With these two novel methods, a methodological framework to perform better maintenance in complex manufacturing processes is established. The simulation study shows that the maintenance cost can be reduced by performing predictive maintenance properly while highest possible yield is retained. This framework provides a possibility of using abundant equipment monitoring data and product quality information to coordinate maintenance actions in a complex manufacturing environment.CHAPTER 4 HIDDEN MARKOV MODEL BASED PREDICTION OF TOOL DEGRADATION UNDER VARIABLE OPERATING CONDITIONS 4.1. Introduction Since particle contamination in semiconductor fabrication tools is a major source ofanbsp;...
|Title||:||Predictive Modeling for Intelligent Maintenance in Complex Semiconductor Manufacturing Processes|
|Publisher||:||ProQuest - 2008|