Nanoimprint lithography (NIL) plays an increasingly important role in modern nanomanufacturing processes, but its effective application in production conditions requires precise tools for evaluating and optimising technological processes. The aim of the study was to develop and model key performance indicators (KPIs) supporting the optimisation of the quality, stability and efficiency of nanoimprint lithography processes. As part of the selection of indicators, a literature review, surveys and in-depth interviews with industry experts were conducted, which enabled the identification of indicators relevant from a technological practice perspective. The proposed KPI classification was directly linked to the stages of the NIL process, creating a basis for operational performance control and process capability analysis. A novel aspect is the proposal of an integrated KPI model that combines the classification of indicators based on the stages of the NIL process with their direct link to technological parameters and measurable quality effects. These indicators have been linked to critical process parameters for different NIL variants, including Thermal NIL, UV-NIL, Roll-to-Roll NIL and Step-and-Repeat NIL, using a process analysis and multi-criteria optimisation approach. Research indicates that the use of an integrated KPI model improves the accuracy of nanostructure mapping, reduced defect density, and increased process efficiency without compromising technological stability. The proposed approach is a universal tool supporting NIL process control, its scaling to industrial applications, and integration with statistical process control and data-driven optimisation methods.
Pacana et al. (Fri,) studied this question.