Univrsity Of Tehran Press Journal of Information Technology Management 2980-7972 15 Special Issue: Digital Twin Enabled Neural Networks Architecture Management for Sustainable Computing 2023 03 01 Integrated Model-Based Engineering using Deep Learning with IIoT for Industry 4.0 112 123 91571 10.22059/jitm.2023.91571 EN P. Senthilkumar Department of Instrumentation and Control Engineering, Kalasalingam Academy of Research and Education, Tamilnadu, India. K. Rajesh Department of Electrical and Electronics Engineering, Kalasalingam Academy of Research and Education, Tamilnadu, India Journal Article 2023 03 15 The Industrial Internet of Things (IIoT) is a potential platform for developing industry 4.0 and its related applications, especially in cyber-physical systems. Such a new trend in manufacturing sectors offers further potential to optimize operations, realize business models, and reduce costs. Such accomplish may also lead to complex and complicated tasks; hence, to deal with such issues, Reference Architecture Model Industry 4.0 (RAMI 4.0) is developed to structure Industry 4.0. In this paper, the standardized framework is considered RAMI 4.0 and its integration with an IIoT software named Software Platform Embedded Systems (SPES). Integrating Model-Based Engineering (MBE) with a framework requires using a deep learning model called Recurrent Neural Network (RNN). The RNN-MBE, which optimizes the entire process, is responsible for optimizing the process and reducing industry costs. The optimization problem has been fixed, and the MBE simulation has shown that using the proposed MBE is efficient. https://jitm.ut.ac.ir/article_91571_29571562b0323cf544d3e19aec793585.pdf