies and sensors, monitoring the sensor data such as pressure, temperature, current, vibration and other electrical, mechanical and chemical variables has become much more significant. With the arrival of Big Data and artificial intelligence (AI), sophisticated solutions can be developed to prevent failures and predict the equipment's remaining useful life (RUL). These techniques allow for taking maintenance actions with haste and precision. Accordingly, this study provides a systematic literature review (SLR) of the predictive maintenance (PdM) techniques in transportation systems. The main focus of this study is the literature covering PdM in the motor vehicles' industry in the last 5 years. A total of 52 studies were included in the SLR and examined in detail within the scope of our research questions. We provided a summary on statistical, stochastic and AI approaches for PdM applications and their goals, methods, findings, challenges and opportunities. In addition, this study encourages future research by indicating the areas that have not yet been studied in the PdM literature. [ABSTRACT FROM AUTHOR]

In this research, the target is to create a "Service Performance Index" for food order mobile applications. In order to create the index, a structural equation model is developed. Then the coefficients which are obtained from the model are used to calculate the index values. There are some revenue management practices carried out in the food sector such as "discounts when you order a meal for two" or "privileges for contracted credit card or mobile line users". In this context, this study tried to measure whether there is a relationship between the revenue management and customer perceptions, which are e-service quality, satisfaction and word of mouth. It was realized that revenue management has a significant, positive and high-level effect on e-service quality, satisfaction and word of mouth. The index scores of participants of the questionnaire were compared according to the frequency of benefiting from revenue management applications and discount campaigns. Thus, it was revealed that the service performance index of those who always use revenue management applications is higher than those who never use them. This result contributes to businesses with an important reference in terms of food marketing strategy. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)