Abstract

Process simulation assesses the impact of changing environmental parameters on a process. To obtain realistic simulation models, process mining techniques can be deployed for a log-based discovery. Such discovery techniques usually rely on a fixed case notion, falling short in capturing the entangled nature of real organizational processes as an interplay of objects and subprocesses. Yet there is a need for such methods, given the requirement for information systems to foresee and adapt to changing environments in an online setting and in a holistic manner. In this work, we approach this research need by elaborating a method for simulation model discovery that is based on the object-centricity paradigm. To implement object-centric simulation, some intrinsic challenges have to be overcome. These include, first, the parametrizable generation of sets of objects having predefined interrelations that structure possible behavior. Second, the generated objects have to be synchronized and routed through a control-flow model. We outline these challenges, describe our solution approach, and evaluate the quality of both object generation and behavior.

Keywords:
Computer science Process (computing) Object (grammar) Quality (philosophy) Process modeling Data science Work in process Human–computer interaction Artificial intelligence Engineering

Metrics

7
Cited By
3.08
FWCI (Field Weighted Citation Impact)
22
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Business Process Modeling and Analysis
Social Sciences →  Business, Management and Accounting →  Management Information Systems
Service-Oriented Architecture and Web Services
Physical Sciences →  Computer Science →  Information Systems
Flexible and Reconfigurable Manufacturing Systems
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
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