Problem Statement
Many business processes involve repetitive and rule-based tasks that can be
time-consuming and prone to errors when performed manually. The project
addresses the need for increased efficiency by implementing Robotic Process
Automation (RPA) to automate such tasks, reducing manual workload and
improving accuracy.
Abstract
This project focuses on the implementation of RPA to automate repetitive tasks
within business processes. By developing software robots that mimic human
actions, the system will automate routine tasks, allowing employees to focus on
more complex and value-added activities. The goal is to improve overall
operational efficiency and reduce the potential for human errors in business
processes.
Outcome
● Implementation of RPA solutions for specific business processes.
● Reduction in manual workload and improved operational efficiency.
● Enhanced accuracy and consistency in task execution.
Reference
Businesses consume a huge amount of time in several routine tasks such as entering data from written documents, confirming identities of employees and setting up meetings. This takes away employees’ time to focus on tasks that add value to their business. Robotic Process Automation (RPA) can help one automate such routine tasks. However, RPA has its limitations and is often applied to rule-based tasks. Any changes in the automated process require direct changes in the RPA application. This is very tedious and requires time to implement using a software development model. Artificial Intelligence (AI) is the ability of a machine to imitate human intelligence and perform tasks like a human would. AI learns from experience and the machine or application makes important decisions without human intervention. It can also implement changes to the application based on experience. Applying AI to RPA applications is often referred to as Intelligent Process Automation (IPA). Optical Character Recognition (OCR) is a routine technology that helps an application to interpret text from images. This research paper explores different ways in which AI and OCR can be incorporated to improve Business Process Automation (BPA).
- Liu Kai, Liu Wenxin, Zhang Ran, Ke Suihua, Yan Dazhu, Zhao Min, Tian Wenhong, “Research on ‘AI+RPA’ Interactive Technology of Intelligent Financial Management Platform,” 2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), pp.1-5, 2022.
- Eija Hartikainen, Virpi Hotti, Markku Tukiainen, “Improving Software Robot Maintenance in Large-Scale Environments–is Center of Excellence a Solution?” IEEE Access, vol.10, pp.96760-96773, 2022.
Citations in Papers – Other Publishers (5):
- Sabyasachi Mukhopadhyay, Amlan Chakrabarti, “A Review on the Impacts of Artificial Intelligence (AI) on Youth,” Handbook of Youth Development, pp.195, 2023.
- Anna Bagaeva, Yuri Danilchenko, Alena Stupina, Anna Glinscaya, Natalya Fedorova, “Application software for business process automation,” E3S Web of Conferences, vol.431, pp.05029, 2023.
- A. Martínez-Rojas, J. M. López-Carnicer, J. González-Enríquez, A. Jiménez-Ramírez, J. M. Sánchez-Oliva, “Intelligent Document Processing in End-to-End RPA Contexts: A Systematic Literature Review,” Confluence of Artificial Intelligence and Robotic Process Automation, vol.335, pp.95, 2023.
- Jayanta Kumar Ray, Rogina Sultana, Rabindranath Bera, Sanjib Sil, Quazi Mohmmad Alfred, “A Comprehensive Review on Artificial Intelligence (AI) and Robotic Process Automation (RPA) for the Development of Smart Cities,” Confluence of Artificial Intelligence and Robotic Process Automation, vol.335, pp.289, 2023.
- Abhishek Gupta, Pranav Soneji, Nikhita Mangaonkar, “Robotic Process Automation Powered Admission Management System,” Inventive Computation and Information Technologies, vol.563, pp.169, 2023.
https://ieeexplore.ieee.org/document/9532902/