Towards a digital twin for cyber-physical production systems: A multi-paradigm modeling approach in the postal industry

10Citations
Citations of this article
39Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper presents our early-stage research on a Multi-Paradigm Modeling (MPM) approach as an initial step towards the definition of a Digital Twin (DT) for Cyber-Physical Production Systems (CPPSs). This work takes place in the context of the digitalization of the mail sorting process at La Poste, the French national postal service company. Indeed, La Poste is currently investing on robotics modules for automatically loading mail containers. The main objective is to reduce the painful work for human operators while optimizing the robots usage. We already worked on targeting such a balance in a past effort that resulted in the production of different kinds of models of the La Poste CPPS. However, these models were defined separately and are not directly related to the underlying business process in particular. Thus, we propose an MPM approach starting from this business process as now modeled explicitly in a BPMN model. Then, we refine the high-level business activities into finer-grained activities represented in a UML Activity model. From these latest, we derive the specification of a Multi-Agent System (MAS) developed with the JADE framework and emulating the behavior of the La Poste CPPS. Our longer term objective is to pave the way for supporting the definition of a DT for this CPPS, and potentially for other CPPSs in different contexts in the future.

Cite

CITATION STYLE

APA

Niati, A., Selma, C., Tamzalit, D., Bruneliere, H., Mebarki, N., & Cardin, O. (2020). Towards a digital twin for cyber-physical production systems: A multi-paradigm modeling approach in the postal industry. In Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings (pp. 651–657). Association for Computing Machinery, Inc. https://doi.org/10.1145/3417990.3421438

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free