Intelligent Process Automation: An Application in Manufacturing Industry

Federico A. Lievano-Martínez, Javier D. Fernández-Ledesma, Daniel Burgos, John W. Branch-Bedoya and Jovani A. Jimenez-Builes
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Federico A. Lievano-Martínez: Departamento de Ingeniería, Universidad Pontificia Bolivariana, Medellín 050030, Antioquia, Colombia
Javier D. Fernández-Ledesma: Departamento de Ingeniería, Universidad Pontificia Bolivariana, Medellín 050030, Antioquia, Colombia
Daniel Burgos: Instituto de Investigación, Innovación y Tecnología Educativas (UNIR iTED), Universidad Internacional de La Rioja, 26006 Logroño, La Rioja, Spain
John W. Branch-Bedoya: Departamento de Ciencias de la Computación y de la Decisión, Facultad de Minas, Universidad Nacional de Colombia, Medellín 050035, Antioquia, Colombia
Jovani A. Jimenez-Builes: Departamento de Ciencias de la Computación y de la Decisión, Facultad de Minas, Universidad Nacional de Colombia, Medellín 050035, Antioquia, Colombia

Sustainability, 2022, vol. 14, issue 14, 1-15

Abstract: Background: The intelligent processes automation has been cataloged as one of the most potential and strategic technology solutions to develop a corporate digital transformation. Method: This paper introduces essential concepts to create Intelligent Process Automation (IPA) in industries and proposes a framework to implement IPA technologies successfully. The approach involves: firstly, assembling a good implementation setup and deeply researching the process using process mining techniques. Secondly, choosing and locating the best AI technology inside the IPA. Finally, defining an appropriate architecture of the IPA. Results: The paper illustrates an IPA use case in the manufacturing industry, where it is possible to automate the process of sending production orders to a manufacturing plant and optimize waste and plant capacity significantly. Conclusions: The research depicts the potential of intelligent process automation and its quantifiable benefits in the manufacturing process, and the contribution can be applied to different enterprises with a global context.

Keywords: cognitive automation; intelligent process automation; robotic process automation; artificial intelligence (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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