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In the field of robust design, most estimation methods for output responses of input factors are based on the response surface methodology (RSM), which makes several assumptions regarding the input data. However, these assumptions may not consistently hold in real-world industrial problems. Recent studies using artificial neural networks (ANNs) indicate that input–output relationships can be effectively estimated without the assumptions mentioned above. The primary objective of this research is to generate a new, robust design dual-response estimation method based on ANNs. First, a second-order functional-link-NN-based robust design estimation approach has been proposed for the process mean and standard deviation (i.e., the dual-response model). Second, the optimal structure of the proposed network is defined based on the Bayesian information criterion. Finally, the estimated response functions of the proposed functional-link-NN-based estimation method are applied and compared with that obtained using the conventional least squares method (LSM)-based RSM. The numerical example results imply that the proposed functional-link-NN-based dual-response robust design estimation model can provide more effective optimal solutions than the LSM-based RSM, according to the expected quality loss criteria.

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When designing a ship, ergonomic considerations are crucial when minimizing a navigator's fatigue due to the burden of work, and to appropriately operate the navigational equipment for each given situation by helping the operator to understand the surroundings as well as the physical functions of the ship. However, insufficient consideration of ergonomic elements in the actual design of ship Bridges is lowering the performance of safe navigation and allows for the possibility of operation or readout errors. Consequently, these errors lead to an increase in maritime accidents. Therefore, this study conducted a usability evaluation on the importance of and the usage frequency of navigational equipment, their influence on actual navigation, and the possibility of error upon operation or readout between training ship officers, to derive an optimized layout that includes the consideration of ergonomic factors for on-Bridge navigational equipment, which are currently arranged differently according to their type or size. The optimized layout of on-Bridge navigational equipment was carried out based on the evaluation results, using the Lingo program. Through the process of optimization, revised layouts of on-Bridge navigational equipments(control and display device) were suggested, considering emergency situations(ship collision, stranding, fire and explosion, sinking, etc.) during navigation.