Aquisição, Transferência e Armazenamento de Dados para Indústria 4.0

Abstract

Industry 4.0, also known as the Fourth Industrial Revolution, is based on the Internet of Things and Cyber-Physical Systems paradigms. These integrated paradigms are responsible for carrying out the control and automation process of the industry. For this, all must be adopted. The collection of data from the devices of the industry must be done. The collected data needs to be prepared and sent securely and reliably for storage and analysis in an external environment, in order to enable decision-making based on this data by industry managers. This fact occurs due to the growing amount of data generated by these devices, where the expense with hardware to perform its processing becomes something unfeasible. As a solution, another paradigm is adopted: Cloud Computing. The cloud is based on the provision of computing services of storage, software, analysis and other services through the internet. This work presents the survey and comparison of collection, formatting, transfer and data storage. In the meantime, a study on safety is also carried out for data transfer. With these technologies mapped, it was possible to implement the solution of a scenario to exemplify a subset of them and thus carry out a deployment industry 4.0 efficient. For the development and testing of this solution, a local instance of MongoDB was used to store data from a cement mill, where each dataset is identified by its timestamp and has 152 tags that represented this information. After that, a software was used to simulate the generation of values associated with mill data. The data were acquired by a Python collector service, using the Open Platform Communications (OPC) protocol and therefore, transferred through the Apache Kafka communication system to the Amazon Web Services (AWS) cloud, where they were pre-processed. and analyzed by two Python applications and their results written to a MongoDB instance in the cloud. The scenario raised consists of using data from a mill to manufacture cement, where each set of data is identified through its timestamp and has 152 tags that represent these information. Finally, according to the studies surveyed and the results obtained, it was possible to notice the efficiency of the technologies selected for the implementation of the scenario, in order to serve as a source of contribution for industry engineers and managers.