In-situ Process Monitoring Data of PECVD Plasma

The storage capacity of 3D-NAND flash memory has been enhanced by the multi-layer dielectrics. The deposition process has become more challenging due to the tight process margin and the demand for accurate process control. To reduce product costs and ensure successful processes, process diagnosis techniques incorporating artificial intelligence (AI) have been adopted in semiconductor manufacturing. Recently there is a growing interest in process diagnosis, and numerous studies have been conducted in this field. For higher model accuracy, various process data are required, such as plasma, gases, equipment control state, and process result. Also it is important to data must be have the reproducibility of raw data is difficult to acquire due to the data security policy of the chip manufactures.

多层电介质（multi-layer dielectrics）可提升3D-NAND闪存的存储容量，但受限于严苛的工艺窗口以及对精准工艺控制的需求，沉积制程的难度显著增加。为降低产品成本并保障制程顺利落地，半导体制造领域已引入融合人工智能（Artificial Intelligence，AI）的工艺诊断技术。近年来，工艺诊断领域的研究关注度持续走高，该领域已涌现出大量相关研究成果。为提升模型精度，需采集多维度工艺数据，涵盖等离子体（plasma）、工艺气体、设备控制状态以及制程结果等类型。此外，原始数据的可复现性是保障研究有效性的关键，但由于芯片制造商的数据安全政策，获取具备可复现性的原始数据存在较大难度。