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Virtual Industrial Process Optimization Models with Cloud Management

Abstract:

The increasing development in ICT has driven and accelerated the advent of IoT technologies, creating the opportunity to empower and innovate data management and production management within factories with data collection, integration, storage and processing as a key challenge. By using the technologies offered by the fourth industrial revolution, it has been possible to test models through simulation before implementing them in real physical systems and with greater complexity. Specifically, by using a combination of cloud computing, IoT platforms, programming software and calculation software, three industrial processes have been virtualized with protocols based on the TCP/IP standard. By considering relevant parameters and variables, an optimization model is developed to improve the operation sequences reducing costs within the factory and a second model to minimize the total cost of operation subject to power balance and production limits. An indispensable element to consider a 4.0 architecture is the database. Mongodb Atlas NoSQL has been able to provide the research with both effective data ingestion and retrieval, which are challenging tasks in case of opting for a SQL database. This paper focuses on the concept of optimization models and their data management from the cloud. The results show that Mongodb is a highly reliable database with enormous scalability and reliability to store data coming from mathematical models or sensors of virtualized production processes, with or without a predefined structure. Moreover, with IoT platforms, it is possible to visualize the retrieved data and interpret them in a graphical way to improve a decision making within the processes.