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2024 | OriginalPaper | Buchkapitel

Control and Monitoring of Software Robots: What Can Academia and Industry Learn from Each Other?

verfasst von : Kelly Kurowski, Antonio Martínez-Rojas, Hajo A. Reijers

Erschienen in: Research Challenges in Information Science

Verlag: Springer Nature Switzerland

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Abstract

Robotic Process Automation (RPA) has witnessed significant growth, becoming widely adopted in practice. This surge in the use of RPA technology has given rise to new challenges, particularly concerning the effective control and monitoring of software robots. Ideally, academia and industry would work together on developing new RPA capabilities, but both domains operate rather separately. In this paper, we employ an explorative approach to examine how academic theories can improve industrial RPA practices and vice versa. By analyzing both academic literature and leading RPA platforms, we present four recommendations for academia, four for industry, and a general recommendation aiming to advance the collaboration between them.

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Vorheriges Kapitel Forensic-Ready Analysis Suite: A Tool Support for Forensic-Ready Software Systems Design

Nächstes Kapitel Creating a Web-Based Viewer for an ADOxx-Based Modeling Toolkit

Gartner Magic Quadrant RPA: www.uipath.com/es/resources/automation-analyst-reports/gartner-magic-quadrant-robotic-process-automation.

Forrester Wave RPA: https://www.uipath.com/resources/automation-analyst-reports/forrester-wave-rpa.

Full academic analysis described in: https://doi.org/10.5281/zenodo.10818625.

Full industrial analysis described in: https://doi.org/10.5281/zenodo.10818625.

Automation Anywhere Control Room Documentation. https://docs.automationanywhere.com/bundle/enterprise-v11.3/page/enterprise/topics/control-room/getting-started/using-control-room.html

BluePrism Control Room: Hub 4.6 and Control Room 4.6 user guide. https://bpdocs.blueprism.com/hub-interact/4-6/en-us/home-control-room.htm

UiPath Orchestrator Documentation. https://docs.uipath.com/orchestrator/standalone/2023.4/user-guide/introduction

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Titel: Control and Monitoring of Software Robots: What Can Academia and Industry Learn from Each Other?
verfasst von: Kelly Kurowski
Antonio Martínez-Rojas
Hajo A. Reijers
Verlag: Springer Nature Switzerland
Buch: Research Challenges in Information Science
Print ISBN: 978-3-031-59467-0

Electronic ISBN: 978-3-031-59468-7

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-59468-7_7

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