Akademik Veri Yönetim Sistemi
SOFT COMPUTING, cilt.27, sa.11, ss.7071-7096, 2023 (SCI-Expanded)
In recent years, the topic of smart manufacturing systems (SMS) has become the focus of attention for researchers and production experts because it enables intelligent optimization of production processes. Enterprises have started to use SMS and technologies to develop complex products, accurately predict customer needs, minimize production costs, increase flexibility in production, and analyze risks. However, enterprises needs more knowledge about the requirements and features which should be in place for SMS. Customizing SMS is more costly and takes more time than traditional manufacturing. For this reason, the system must be considered in its entirety during the design process and the requirements must be met. The features of the SMS technology to be used must also be determined during the design process. In this study, 6 main and 30 sub-features of the SMS are defined to enable its implementation. The objective is to analyze the impact of these features on the SMS technology. The weighting coefficients of the defined main and sub-features were calculated using the Fuzzy Full Consistency Method (F-FUCOM), one of the multi-criteria analysis (MCA). Later, these coefficients were used in the Fuzzy Measurement Alternatives and Ranking according to COmpromise Solution (F-MARCOS) method to determine SMS technologies. The analysis results provide some important information for companies planning to switch to the intelligent production system. When examining the results related to the main criteria, it was found that the best ranking was Internet of things (IoT), the second best ranking was cyber-physical systems (CPS), and the third best ranking was big data. For the sub-criteria, the best score was CPS, the second best score was IoT, and the third best was big data. Overall, the results show enterprises should prioritize IoT, CPS, and big data.