Rule-based Decision Support for No-Code Digitalized Processes

Procedia CIRP, vol. 107, pp. 258–263

Abstract

Digitalized processes offer various advantages: uniform information flow, traceability of process progress, and enhanced analyzability. While these represent initial benefits from the digitalization of the process, a recurring evaluation and optimization of the process are required to sustain and improve process efficiency. For both non-digitalized and digitalized processes, the challenges for process owners are comparable. However, for digitalized processes, convenient tools facilitate process modifications. Particularly no-code digitalized processes exploit the opportunity for quick and agile process adaption with low efforts but require a structured and systematic method to ensure a quality-driven approach. This paper conceptualizes a rule-based decision support model for process improvement that takes advantage of digital traces recorded during process execution of digitalized processes. On the one hand, process mining techniques support data analysis and assist the extraction of process performance indicators as precursors to predict low process performance. On the other hand, process experts compile a list of recommendations for action in workshops and interviews to counteract low process efficiency. The approach to rule-based decision support developed in the scope of this research merges these two dimensions and constitutes an assistive tool for the continuous improvement of digitalized processes. Initial results of the model in practical application support this assessment and demonstrate further research needs.

Authors 3

1. Jimmy Chhor corresponding Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Campus-Boulevard 30, 52074 Aachen, Germany

2. Fabian Kröppel
   Affiliation as printed

   Modell Aachen GmbH, Am Kraftversorgungsturm 5, 52070 Aachen, Germany

3. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology IPT Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University · Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstr. 17, 52074 Aachen, Germany

   Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Campus-Boulevard 30, 52074 Aachen, Germany