Optimization of actuator performance using robust engineering and feature selection methodologies

What is it about?

The purpose of this study is to demonstrate how the variation between the set torque and the actual torque at which the actuator trips can be minimized using Taguchi’s robust engineering methodology. The paper also demonstrates the application of feature selection methodology for the identification of insignificant effects in unreplicated fractional factorial experiments. An experiment was designed with the set torque as the signal factor and the tripping torque as response variable using L8 orthogonal array. The compounded noise factor was selected based on the type of operation and load variation, which are not under the actuator manufacturer’s control. The effect of five control factors (with two levels each) and two interactions were also studied. The results showed that the factors spring height, spring thickness, star washer position and the interaction between drive shaft length and spring height play a significant role in actuator performance. The implementation of the optimum combination of factors resulted in improving the overall capability indices, Cp from 0.52 to 2.12 and Cpk from 0.4 to 1.67.

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Why is it important?

This study provides valuable information to the actuator manufacturers on optimizing the actuator performance. To the best of author’s knowledge, no study has been conducted using Taguchi’s robust engineering methodology to optimize the actuator performance. In addition, no attempt has been made in the past to identify the insignificant factors and interactions using feature selection methodology for unreplicated fractional factorial experiments.

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