Digitization and IOT of industrial processes. Predictive models.
Nowadays, the digitalization of industrial processes has become a necessity since it provides us with tools to have a greater control in real time and in a more exhaustive way of the same processes.
In the traditional industry, the period for capturing process values and indicators is quite long, so that decision making based on these collected values may take longer than desired or necessary.
The cheapening and diversification of IOT data collection devices allows this period to become a period of real-time data collection and recording, which allows decision making to be carried out with greater effectiveness and agility.
Digitization of process data
Standard local network protocols.
IoT Networks
Multi M2M services. API’s.
Advanced wireless communication systems :
- Arduino
- Nodemcu
- LoraWAN
Machine Learning, Deep Learning and Reinforcement Learning
In addition, the development and application of artificial intelligence in recent years and more specifically of tools such as Machine Learning, Deep Learning and Reinforcement Learning gives us the opportunity to build predictive models based on the data recorded from the same production process, which allows us to :
Selection of the appropriate process set-points (SET-POINTS) according to the requirements to be met in each part of the process.
Knowledge of deviations in real time.
More effective analysis of the reasons for such deviations.
Reduction of time in the resolution of incidents.
Savings in manufacturing costs.
Digital cufflinks
Digital twins for prediction of influential factors in the process that cannot be detected in the initial design phases but that can be crucial in the implementation phase as well as in later phases of the project, reducing the detection times of the same factors, which results in :
Decreased uncertainty in the face of unknown problems.
More effective decision making in the choice of possible solutions.
Possibility of providing solutions to problems that have not yet occurred but that in the future will condition the viability of the projects.
Savings in costs associated with the project.
