2018· International Journal of Intelligent Automation & Robotics Engineering· Vol 1, pp. 01-08· 0 citations
TL;DR
The evolution from RPA to Intelligent Process Automation (IPA) is examined, discussing how AI and ML technologies are disrupting and enhancing business processes.
Abstract
The landscape of business process automation is undergoing a significant transformation with the integration of artificial intelligence and machine learning into traditional robotic process automation. This paper examines the evolution from RPA to Intelligent Process Automation (IPA), discussing how AI and ML technologies are disrupting and enhancing business processes. We analyze the current trends, applications, and future prospects of IPA, identifying key research challenges and opportunities at the intersection of AI and business process management. Our findings aim to provide insights for organizations considering the adoption of IPA and to stimulate further research in this emerging field.
Automation of business processes is becoming a success factor for an enterprise. Neural networks and other artificial intelligence technologies are increasingly being used for automation. And the procurement sector has long been a pioneer of digitalization. However, neither digitalization in general nor artificial inte...
As the global manufacturing industry accelerates its digital and intelligent transformation, the deep integration of Artificial Intelligence (AI) with the Internet of Things (IoT) is emerging as a central driver behind the evolution of smart manufacturing systems. This paper provides a comprehensive review of the techn...
Xuan-Yi Chen· Applied and Computational En...· 0 citations
The findings emphasize that edge-enabled intelligent control can be used to greatly increase the responsiveness of a system, decrease the latency, and increase the overall operational efficiency.
K. Vijayakumar· Materials Research Proceedin...· 0 citations
This paper introduces an extended outline of the AI-based decision-making in manufacturing facilities with the application of real-time sensor data, machine learning, and adaptive control and puts emphasis on the possibilities of AI-powered systems to reach Industry 4.0 goals.
Davinder Singh· Materials Research Proceedin...· 0 citations
It is argued that first-principles models (FPMs) remain essential for mission- and business-critical workflows in industrial automation, both in process design and operations and hybrid intelligence integrates mechanistic rigor with data-driven insights to deliver smarter design, safer operations, and more sustainable...
Hong Zhao, Shu Wang, Salvador I. Pérez-Uresti et al.· Industrial & Engineering...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.