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Related Experiment Video

Updated: Sep 24, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

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Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making.

Malvina Roci1, Niloufar Salehi1, Saman Amir2

  • 1Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.

Methodsx
|May 6, 2022
PubMed
Summary
This summary is machine-generated.

This study presents a step-by-step method for building multi-method simulation models of circular manufacturing systems (CMS). This approach enhances decision-making by assessing the economic, environmental, and technical performance of these complex value networks.

Keywords:
AB:, Agent-basedAgent-basedCMS:, Circular Manufacturing SystemsCircular economyCircular manufacturing systemsComplex adaptive systemsDE:, Discrete-eventDiscrete-eventGHG:, Greenhouse gas emissionsGIS:, Geografic Information SystemMulti-method simulationSD:, System dynamicsSystem dynamics

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Area of Science:

  • Systems Engineering
  • Industrial Ecology
  • Computational Science

Background:

  • Circular manufacturing systems (CMS) are intricate value networks requiring collaboration among diverse stakeholders to achieve product lifecycle closure.
  • Effective modeling and simulation are essential for understanding the complex dynamics and performance of CMS.
  • Traditional simulation methods often fall short in capturing the multifaceted nature of CMS.

Purpose of the Study:

  • To provide a structured methodology for developing multi-method simulation models for CMS.
  • To enable comprehensive assessment of economic, environmental, and technical performance within CMS.
  • To support enhanced decision-making for optimizing circular economy strategies.

Main Methods:

  • Utilizing a multi-method simulation architecture combining agent-based, discrete-event, and system dynamics approaches.
  • Integrating a Geographic Information System (GIS) to define agent interactions based on spatial proximity within the CMS environment.
  • Tracing the product journey across multiple lifecycles through stakeholder interactions in the circular value network.

Main Results:

  • Demonstrates the feasibility of building a comprehensive multi-method simulation model for CMS.
  • Highlights the capability of the model to capture heterogeneous stakeholder characteristics and interactions.
  • Establishes a framework for quantitatively evaluating CMS performance across economic, environmental, and technical dimensions.

Conclusions:

  • Multi-method simulation modeling is highly suitable for analyzing the complexity of circular manufacturing systems.
  • The proposed step-by-step approach facilitates the creation of robust CMS simulation models.
  • This modeling framework provides valuable insights for improving the design and operation of circular economy initiatives.