Automation in the industry 4.0 context and closed loop control
Super quick automation and monitoring is all the rage when we talk about Industry 4.0. As a matter of fact, when we make references to Industry 4.0, we are speaking about the development of a digital physical world that has been developed to automate and survey manufacturing processes and the leveraging of closed-loop control systems.
How exactly does automatization function? And what tech is required to completely go about implementing these solutions? This blog by AICoreSpot explores these issues in brief depth.
Closed loop systems – defined
In basic terminology, a closed-loop control system is a system where human intervention is not required. There is a result that is wanted, and the framework is established to accomplish it. When we visualize a smart thermostat, we have sensors that quantify the temperature levels in the environment. When it obtains the information, let’s assume that the temperature is 75.2F, it goes about alerting the system with regards to this feedback. On the basis of our desirable temperature levels, the system determines whether to increasing the heat levels, retain the same level, or go about cooling down the room.
Therefore, there is a framework that we wish to manage, an output we desire to accomplish, a sensor quantifying the output and delivering feedback, and a control system that determines on the activities required to accomplish the desirable outcome. These processes don’t need manual intervention and thus are automated.
The several use cases for closed-loop systems
A closed loop control system is a critical aspect of automatized work processes. It’s currently being leveraged in agriculture, manufacturing, quality control, processing facilities, food packaging, and building. This framework can be leveraged to manage the processes and alter process variables, or it can act as a supervisory body that ensures quality, consistency in operations, and security.
On top of industrial applications, medical devices have huge advantages to reap from the closed loop system implementation. For instance, such systems can be leveraged to quantify blood sugar levels and manage insulin pumps.
Closed-loop systems driven by machine learning, provide quicker decision-making, improved response times, increased efficiency, an enhanced security. But what is required for these frameworks to become truly functional?
Present problems plaguing closed-loop systems application
Presently, industry 4.0 is still in its nascent stages of development. Cloud-based computing and 4G can be the foundation for development of machine-to-machine interaction, but the deficiencies outweigh the advantages. The entire point of automation is that it’s quicker than work carried out by humans. With information being transmitted to a remote data centre and 4G latency problems, these systems have reduced speed and are not dependable.
Thus far, the most typical way in going about implementing closed-loop systems in industry 3.0 has been integrating the control system and the sensor with their proprietary computational system. The issue with this strategy is that every gadget needs its proprietary compute system, with differing OS and software variants. This approach is not only a hassle to go about maintaining, but it also escalates the cumulative cost of ownership.
The Industry 4.0 Solution
Latency has a dramatic effect on how stable control systems are. To ensure three factors, a holistic strategy, quick decision-making and data transmission, closed-loop control systems are best leveraged when integrated in an edge-cloud network that functions in close proximity to the action. Add in 5G which provides 1ms latency, and all of a sudden, we can have closed-loop smart gadgets that render information and make educated decisions in a matter of seconds.