Getting Our Hands Dirty With Robotic Process Automation
The effective use of RPA would free humans to focus on other productive work and would eliminate mundane tasks in robot production, at least to some extent.
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Robots are trained using demonstrative steps instead of programming. They are meant for replicating human behavior while interacting with a user interface instead of using APIs, which differentiates them from existing traditional applications. Robots interpret the screen display electronically and as such does not need a physical screen. Robots need to be trained using demonstrative steps instead of programming it.
Productivity measures how much output one unit of input can create in one unit of time. It can be a repetitive job, meaning it can be error-prone, boring, and time-consuming when done by humans.
We evaluated UiPath to get our hands dirty. This article will give a small introduction to the components the platform consists of and our experience evaluating it.
- Studio: A visual process modeling tool. It is used to design business processes. It has built-in components and a nice drag-and-drop facility to create workflows that need to be automated.
- Robot: Robots are programmed to execute the workflows created through Studio. It can work either in fully automated mode or as an assistant. A fully autonomous robot can work unattended. In Assistant Mode, humans trigger workflows. It can run on both virtual and remote environments. It can work with legacy systems, cloud, web-based applications, Citrix, Java applications, and documents.
- Orchestrator: A platform used to manage robots and processes. Using it, the user can deploy, start, stop, and schedule processes and monitor their execution using robots. It facilitates collaboration between humans and robots. It also offers analytical tools and allows creating configurable reports and dashboards.
Due to interest in the stock market, we thought of making robots learn how to fetch real-time data from the market and store it on-disk in an Excel sheet for evaluation later on.
Instead of designing the process, we used its ability to learn the workflow. The Studio was used to learn through demonstrations. We made the robot learn to open a stock market site in a browser, capture data for various stocks, and store it in an Excel sheet on the disk. Bingo, our workflow, was created by demonstrating the steps instead of drawing the workflow manually.
When we executed it, we had a robot created in the Orchestrator and monitor it. The robot did a marvelous job in executing the learned steps. It opened the site automatically, fetched the real-time data for us, and saved it on the disk. A very impressive learner.
The robots were great learners. We found them to execute repetitive tasks without getting bored and without any errors. The effective use of RPA would free humans to focus on other productive work and would eliminate mundane tasks in robot production, at least to some extent.
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