Integrating Machine Learning for Automated Root Cause Analysis of Critical-to-Quality (CTQ) in Hard Disk Drive Manufacturing

Abstract

This research was studying the process of analyzing key factors that significantly impact the quality of Head Stack Assembly (HSA) in the production of Hard Disk Drives (HDDs). Various factors are considered, such as production machine, testing equipment, lot numbers of raw materials, production time and testing times etc. The assembly of the Head Stack is a critical step in Hard Disk Drives manufacturing. As the number of heads increases, the process requires greater precision and careful consideration of multiple factors. The use of artificial Intelligence technology in research is to be able to analyze the causal factors that affect the assembly of Head Stack more quickly and accurately in order to help reduce damage that will affect the production process and the quality of the Hard Disk Drives. It also increases the reliability of the product and raises the production standards, including quality control for the Hard Disk Drives manufacturing industry.