Authored

17 records found

Production efficiency in metal forming processes can be improved by implementing robust optimization. In a robust optimization method, the material and process scatter are taken into account to predict and to minimize the product variability around the target mean. For this purpo ...
Production efficiency in metal forming processes can be improved by implementing robust optimization. In a robust optimization method, the material and process scatter are taken into account to predict and to minimize the product variability around the target mean. For this purpo ...
In this work, metamodel-based robust optimization is performed using measured scatter of noise variables. Principal component analysis is used to describe the input noise using linearly uncorrelated principal components. Some of these principal components follow a normal probabil ...
In this work, metamodel-based robust optimization is performed using measured scatter of noise variables. Principal component analysis is used to describe the input noise using linearly uncorrelated principal components. Some of these principal components follow a normal probabil ...
A robustness criterion that employs skewness of output is presented for a metamodel-based robust optimization. The propagation of a normally distributed noise variable via nonlinear functions leads to a non-normal output distribution. To consider the non-normality of the output, ...
Robust optimization is a powerful method to find the parameters for a process at which its output is least sensitive to the variation of the input parameters. In this method, measured or estimated noise parameters are used to estimate the scatter of the output. At the optimum des ...
Robust optimization is a powerful method to find the parameters for a process at which its output is least sensitive to the variation of the input parameters. In this method, measured or estimated noise parameters are used to estimate the scatter of the output. At the optimum des ...
Optimization under uncertainty requires proper handling of those input parameters that contain scatter. Scatter in input parameters propagates through the process and causes scatter in the output. Stochastic methods (e.g. Monte Carlo) are very popular for assessing uncertainty pr ...
Optimization under uncertainty requires proper handling of those input parameters that contain scatter. Scatter in input parameters propagates through the process and causes scatter in the output. Stochastic methods (e.g. Monte Carlo) are very popular for assessing uncertainty pr ...

Contributed

3 records found

How Do Exoskeletons Change Shoulder Biomechanics?

A New Design Tool for “Human-In-the-Loop” Optimization of Shoulder Exoskeletons

Shoulder exoskeleton is a popular solution to work-related shoulder disorders and muscle fatigue. With a wide range of exoskeletons designed, a comprehensive report on how the use of shoulder exoskeletons changes shoulder biomechanics is still missing. In this project, the impact ...

Binder Jet Additive Manufacturing of Copper

Optimizing the print and post-process parameters to achieve high density copper parts

This research aimed to optimize the process parameters of small copper parts printed with binder jetting. The optimisation was distinguished by dividing the parameters in print and post-process parameters. Binder jetting is an additive manufacturing technique that combines layers ...
Hydrofoil crafts with fully submerged foils can provide fast and economical waterway transport. However, their operation requires reliable onboard control systems to ensure the safety and comfort of their passengers, especially in rough sea conditions. This thesis project is focu ...