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Record Nr. |
UNINA9910484979503321 |
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Autore |
Tang Dunbing |
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Titolo |
Adaptive Control of Bio-Inspired Manufacturing Systems [[electronic resource] /] / by Dunbing Tang, Kun Zheng, Wenbin Gu |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (135 pages) |
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Collana |
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Research on Intelligent Manufacturing, , 2523-3386 |
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Disciplina |
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Soggetti |
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Control engineering |
Artificial intelligence |
Manufactures |
Quality control |
Reliability |
Industrial safety |
Control and Systems Theory |
Artificial Intelligence |
Manufacturing, Machines, Tools, Processes |
Quality Control, Reliability, Safety and Risk |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Bio-Inspired Manufacturing System Model -- Hormone-regulation based Algorithm for Production Scheduling Optimization -- NeuroEndocrine-regulation based Dynamic Coordination Mechanism in Bio-Inspired Manufacturing System -- Hormone-regulation based approach for distributed and on-line scheduling of machines and AGVs -- Production control strategy inspired by neuroendocrine regulation -- NeuroEndocrine-Immune regulation based approach for disturbance handling -- Prototype and Application of the Bio-Inspired Manufacturing System. |
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Sommario/riassunto |
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This book introduces state-of-the-art models and methods based on the neuroendocrine-immune-inspired approaches in the field of manufacturing control systems. It develops various bio-inspired intelligent approaches for multiple applications in order to efficiently |
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generate production plans and control solutions and agilely deal with the frequent unexpected disturbances at the shop floor level. It also provides an introduction to bio-inspired manufacturing systems with intelligent control structures and the latest technologies. Further, the book describes recent advances in the bio-inspired methodology for a high-level adaptability in manufacturing systems, including the bio-inspired control architecture and the implementation of intelligent and adaptive control approaches based on neuroendocrine-immune mechanisms and hormone-regulation principles. It offers a valuable resource for graduate students, researchers and engineers in the fields of production management, manufacturing system control and related areas. . |
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