In recent years TSK has witnessed the unceasing growth of the industrial sector, which has resulted in industrial plants and systems that are ever larger and more complex, and that are managed and monitored by means of broad networks of sensors and data receivers.
The volumes of information created by these networks are increasingly large, which requires a management process appropriate for processing this immense quantity of data. As a result, traditional commercial systems are no longer able to manage this information efficiently. This growing quantity of information also constitutes a new opportunity to improve production systems and gain increased understanding of the different processes. Concealed behind these data are relationships, hidden information and indicators that could result in a great benefit for the industrial sector. In order to obtain this valuable hidden information it is necessary to develop effective analysis procedures and artificial intelligence techniques appropriate to the characteristics of the data.
Which of the 4.0 technologies addresses the problem?
The problem is addressed mainly by two technologies:
Industrial Internet of Things (IIoT). The main goal of the Iot technology is to enable interconnection of any object, at all times and from any location. The IIoT technologies have arisen from their application to the industrial sector, and in recent years they have shown great potential. These technologies become a key element of communication that will allow the acquisition of all information generated in an industrial plant and the monitoring of the elements involved in the process.
Big Data. The large volumes of data generated and acquired through the IoT technologies is captured and processed by integrating the technology of Big Data Analytics in “streaming” (real-time processing) and in “batch” (processing in batches).
Both technologies are combined for simultaneous, remote monitoring of the elements of the plant and for taking action on these elements if needed as rapidly as possible. To this end, the application of emerging paradigms such as “fog computing” or “edge analytics” and standards such as the “web of things” is currently the subject of further research.
Result of the project and impact on the company/industry:
The implementation of the SISPLANT project enables TSK to benefit from an efficient monitoring system for its ever-growing number of industrial plants. In this manner, there is no longer a need to acquire licenses for external commercial systems, and the difficulties in use due to their restrictions on carrying out modifications in the programs and developing new flexible software modules is resolved, together with the impossibility of scalability and adoption of standards that these systems entail.
In addition, the results obtained from the analysis procedures will have a very positive effect on the company’s activity, especially regarding the decrease in maintenance costs and improvement in the times of different production phases.