Access Type

Open Access Thesis

Date of Award

January 2013

Degree Type


Degree Name



Mechanical Engineering

First Advisor

Xin Wu


AISI D2 steels are widely used as tools for forming, drawing and trimming dies due to its high wear resistance, high compressive strength and low distortion, and its performance as a trim die material for cutting ultra-high strength steels (at 1GPa or above) is investigated in this study.

To simulate the production trimming process under a laboratory accelerated fatigue condition, a trim die simulator and testing technique have been developed. In this test 1" cubic die samples were used that offers total 12 cutting edges of 6 different material grain orientations in shearing, and with adjustable die clearance. A non-contact metal removal volume measurement was developed to quantify the degree of fatigue damage during cyclic loading, and the metallurgical replica method was used at different number of cycles from the interrupted testing for obtaining micro-damage information. The damage rate at the cutting edge was obtained as a function of trimming process variables, including the die material grain orientations, the loading frequency, and the amplitude of fatigue loading. The microstructure, micro-damage and fractured surfaces were examined with optical microscopy and scanning electron microscopy.

The results show that there exist two types of distinct damage processes: the continuous contact deformation process that occurs at a low fatigue load, and the discontinuous cutting edge chipping process at a high fatigue loading with significantly higher material removal rate. The chipping involves crack initiation and propagation within the carbide phase surrounding the pro-eutectic grains, leading to grain broken and fall apart. An empirical trim die damage rate model in Paris law form is obtained from experimental data regression, and can be used for tool life prediction. The grain orientation relative to the cutting direction is found to have remarkable effect on trimming damage rate.