SaaMES: SaaS-Based MSA/MTA Model for Real-Time Control of IoT Edge Devices in Digital Manufacturing

• Published in: Sustainability 2022-08, Vol.14 (16), p.9864
• Main Authors: Do, Sanghoon, Kim, Woohang, Cho, Huiseong, Jeong, Jongpil
• Format: Article
• Language: English
• Subjects: Access control; Architectural design; Artificial intelligence; Automation; Big Data; Cloud computing; Computer architecture; Customers; Cyber-physical systems; Data processing; Decision making; Distributed processing; Electronics; Factories; Internet of Things; Licensing (technology); Manufacturing; Manufacturing execution systems; Manufacturing processes; Operating costs; Productivity; Real time; Social networks; Software; Software as a service; Software services; Subscriptions; Systems design; Technology application; Time response; Workplaces
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su14169864

As a software delivery model, Software as a Service (SaaS) has attracted considerable attention from software providers and users. Most traditional companies are shifting their businesses to an SaaS model. SaaS development is a very complicated process and its success depends on architectural design and development. A Manufacturing Execution System (MES) was used at the expense of licensing fees for features not used in the On-Premise environment, although the features used vary depending on the manufacturing environment. In an SaaS environment, MES is applied with a function-specific container approach through a Microservice Architecture (MSA) to select and employ only the necessary functions. Furthermore, as the number of customers of virtualized applications increases in SaaS-based services, complexity and operating costs increase; thus, Multi-tenancy Architecture (MTA) technology, which serves all customers through a single instance of the application is crucial. Thus, in this study, we investigate the MTA approach and propose a suitable MTA for the manufacturing execution system. Real-time response is crucial to achieving a cyber-physical system of digital manufacturing in SaaS-based MES. Furthermore, SaaS-based big data analytics and decision-making cannot meet the needs of numerous applications in real-time sensitive workplaces. In this study, we propose an SaaS-based MSA/MTA model for real-time control of Internet of Things (IoT) Edge in digital manufacturing (SaaMES), an architecture of SaaS-based MES with MSA and MTA to meet vulnerable workplaces and real-time responses in Cloud environments. The analysis is used by applying the Autoencoder and Generic Adversarial Networks analysis model to IoT Edge for the connection between the Cloud environment and work site to enable real-time response and decision-making through communication using OPC-UA and small-scale analysis.