{"title":"利用遗传算法和深度强化学习对半导体晶片探针卡盘进行优化研究","authors":"Geuna Choi, Sheriff Abiodun Aodu, Il Seouk Park","doi":"10.1007/s12206-024-0734-4","DOIUrl":null,"url":null,"abstract":"<p>The probe chuck is an inspection device assessing the thermal durability of semiconductor wafers in various temperature environments before shipping. It is most important to ensure that the temperature of the chuck upper surface, on which the wafers are placed, is uniform. This study presents an axisymmetric chuck model to improve surface temperature uniformity in both radial and circumferential directions. The local distribution of the flow path height in the axisymmetric chuck was adjusted to make the chuck upper surface with a constant wall heat flux to simultaneously become as uniform temperature as possible. Three optimization algorithms, namely the genetic algorithm (GA), deep q-network (DQN), and actor-critic (AC) were applied. The optimized shape of the flow pathway, improved temperature uniformity, pressure drop, and local heat transfer coefficient profile by three different optimization algorithms are presented in detail. As a result, the surface temperature difference was significantly reduced from 7.137 K in the existing spiral model to 0.682 K. The optimal axisymmetric chuck could reduce surface temperature differences up to 90 % compared with the conventional spiral chuck.</p>","PeriodicalId":16235,"journal":{"name":"Journal of Mechanical Science and Technology","volume":"37 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization study of a probe chuck for semiconductor wafers using genetic algorithm and deep reinforcement learnings\",\"authors\":\"Geuna Choi, Sheriff Abiodun Aodu, Il Seouk Park\",\"doi\":\"10.1007/s12206-024-0734-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The probe chuck is an inspection device assessing the thermal durability of semiconductor wafers in various temperature environments before shipping. It is most important to ensure that the temperature of the chuck upper surface, on which the wafers are placed, is uniform. This study presents an axisymmetric chuck model to improve surface temperature uniformity in both radial and circumferential directions. The local distribution of the flow path height in the axisymmetric chuck was adjusted to make the chuck upper surface with a constant wall heat flux to simultaneously become as uniform temperature as possible. Three optimization algorithms, namely the genetic algorithm (GA), deep q-network (DQN), and actor-critic (AC) were applied. The optimized shape of the flow pathway, improved temperature uniformity, pressure drop, and local heat transfer coefficient profile by three different optimization algorithms are presented in detail. As a result, the surface temperature difference was significantly reduced from 7.137 K in the existing spiral model to 0.682 K. The optimal axisymmetric chuck could reduce surface temperature differences up to 90 % compared with the conventional spiral chuck.</p>\",\"PeriodicalId\":16235,\"journal\":{\"name\":\"Journal of Mechanical Science and Technology\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mechanical Science and Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s12206-024-0734-4\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mechanical Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12206-024-0734-4","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
摘要
探针卡盘是一种检测设备,用于评估半导体晶片在运输前各种温度环境下的热耐久性。最重要的是确保放置晶片的卡盘上表面温度均匀。本研究提出了一种轴对称卡盘模型,以改善径向和圆周方向的表面温度均匀性。通过调整轴对称卡盘中流道高度的局部分布,使卡盘上表面的壁面热通量恒定,同时温度尽可能均匀。应用了三种优化算法,即遗传算法(GA)、深q-网络(DQN)和行为批判(AC)。详细介绍了三种不同优化算法优化后的流道形状、改善后的温度均匀性、压降和局部传热系数曲线。结果,表面温差从现有螺旋模型的 7.137 K 显著降低到 0.682 K。与传统螺旋卡盘相比,优化轴对称卡盘可将表面温差降低达 90%。
Optimization study of a probe chuck for semiconductor wafers using genetic algorithm and deep reinforcement learnings
The probe chuck is an inspection device assessing the thermal durability of semiconductor wafers in various temperature environments before shipping. It is most important to ensure that the temperature of the chuck upper surface, on which the wafers are placed, is uniform. This study presents an axisymmetric chuck model to improve surface temperature uniformity in both radial and circumferential directions. The local distribution of the flow path height in the axisymmetric chuck was adjusted to make the chuck upper surface with a constant wall heat flux to simultaneously become as uniform temperature as possible. Three optimization algorithms, namely the genetic algorithm (GA), deep q-network (DQN), and actor-critic (AC) were applied. The optimized shape of the flow pathway, improved temperature uniformity, pressure drop, and local heat transfer coefficient profile by three different optimization algorithms are presented in detail. As a result, the surface temperature difference was significantly reduced from 7.137 K in the existing spiral model to 0.682 K. The optimal axisymmetric chuck could reduce surface temperature differences up to 90 % compared with the conventional spiral chuck.
期刊介绍:
The aim of the Journal of Mechanical Science and Technology is to provide an international forum for the publication and dissemination of original work that contributes to the understanding of the main and related disciplines of mechanical engineering, either empirical or theoretical. The Journal covers the whole spectrum of mechanical engineering, which includes, but is not limited to, Materials and Design Engineering, Production Engineering and Fusion Technology, Dynamics, Vibration and Control, Thermal Engineering and Fluids Engineering.
Manuscripts may fall into several categories including full articles, solicited reviews or commentary, and unsolicited reviews or commentary related to the core of mechanical engineering.