Modelling Key Performance Indicators (KPIs) in the Optimisation of Nanoimprint Lithography (NIL) Processes

Area of Science:

• Nanotechnology and Materials Science
• Manufacturing Engineering
• Process Optimization

Background:

• Nanoimprint lithography (NIL) is crucial for nanomanufacturing but requires robust process evaluation tools.
• Current methods lack integrated indicators for optimizing quality, stability, and efficiency.

Purpose of the Study:

• To develop and model Key Performance Indicators (KPIs) for optimizing nanoimprint lithography (NIL) processes.
• To create an integrated KPI model linking process stages, parameters, and quality outcomes.

Main Methods:

• Literature review, industry expert surveys, and interviews to identify relevant KPIs.
• Process analysis and multi-criteria optimization to link KPIs with critical parameters for various NIL techniques (Thermal NIL, UV-NIL, R2R NIL, Step-and-Repeat NIL).

Main Results:

• An integrated KPI model classifying indicators by NIL process stages.
• Demonstrated improvements in nanostructure mapping accuracy and defect density reduction.
• Increased process efficiency without compromising technological stability.

Conclusions:

• The proposed integrated KPI model offers a universal tool for NIL process control and optimization.
• Facilitates scaling NIL to industrial applications and integration with data-driven methods.
• Enhances overall nanomanufacturing performance and product quality.