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Required parameters for modelling heterogeneous geographically dispersed manufacturing systems.
Mark Goudswaard1, Chris Snider1, Martins Obi1
1University of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Procedia CIRP
|February 6, 2023
Summary
Global crises necessitate rethinking manufacturing strategies. Agent-based brokering of Additive Manufacturing (AM) offers a solution, but requires considering AM capability diversity for effective coordination.
Area of Science:
- Manufacturing Systems Engineering
- Supply Chain Management
- Additive Manufacturing (AM) Technologies
Background:
- Global events like COVID-19 expose vulnerabilities in traditional manufacturing and supply chains.
- Existing manufacturing models are often homogeneous, failing to capture the diverse capabilities of Additive Manufacturing (AM).
- Future manufacturing faces volatility from supply chain disruptions, trade shifts, and natural disasters, demanding adaptable solutions.
Purpose of the Study:
- To conceptualize the reality of Additive Manufacturing (AM) systems.
- To identify essential parameters for modeling and coordinating diverse AM capabilities.
- To explore levels of abstraction, performance metrics, and human roles in agent-based manufacturing.
Main Methods:
- Conceptual framework development for agent-based Additive Manufacturing (AM) brokering.
- Identification and elucidation of key parameters for diverse AM system modeling.
- Discussion of abstraction levels, performance metrics, and human-agent interaction in manufacturing.
Main Results:
- Additive Manufacturing (AM) offers a potential solution to manufacturing system volatility.
- Modeling diverse AM capabilities is crucial for effective agent-based brokering.
- Key parameters for successful AM system modeling and coordination have been identified.
Conclusions:
- Agent-based brokering of Additive Manufacturing (AM) can address production needs at various scales.
- Acknowledging and modeling the diversity of AM capabilities is imperative for realizing brokered AM.
- Further research into abstraction levels, metrics, and human roles is needed for advanced agent-based manufacturing systems.
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