Technologies (Nov 2023)

Developing Robotic Process Automation to Efficiently Integrate Long-Term Business Process Management

  • Nurgul Nalgozhina,
  • Abdul Razaque,
  • Uskenbayeva Raissa,
  • Joon Yoo

DOI
https://doi.org/10.3390/technologies11060164
Journal volume & issue
Vol. 11, no. 6
p. 164

Abstract

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Robotic process automation (RPA) is a popular process automation technology that leverages software to play the function of humans when employing graphical user interfaces. RPA’s scope is limited, and various requirements must be met for it to be applied efficiently. Business process management (BPM), on the other hand, is a well-established area of research that may provide favorable conditions for RPA to thrive. We provide an efficient technique for merging RPA with BPM (RPABPM) to synchronize the technology for efficient automated business processes. The problem formulation process is carried out to cut management-related expenditures. The proposed RPABPM strategy includes the five stages (design, modeling, execution, monitoring, and optimization) for optimal business automation and energy savings. Effective business process management is proved by employing an end-to-end process. Furthermore, findings have been obtained employing three empirical investigations that are performed to assess the practicality and precision of the proposed RPABPM approach. The first objective of the initial study is to confirm the practicality and precision of the approach employed to evaluate the acceptance, possibility, significance, and integration of RPA with BPM. The second study attempts to verify the method’s high-quality characteristics. The third study attempts to assess the approach’s effectiveness in analyzing and identifying BPM that are best suited for RPA. The proposed RPABPM is validated on the industrial robot manufactured by ABB with six-axis IRB140 and supported with a Windows CE-based Flex Pendant (teach pendant). An IRC5 controller is used to run RobotWare 5.13.10371. A pre-installed .NET Compact Framework 3.5 is used. Finally, the proposed method is compared with state-of-the-art methods from an efficiency and power consumption perspective.

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