Optimisation of Lapping Process Parameters for Single-Crystal 4H-SiC Using Orthogonal Experiments and Grey Relational...

Area of Science:

• Materials Science and Engineering
• Surface Metrology
• Semiconductor Manufacturing

Background:

• Global planarization of silicon carbide (SiC) and semiconductor substrates relies on lapping.
• Optimizing SiC lapping requires understanding parameters influencing material removal rate (MRR_m), surface roughness (Ra), and total thickness variation (TTV).
• Existing methods lack comprehensive optimization for multiple lapping performance indicators.

Purpose of the Study:

• To investigate the effects and interactions of SiC lapping process parameters on lapping performance.
• To identify optimal parameters for achieving high MRR_m, low Ra, and low TTV.
• To develop a comprehensive evaluation method for SiC lapping performance.

Main Methods:

• Orthogonal experiments were employed to study the influence of lapping parameters and their interactions.
• Intuitive analysis (range, variance, effect curve) was used for single-index optimization.
• Entropy value and grey relational analysis were applied for multi-index optimization to determine the grey relational grade (GRG).

Main Results:

• Lapping plate type, abrasive size, and their interaction significantly impacted MRR_m and Ra (>85% contribution).
• The interaction between lapping plate type and abrasive size was most critical for TTV (51.07% contribution).
• Optimized parameters using grey relational analysis yielded MRR_m of 90.2 μm/h, Ra of 0.769 nm, and TTV of 3 μm.

Conclusions:

• Lapping plate type, abrasive size, and normal pressure are key parameters influencing SiC lapping performance.
• Grey relational analysis provides a superior method for multi-objective optimization compared to intuitive analysis.
• The combined approach of orthogonal experiments and grey relational analysis offers a robust strategy for optimizing SiC lapping processes.