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1 Journal of Achievements in Materials and Manufacturing Engineering

1 2011

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Six Sigma methodology applied to minimizing damping lag in hydraulic shock absorbers

Czop P., Sławik D., Włodarczyk T. H., Wojtyczka M., Wszołek G.

Journal of Achievements in Materials and Manufacturing Engineering

2011

Vol. 49, nr 2

243--250

Purpose: The aim of this paper is to identify the root cause of the temporary decrease of the damping force during the early stage of the compression phase of the stroking cycle, the so called damping lag, to describe measures of the phenomenon and to present methods for optimizing the design towards minimizing this (negative) effect. Design/methodology/approach: Theoretical background is presented in a constructive and computable manner with emphasis on measurement data analysis and MATLAB/Simulink modeling. Six Sigma tools were used to validate the model statistically and, more importantly, to propose a method of data-driven optimization of the design. Findings: Root cause of the occurrence of the damping lag was confirmed during model validation to be caused by oil aeration. The dependence of the damping lag on parameters is nonlinear. Six Sigma methodology proved to be useful in achieving design optimality. Research limitations/implications: Statistical model and conclusions drawn from it are only valid in the interior of the investigated region of the parameter space. Additionally, it might not be possible to find a local minimum of the aeration measure (damping lag) inside the selected region of the parameter space; global minimum located at the boundary might be the only possible solution. Practical implications: Optimal value of parameters is not unique and thus additional sub-criteria (cost/ durability) can be imposed. Conducting tests in an organized manner and according to the Six Sigma methodology allows for expediting the design optimization process and eliminating unnecessary costs. Originality/value: : Improvements in understanding and measuring aeration effects constitute a clear foundation for further product optimization. Signal post-processing algorithms are essential for the statistical analysis and are the original contribution of this work.