Wafer asset modeling using language processing methods

A computing device comprising:

• a processor;
• a storage device for content and programming coupled to the processor;
• a wafer asset modeling module stored in the storage device, wherein an execution of the wafer asset modeling module by the processor configures the computing device to perform acts comprising:
• identifying and clustering a plurality of assets based on static properties of a wafer asset using a first module of the wafer asset modeling module;
• determining a rating of one or more assets of the clustered plurality of assets based on dynamic properties of the wafer asset by a second module of the wafer asset modeling module;
• performing an event prediction by converting a numeric data of the clustered plurality of assets to a natural language processing (NLP) domain by a third module of the wafer asset modeling module;
• performing one or more sequence-to-sequence methods to predict a malfunction of a component of the wafer asset and/or an event based on past patterns, by the third module of the wafer asset modeling module;
• and
• providing the event prediction information and storing in the storage device.