LAUSR

The current thin film transistor liquid crystal display (TFT-LCD) panel industry evolves in transition from volume production to customized production service as a major competition strategy. Owing to the highly mixed production type of small batch sizes and high varieties, metrology data are usually collected too infrequently for building accurate virtual metrology (VM) models. In this paper, a new product-to-product (P2P) VM model to predict photoresist spacer heights in the color filter process of the array sector is developed. First, a position-based random forests model is proposed for the base product. Second, an ensemble model combining the base model and a biased estimation random forests model for the new product of small batch size is proposed to perform P2P VM between different products on the same tool. The real datasets of photoresist spacer heights for different products are used to illustrate the accuracy of the new P2P VM framework in the experimental study. Note to Practitioners—As global competition intensifies, production management needs to be adjusted to adapt swiftly to changes in the time-varying and competitive market. For manufacturing firms, how to operate the manufacturing system effectively and efficiently plays a crucial role in quality and yield improvements. The color filter process in the array sector is of critical importance in the TFT-LCD practice since it essentially dictates the quality level of subsequent processing steps in the cell and assembly sectors. Virtual metrology is a state-of-the-art measure that can be used for monitoring and controlling purposes to maintain the yield and productivity of the color filter process in the highly mixed production environment. An immediate challenge to be faced by the data scientists is how to build accurate virtual metrology models for a variety of product lines separately in color filter manufacturing. A new proposal of product-to-product virtual metrology is first addressed between products, enabling to build appropriate virtual metrology models for new products with small-sized production batches.