Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations
In this study, we explore the fundamentals of design and deployment of Multi-Agent Swarm Engineering Systems (MASESs), a comprehensive framework aimed at improving decision-making and operational efficiency in industrial environments. Swarm engineering systems draw inspiration from collective behavi...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11097308/ |
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| author | Raza Muhammad Kazim Guoxin Wang Zhenjun Ming Janet K. Allen Farrokh Mistree |
| author_facet | Raza Muhammad Kazim Guoxin Wang Zhenjun Ming Janet K. Allen Farrokh Mistree |
| author_sort | Raza Muhammad Kazim |
| collection | DOAJ |
| description | In this study, we explore the fundamentals of design and deployment of Multi-Agent Swarm Engineering Systems (MASESs), a comprehensive framework aimed at improving decision-making and operational efficiency in industrial environments. Swarm engineering systems draw inspiration from collective behaviors observed in natural swarms (such as ants or bees), offering a decentralized approach to problem-solving in complex systems. We provide a detailed theoretical foundation for MASES, focusing on key elements such as spatial control formation, adaptive coordination, decision-making dynamics, and critical factors such as scalability, adaptability, and robustness in practical applications. The analysis is enriched with insightful tables that highlight current innovations and challenges, underscoring the importance of balancing decentralization with scalability. In transitioning to practical applications, we discuss design methodologies and performance evaluation strategies, emphasizing the transformative potential of swarm engineering systems. Crucially, we highlight how artificial intelligence (AI) and machine learning (ML) are being integrated into MASES to enhance decision-making capabilities, adaptability, and scalability. Advanced frameworks and simulation environments have been shown to play a crucial role in ensuring that MASES operates effectively, fostering intelligence and adaptability to meet complex industrial demands. By showcasing various applications, we highlight the potential of MASES to enhance operational landscapes across industries and identify pathways for future research to refine and perfect this integration. |
| format | Article |
| id | doaj-art-3ad3c1b287bf4d1eba33076febfab5e4 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-3ad3c1b287bf4d1eba33076febfab5e42025-08-20T03:06:44ZengIEEEIEEE Access2169-35362025-01-011313934513937610.1109/ACCESS.2025.359295011097308Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and InnovationsRaza Muhammad Kazim0Guoxin Wang1https://orcid.org/0000-0003-2363-8595Zhenjun Ming2https://orcid.org/0000-0001-6429-5889Janet K. Allen3https://orcid.org/0000-0003-0686-6764Farrokh Mistree4https://orcid.org/0000-0001-6835-0902School of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing, ChinaSystems Realization Laboratory, The University of Oklahoma, Norman, OK, USASystems Realization Laboratory, The University of Oklahoma, Norman, OK, USAIn this study, we explore the fundamentals of design and deployment of Multi-Agent Swarm Engineering Systems (MASESs), a comprehensive framework aimed at improving decision-making and operational efficiency in industrial environments. Swarm engineering systems draw inspiration from collective behaviors observed in natural swarms (such as ants or bees), offering a decentralized approach to problem-solving in complex systems. We provide a detailed theoretical foundation for MASES, focusing on key elements such as spatial control formation, adaptive coordination, decision-making dynamics, and critical factors such as scalability, adaptability, and robustness in practical applications. The analysis is enriched with insightful tables that highlight current innovations and challenges, underscoring the importance of balancing decentralization with scalability. In transitioning to practical applications, we discuss design methodologies and performance evaluation strategies, emphasizing the transformative potential of swarm engineering systems. Crucially, we highlight how artificial intelligence (AI) and machine learning (ML) are being integrated into MASES to enhance decision-making capabilities, adaptability, and scalability. Advanced frameworks and simulation environments have been shown to play a crucial role in ensuring that MASES operates effectively, fostering intelligence and adaptability to meet complex industrial demands. By showcasing various applications, we highlight the potential of MASES to enhance operational landscapes across industries and identify pathways for future research to refine and perfect this integration.https://ieeexplore.ieee.org/document/11097308/Swarm intelligencedecentralized systemsmulti-agent systemsdesign approachesdevelopment frameworks |
| spellingShingle | Raza Muhammad Kazim Guoxin Wang Zhenjun Ming Janet K. Allen Farrokh Mistree Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations IEEE Access Swarm intelligence decentralized systems multi-agent systems design approaches development frameworks |
| title | Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations |
| title_full | Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations |
| title_fullStr | Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations |
| title_full_unstemmed | Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations |
| title_short | Design and Deployment of Swarm Engineering Systems: Insights, Challenges, and Innovations |
| title_sort | design and deployment of swarm engineering systems insights challenges and innovations |
| topic | Swarm intelligence decentralized systems multi-agent systems design approaches development frameworks |
| url | https://ieeexplore.ieee.org/document/11097308/ |
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