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Robotic Process Automation for Efficient Enterprise Business Management

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Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future (SOHOMA 2021)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1034))

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Abstract

Nowadays, enterprise processes are gradually subject to digital transformation, significantly reducing the intervention of the human agent. The automation is going to spread both on technical and business processes of the enterprise. A very important technology for the automation of high volume, repetitive, mainly routine business processes is represented by Robotic Process Automation (RPA) which consists in creating a process that simulates the activity of a human agent and replicating it, by delegating a software robot to do it. The area of RPA usability is very vast like accounting, inventory, finance, human resources, and extends to composite Supply Chain Management (SCM) and Customer Relationship Management (CRM) processes as part of Enterprise Business Management. The paper describes an RPA solution for a company that provides repair and maintenance services for technology resources (busses, trucks) of public and private transport organizations, and that can be easily adopted in other fields of activity that involve SCM and CRM. The necessary steps to set up an RPA robot that simplifies enterprise business logistics activities and brings value to the business are presented. First, RPA functionalities are stated; next, the role of RPA in Enterprise Business Management is described; a particular RPA solution is developed for the enterprise’s taxation and invoicing process. Experimental results obtained by running the automated processes are finally reported.

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Correspondence to Radu Florin Negoiţă .

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Negoiţă, R.F., Borangiu, T., Iacob, I., Nicolae, M. (2022). Robotic Process Automation for Efficient Enterprise Business Management. In: Borangiu, T., Trentesaux, D., Leitão, P., Cardin, O., Joblot, L. (eds) Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future. SOHOMA 2021. Studies in Computational Intelligence, vol 1034. Springer, Cham. https://doi.org/10.1007/978-3-030-99108-1_36

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