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Towards Intelligent Robotic Process Automation for BPMers
arXiv - CS - Software Engineering Pub Date : 2020-01-03 , DOI: arxiv-2001.00804 Simone Agostinelli, Andrea Marrella and Massimo Mecella
arXiv - CS - Software Engineering Pub Date : 2020-01-03 , DOI: arxiv-2001.00804 Simone Agostinelli, Andrea Marrella and Massimo Mecella
Robotic Process Automation (RPA) is a fast-emerging automation technology
that sits between the fields of Business Process Management (BPM) and
Artificial Intelligence (AI), and allows organizations to automate high volume
routines. RPA tools are able to capture the execution of such routines
previously performed by a human users on the interface of a computer system,
and then emulate their enactment in place of the user by means of a software
robot. Nowadays, in the BPM domain, only simple, predictable business processes
involving routine work can be automated by RPA tools in situations where there
is no room for interpretation, while more sophisticated work is still left to
human experts. In this paper, starting from an in-depth experimentation of the
RPA tools available on the market, we provide a classification framework to
categorize them on the basis of some key dimensions. Then, based on this
analysis, we derive four research challenges and discuss prospective approaches
necessary to inject intelligence into current RPA technology, in order to
achieve more widespread adoption of RPA in the BPM domain.
中文翻译:
面向 BPM 人员的智能机器人流程自动化
机器人流程自动化 (RPA) 是一种快速新兴的自动化技术,介于业务流程管理 (BPM) 和人工智能 (AI) 领域之间,可让组织实现大量例程的自动化。RPA 工具能够捕获先前由人类用户在计算机系统界面上执行的此类例程的执行,然后通过软件机器人代替用户模拟它们的执行。如今,在 BPM 领域,只有涉及日常工作的简单、可预测的业务流程才能在没有解释空间的情况下由 RPA 工具自动化,而更复杂的工作仍然留给人类专家。在本文中,从对市场上现有 RPA 工具的深入实验开始,我们提供了一个分类框架,根据一些关键维度对它们进行分类。然后,基于这一分析,我们提出了四个研究挑战,并讨论了将智能注入当前 RPA 技术所需的前瞻性方法,以便在 BPM 领域更广泛地采用 RPA。
更新日期:2020-01-06
中文翻译:
面向 BPM 人员的智能机器人流程自动化
机器人流程自动化 (RPA) 是一种快速新兴的自动化技术,介于业务流程管理 (BPM) 和人工智能 (AI) 领域之间,可让组织实现大量例程的自动化。RPA 工具能够捕获先前由人类用户在计算机系统界面上执行的此类例程的执行,然后通过软件机器人代替用户模拟它们的执行。如今,在 BPM 领域,只有涉及日常工作的简单、可预测的业务流程才能在没有解释空间的情况下由 RPA 工具自动化,而更复杂的工作仍然留给人类专家。在本文中,从对市场上现有 RPA 工具的深入实验开始,我们提供了一个分类框架,根据一些关键维度对它们进行分类。然后,基于这一分析,我们提出了四个研究挑战,并讨论了将智能注入当前 RPA 技术所需的前瞻性方法,以便在 BPM 领域更广泛地采用 RPA。