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Related Experiment Video

Updated: Aug 12, 2025

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

Digital twin-based multi-level task rescheduling for robotic assembly line.

Bitao Yao¹, Wenjun Xu^2,3, Tong Shen^2,3

¹School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, 430070, China.

Scientific Reports

|January 31, 2023

Summary

This summary is machine-generated.

This study introduces a digital twin (DT) framework to dynamically reschedule robotic assembly lines (RALs) amidst production disturbances. The DT-based approach ensures real-time adaptation, improving manufacturing efficiency and addressing scheduling deviations.

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Area of Science:

Manufacturing Engineering
Robotics
Industrial Automation

Background:

Robotic assembly lines (RALs) enhance production efficiency but are vulnerable to dynamic disturbances causing scheduling deviations.
Traditional scheduling methods lack the real-time adaptability required for smart manufacturing environments.

Purpose of the Study:

To propose a digital twin (DT)-based framework for dynamic task rescheduling in RALs.
To enable timely and adaptive adjustments to scheduling plans under uncertain interferences.

Main Methods:

A DT model for RAL task rescheduling, comprising physical entity (PE), virtual entity (VE), and virtual-reality interaction.
A DT-driven, multi-level rescheduling strategy triggered by events or user demand.
An improved discrete fireworks algorithm utilizing precedence graphs for efficient rescheduling.

Main Results:

The proposed DT framework effectively models RAL task rescheduling.
The multi-level rescheduling strategy demonstrates adaptive planning under disturbances.
The improved discrete fireworks algorithm balances computing time and solution quality.

Conclusions:

The DT-based framework offers a robust solution for dynamic task rescheduling in robotic assembly lines.
The developed methodologies facilitate real-time adaptation to manufacturing uncertainties.
Experimental verification confirms the effectiveness of the proposed model and approach for RAL task scheduling.