How RPA works
To recap from my two previous blogs “Introduction to RPA” and “The relevance of RPA”, we know that Robotic Process Automation (RPA) is a software application robot designed to make lives easier by automating mundane and repetitive tasks autonomously that humans wouldn’t want to work on. We know its also relevant due to its increasing growth as time goes on and the number of applications and implementations it can be used in. Moving forward with the knowledge that we have already gained; in this final blog I will go over how this amazing technology functions.
What is it made up of?
RPA is made up of multiple parts, to go over a few main pieces that make up how it works, we can cover: the software robot, orchestrator, machine learning and artificial intelligence. These pieces are what allow these software robots to automate tasks autonomously, taking the place of human workers to allow for the reallocation of human resources to more important areas of work.
Software robots and orchestrator
RPA uses software application robots, which aren’t the same as physical robots you would see. They can take different forms, one common example you would see when visiting many websites would be a chatbot, they reside entirely on software. These robots are what carry out tasks they are assigned to. RPA robots can work on the user interface level, meaning they see what users would see, for example, when opening a browser, the machine is able to see the same browser you see, allowing you to easily specify what your robot should automate by simply pointing it out. With all these robots being created for different purposes, there is a tool to help you manage all your robots. The orchestrator is that tool to manage your robots, using the example RPA software company UiPath from my previous blog, UiPath has an orchestrator and it includes a dashboard so you can easily see all your robot’s status, whether they’re still running, stopped, pending, terminated and other helpful information such as viewing what automations there are to execute and tasks that are queued up, waiting in order to run. The most common place to create robots and manage them from an orchestrator would be to use an RPA software, such as UiPath.
Machine learning and AI
With RPA, you can also implement machine learning to “teach” the robot how to automate by doing a few sample tasks yourself. This allows the robot to gather data and learn from the process of how you do them. You can also implement AI which is a bit more difficult to implement but over time this process should be easier. AI is similar to machine learning; however, it tries to make decisions based off specific data to imitate human thinking and decision making. These two pieces of technology allow RPA’s ability to learn by itself and potentially make decisions by itself is what enhances it. With the steady growth of all these pieces of technology moving forward to the future, RPA will benefit and allow itself to be developed further allowing more practical uses and ways it can work that would have been previously unimaginable.
Conclusion
Robotic Process Automation allows for the creation of robots to automate specific tasks. With an orchestrator, a common tool found in RPA software, you can manage your robots and see when and what they can do. RPA can involve other pieces of popular and growing technology to benefit itself, and in the coming future with the advancements in all types of technology; machine learning and AI included, RPA stands to benefits and grow alongside these pieces of technology as well.
