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Multi-stage Bayesian optimization for throughput improvement in stochastic manufacturing systems
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DOI：10.1016/j.jmsy.2026.04.015.png)
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Abstract
En 中文
• Proposed a Multi-Stage Bayesian Optimization for manufacturing throughput. • Optimized bottleneck improvement sequences under budget constraints using a look-ahead policy. • Achieved higher and more consistent throughput compared to greedy methods. • Integrated NEI (Noise Expected Improvement), Sobol’-screening, and Knowledge Gradient for robust optimization. • Demonstrated potential for Digital Twin-based dynamic line balancing.
Keywords:
Bayesian Optimization
Throughput Improvement
Stochastic Manufacturing Systems
Multi-stage Optimization
Digital Twin
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14.2
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2.6K
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