Outliers Effect in Measurement Data for T-peel Adhesion Test using Robust Parameter Design

Abstract

As many researches focused on application of robust design engineering in practical case study, very less concerned on the criticality to data measurement system in parameter design. This paper will emphasize on the importance to be critical to data obtained during experiment. The existence of outliers is often ignored and the impact overlooked, thus endanger the results by producing false alarm and giving completely wrong parameter setting. The optimum condition from the data that contains outliers is compared with the corrected data measurement. The finding presents the indication procedure on how to confirm whether the data is reliable or not for evaluation. The data is unreliable when two main indicators are detected. Firstly, the measurement data plot detects outlier through linear regression analysis as it does not belong on the linear line. Secondly, poor reproducibility presented by estimation and confirmation of signal-to-noise ratio. This failure affects the experimental design and lead to wrong optimum condition. T-peel adhesion test using orthogonal array L9 is done as a case study to elucidate the detection of outlier and outlier effect on optimum condition.

Development of F-N-C-O Taguchi Method for Robust Measurement System Using a Case Study of T-Peel Test on Adhesion Strength

“…After determining the control factors and factor's level, they are assigned into an orthogonal array. An orthogonal array is used for optimization to maximize the signal-to-noise ratio [1,8,9]. Balance set of experimentation runs is provided by orthogonal array.…”

“…These factors are said to be active but have no interaction with noise factors. The second category is a group of control factors that are active by virtue of having an interaction with noise factors [8]. They have the dispersion effect.…”

“…It is very important to have a robust measurement system explaining from the method of data measurement up to its optimization with minimum variation in the system. Most published papers discussed the test method used in some case studies [9][10][11][12][13][14][15][16][17][18][19][20][21] while others discussed the measurement concepts and theories [8,10,[22][23][24][25]. However, less research has been done to connect both aspects in a single study [9].…”

Optimisation of Process Parameters for Lower Leakage Current in 22 nm n-type MOSFET Device using Taguchi Method

“…In this case, the dynamic ideal function is used where the dynamic ideal function equation is given by, y = βM [18], where y is the output response where in this case is the ILEAK value. M is the input signal which refers to the drain voltage that is internally applied in the simulation process.…”