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Application of Multimodel Concept and Virtual Assistants to Build a Digital Twin for Supporting Adaptive Control of Manufacturing Process

  • WSB Merito University in Poznań

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The implementation of advanced production management systems, in particular digital twins of production processes, allows for the simulation of various process variants in response to changing internal and external factors, which allows for adaptive control of this process. At the same time, building a digital twin of the entire process is most often labor-intensive and troublesome. To reduce this problem, the concept of a distributed modular system was proposed, where modules (digital assistants) are linked to production subprocesses implemented on individual machines or smaller groups of machines. This concept facilitates the construction of a digital twin for complex processes. Large models are built as a multimodel - a non-homogeneous model of a complex object or process, consisting of integrated simpler models of a different nature, which are easier to build and tune to a specific machine/group of machines implementing individual processes. This approach facilitates the integration of IT systems in a manufacturing enterprise, allowing, among others, the use of the synergy effect between robotic process automation (RPA) and artificial intelligence (AI). These technologies are used in the proposed Intelligent Integration and Automation of Information Systems (SIIA ITS), which consists of cooperating digital assistants and a master module that coordinates their work and combines the results of their actions. Digital assistants, which can also act as digital twins of production subprocesses, allow for the simulation of various process variants in response to changing internal and external factors. The solution integrates advanced technologies such as machine learning, artificial intelligence and predictive optimization models, creating a comprehensive tool supporting decision-making processes. The effectiveness of the proposed model of the production process optimization system has been confirmed in practice on the example of a station for machining a cast iron hub, where the test results showed a significant improvement in the efficiency of production processes.

Original languageEnglish
Title of host publicationIntelligent Systems in Production Engineering and Maintenance IV - Production Engineering
EditorsAnna Burduk, Joanna Kochanska, Pichai Janmanee, Andre D.L. Batako, Justyna Patalas-Maliszewska, Ewa Dostatni, Ryszard Wyczólkowski
PublisherSpringer Science and Business Media Deutschland GmbH
Pages580-591
Number of pages12
ISBN (Print)9783032015167
DOIs
Publication statusPublished - 2026
Event5th International Conference on Intelligent Systems in Production Engineering and Maintenance, ISPEM 2025 - Wroclaw, Poland
Duration: 25 Jun 202527 Jun 2025

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference5th International Conference on Intelligent Systems in Production Engineering and Maintenance, ISPEM 2025
Country/TerritoryPoland
CityWroclaw
Period25/06/2527/06/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • AI
  • IPA
  • Industry 4.0
  • RPA
  • digital twin

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

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