Affiliation:
1. H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332
2. The Boeing Company, 900 N Sepulveda Boulevard, El Segundo, CA 90245
Abstract
Abstract
In a half fuselage assembly process, shape control is vital for achieving ultra-high-precision assembly. To achieve better shape adjustment, we need to determine the optimal location and force of each actuator to push or pull a fuselage to compensate for its initial shape distortion. The current practice achieves this goal by solving a surrogate model-based optimization problem. However, there are two limitations of this surrogate model-based method: (1) low efficiency: collecting training data for surrogate modeling from many finite element analysis (FEA) replications is time-consuming; (2) non-optimality: The required number of FEA replications for building an accurate surrogate model will increase as the potential number of actuator locations increases. Therefore, the surrogate model can only be built on a limited number of prespecified potential actuator locations, which will lead to suboptimal control results. To address these issues, this paper proposes an FEA model-based automatic optimal shape control (AOSC) framework. This method directly loads the system equation from the FEA simulation platform to determine the optimal location and force of each actuator. Moreover, the proposed method further integrates the cautious control concept into the AOSC system to address model uncertainties in practice. The case study with industrial settings shows that the proposed Cautious AOSC method achieves higher control accuracy compared to the current industrial practice.
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering
Cited by
7 articles.
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