Monitoring process of measurement and regulation
The measurement and regulation monitoring process, in which the SensoCom module is connected to existing PLC units, HMI units or evaluation units, which on one side receives data from the attached sensors and on the other one wirelessly sends them to the cloud storage, is a typical example of the system implementation.
During the initial analysis of the outputs it will be then determined whether it will be appropriate to measure and know the correlation of the collected data with other parameters, such as pressure in a certain section of production, humidity in a specific place, temperature around the workplace, dustiness, weight, force or others. Here too, will be used one of the SensoCom measuring modules according to the required measured parameter..
The connected SensoCom module will allow data to be stored in a database that will provide future insight into the process with the aim of current interpretation for future improvements and savings. Tools for data processing (correlation between data signals, statistical data analysis, mathematical methods of PCA and ICA) will enable this analysis to be carried out.
A dashboard will be prepared to monitor the status of measured quantities 24 hours a day. This is the initial output of the stored data and provides information on whether data is being stored while simultaneously displaying the measured values, from which certain findings can already be interpreted. At the same time, the alarms are set, which allow you to immediately inform about a situation requiring an immediate response. It can be for example overloading the scale, exceeding the maximum temperature, etc.
Reports on the behavior of the production system will be prepared for the initial analysis of the management and the data engineers. Thanks to these reports, it is possible to determine further steps for improving the process, the requirements for finding additional measurements and setting evaluation criteria for the success of the steps taken for optimization.
Artificial intelligence can be used as an application of basic artificial intelligence or deep learning and can be applied only when there is a large amount of data. This data is used for training, validating and testing the neural network. It is not only for this reason that it is necessary to start the process of measurement and data storage as soon as possible.