Assessing the Compliance of Business Process Models with Regulatory Documents

Winter, Karolin; Aa, Han van der; Rinderle-Ma, Stefanie; Weidlich, Matthias

doi:10.1007/978-3-030-62522-1_14

Cited by 9 publications

(1 citation statement)

References 13 publications

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“…DigiEDraw [15], for example, provides conceptual and tool support to automatically extract this information from the drawings such that they can be included in the process models, but also in process analysis. Approaches such as [22] provide NLP-based concepts and tools to check the compliance of (manufacturing) processes with regulatory documents.…”

Section: Legacy Systemsmentioning

confidence: 99%

Process Automation and Process Mining in Manufacturing

Rinderle-Ma

Mangler

2021

Lecture Notes in Computer Science

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Process automation and process mining are (interconnected) key technologies with respect to digital transformation. Hence, expectations are high, in particular, in challenging application domains such as manufacturing that combine systems, machines, sensors, and users. Moreover, manufacturing processes operate at a high level of collaboration, e.g. in inter-factory or cross-organizational settings. This paper investigates the following questions: 1) How to automate manufacturing processes? 2) What are the specifics with respect to the involvements of humans? 3) How do the automation strategies impact process mining options and vice versa? For 1), we discuss two starting positions in practice, i.e., legacy automation and greenfield automation. For 2), we discuss the range of automation options with respect to human involvement, i.e., non-interactive automation, robotic process automation, supportive process automation, and interactive process automation. For 3), the different automation settings and strategies are examined with respect to data collection and integration capabilities. Conversely, process mining is discussed as technology to further process automation in manufacturing. The paper builds on more than a decade of experience with process automation in manufacturing. We built an orchestration engine based on which 16 real-world manufacturing processes have been realized so far, resulting in various benefits for the companies such as traceability, flexibility, and sustainability. The investigation of the manufacturing domain also sheds light on other challenging scenarios with similar requirements such as health care and logistics.

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Section: Legacy Systemsmentioning

confidence: 99%