Artificial Intelligence Techniques for Quality Control of Hard Disk Drive Components

Abstract

© 2015 John Wiley & Sons, Inc. All Rights Reserved. This chapter presents the theoretical aspect concerning the application of artificial intelligence (AI) techniques to control the quality of hard disk drive (HDD) components. It first describes general guidelines of how AI could be applied to quality control (QC) task, and includes a review of some key literatures. AI tasks in QC can be classified into three groups: classification and prediction, clustering and time series analysis. Subsequently, the chapter presents three examples, namely, the case of using artificial neural networks (ANN) for multipanel lamination process modeling, HDD actuator arm control chart pattern recognition with AI, and machine clustering with AI. From all the examples, it can be concluded that AI tools have demonstrated highly promising results in the field of QC of HDD components where the process is complex and usually nonlinear.