A green scheduling model for two-stage photo-etching and acid-etching collaboration in semiconductor manufacturing

Abstract

In semiconductor manufacturing, photo-etching and acid-etching processes play crucial roles in precisely crafting intricate patterns on storage chip wafers. However, these processes generate significant hazardous waste, leading to high disposal costs. Consequently, there has been increased research into cost-effective and environmentally friendly solutions. This study introduces a custom green scheduling framework inspired by sustainable practices in storage chip wafer fabrication. The framework optimizes the coordination of photo-etching and acid-etching processes, taking into account wait time limits and capacity constraints. Additionally, we propose an efficient hybrid meta-heuristic algorithm designed to reduce energy consumption, minimize makespan, and optimize the quantity of acid-etching baths. This approach identifies the most efficient number of acid-etching tanks for various scenarios, significantly reducing waste production. Empirical results demonstrate the algorithm's effectiveness, highlighting its potential for substantial cost savings and waste reduction. By exploring the relationship between the number of acid-etching tanks and makespan, we identify the optimal tank quantity for diverse scenarios. These insights pave the way for enhanced resource efficiency and sustainable practices in semiconductor manufacturing.