Predictive Analytics for Equipment Maintenance Operations

Abstract

Predictive maintenance (PdM) is a key application of data analytics in semiconductor manufacturing. The optimization of equipment performance has been found to deliver significant revenue benefits, especially in the wafer fabrication process. This chapter addresses two main research objectives: first, to investigate the particular challenges and opportunities of implementing PdM for wafer fabrication equipment and, second, to identify the implications of PdM on key performance indicators in the wafer fabrication process. The research methodology is based on a detailed case study of a wafer fabrication facility and expert interviews. The findings indicate the potential benefits of PdM beyond improving equipment maintenance operations, and the chapter concludes that the quality of analytics models for PdM in wafer fabrication is critical, but this depends on challenging data preparation processes, per machine type. Without valid predictions, decision-making ability and benefits delivery will be limited.

Predictive Maintenance of Pins in the ECD Equipment for Cu Deposition in the Semiconductor Industry

“…Besides manufacturing optimization and control, another important area of intervention of Industry 4.0 is Predictive Maintenance (PdM), where suitable machine-dependent software analyzes sensor data gathered from the hardware equipment and tools during a process, and predicts when such equipment requires maintenance, before a breakdown occurs, avoiding unnecessary maintenance and rupture of hardware tools as well. See [ 15 ] for an up-to-date history in industry with its growing importance and [ 16 ] for its impact in the semiconductor industry specifically, also based on interviews.…”