Optimization of hydraulic dampers with the use of Design For Six Sigma methodology

Purpose: The aims of this paper are to identify the root cause of the temporary decrease in the damping force which occurs during the early stage of the stroking cycle’s compression phase, 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: A theoretical background is presented in a constructive and computable manner with emphasis on data-driven modeling. The Design For Six Sigma (DFFS) approach and tools were used to validate the model statistically and, more importantly, to propose a method for data-driven optimization of the design. Findings: The root cause of the damping lag was confirmed during model validation as being a result of oil aeration. DFFS methodology proved to be useful in achieving design optimality. Research limitations/implications: The 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; a/the (depending on the context) global minimum located at the boundary might be the only possible solution. Practical implications: The 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 the design optimization process to be expedited and unnecessary costs to be eliminated. 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.