{"title":"Anomaly Detection for Semiconductor Tools Using Stacked Autoencoder Learning","authors":"Da-Yin Liao, Chieh-Yu Chen, Wen-Pao Tsai, Hsuan-Tseng Chen, Yao-Tsu Wu, Shi-Chung Chang","doi":"10.1109/ISSM.2018.8651179","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651179","url":null,"abstract":"Anomaly detection for semiconductor tools deals with the problems of finding patterns in process and equipment data that do not conform to expected behaviors. Due to the complexity and unknown correlation of data, machine learning is promising for anomaly detection for semiconductor tools. This paper proposes a Stacked Autoencoder Learning for Anomaly Detection (SALAD) framework that enables anomaly detection in realtime by using a multidimensional time-frequency analysis of sensory data from fab tools. We adopt the Chemical Vapor Deposition (CVD) tool as our study vehicle to demonstrate the feasibility and effectiveness of the developed SALAD framework for anomaly detection of semiconductor tools.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126166351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Precise Positioning System and Potential Application in a “SMART Fab”","authors":"Chih Ming Chan","doi":"10.1109/ISSM.2018.8651178","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651178","url":null,"abstract":"In recent years, the “SMART Factory” concept is becoming common in the wafer fab industry. A truly “SMART Fab” has all the production systems connected and integrated real-time with automated material handling system to optimize all production resources. In this paper, the concept of adopting a precise positioning system in a wafer fab is being discussed. The functions of this positioning system and how it fits into the “SMART Fab” vision will be shared.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127801980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Process, Products and Machine Control Chart Application in Semiconductors","authors":"C. J. Wu, J. Wei","doi":"10.1109/ISSM.2018.8651131","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651131","url":null,"abstract":"For foundry factories, the different products have their respective spec in foundry factories, so we standardize it and monitor the process performance by multi-process, multi-products and multi-machine. The standardized control chart can solve the control problems of Shewhart control chart in high-mix and low-volume products, and combine with different products, machines, and process layers. It can also be used in LtL/WtW/WiW to get the variations of these sources immediately.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126313655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ang Kian Huat, J. Yap, Ning Ning, Tan Siew Fen, Shakar Govindasamy Mani, Myla Terredano
{"title":"Smart Sampling Methodology for Yield Defect Inspection in a 200mm Foundry Wafer Fab","authors":"Ang Kian Huat, J. Yap, Ning Ning, Tan Siew Fen, Shakar Govindasamy Mani, Myla Terredano","doi":"10.1109/ISSM.2018.8651141","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651141","url":null,"abstract":"In Semiconductor Manufacturing, inline Inspection monitoring by Brightfield and Darkfield scan tool platform is a 2nd line of defence to detect abnormal events to prevent defectivity escape to Wafer Sort or Assembly Test. Early detection and good process tool coverage are essential to the quality of wafers. These have to be balanced with competitive cycle time and cost. There are many newer scan tool, software and manufacturing systems available today that can optimize this sampling monitoring. As a legacy 200mm foundry wafer fab, system upgrade may not be feasible or can be expensive. As a result, an innovative solution had to be developed in order to stay relevant in the semiconductor industry. This paper introduces an inline inspection sampling Artificial Intelligent (AI) methodology to ensure maximum process tool scan coverage without additional CAPEX cost - getting more out from the same capacity; getting more coverage with same scan capacity and improve line of defence.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121855962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yusuke Suzuki, S. Iwashita, Toshiki Sato, Hitoshi Yonemichi, Hironori Moki, T. Moriya
{"title":"Machine Learning Approaches for Process Optimization","authors":"Yusuke Suzuki, S. Iwashita, Toshiki Sato, Hitoshi Yonemichi, Hironori Moki, T. Moriya","doi":"10.1109/ISSM.2018.8651142","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651142","url":null,"abstract":"We have optimized semiconductor manufacturing processes by machine learning (ML) approaches. The optimization of the nonuniformity of plasma enhanced atomic layer deposition (PEALD) film thickness, the PEALD film stress, the carbon etching profile and the PEALD film thickness profile have been successfully achieved the targets. In some cases (stress and thickness nonuniformity optimization), the ML approach is found to be more powerful than the knowledgeable engineers. The authors showed the effectiveness of ML approach for the semiconductor manufacturing processes.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126174007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Hamada, K. Nagashima, Naoki Kanda, N. Sato, Kuniaki Takeda, Junya Kawano
{"title":"Super-multipoint thickness measurement technology using optical macro inspection system","authors":"T. Hamada, K. Nagashima, Naoki Kanda, N. Sato, Kuniaki Takeda, Junya Kawano","doi":"10.1109/ISSM.2018.8651139","DOIUrl":"https://doi.org/10.1109/ISSM.2018.8651139","url":null,"abstract":"In this report, a new technology of entire wafer surface film thickness measurement is explained. The technology provides an extra-fine map of entire wafer surface using the data of about 440,000 measurement points. We show the benefit of having an extremely large number of measurement points for detecting local film thickness characteristics. This “super-multipoint thickness measurement technology” is based on the use of an optical macro inspection system, and it enables more precise film deposition tool management.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125179971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Tabuchi, K. Bando, S. Kondo, H. Tomita, E. Shiobara, H. Hayashi, H. Kato, Y. Matsuura, A. Nakamura, K. Kondo
{"title":"Real Time Measurement of Exact Size and Refractive Index of Particles in Liquid by Flow Particle Tracking Method","authors":"T. Tabuchi, K. Bando, S. Kondo, H. Tomita, E. Shiobara, H. Hayashi, H. Kato, Y. Matsuura, A. Nakamura, K. Kondo","doi":"10.1109/issm.2018.8651167","DOIUrl":"https://doi.org/10.1109/issm.2018.8651167","url":null,"abstract":"It is known that particle size obtained from the Brownian motion of a particle is called the diffusion coefficient equivalent size (DCES) and is close to the geometric size independent of the physical properties of particle. This paper describes that we succeeded in measurement of particle size and the number concentration of particles by a new instrument that measures the displacement of particles by Brownian motion except the influence of flow field in real time using the flow particle tracking (FPT) method. Furthermore, we succeeded in evaluation of refractive index of particles by simultaneous measurement of DCES and light scattering intensity of particles.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124360952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of underfill materials for the latest package","authors":"O. Suzuki, T. Enomoto, K. Kotaka","doi":"10.1109/issm.2018.8651155","DOIUrl":"https://doi.org/10.1109/issm.2018.8651155","url":null,"abstract":"In this paper, penetration capability and stress behavior of capillary underfill (CUF) is discussed. The constituent materials of the CUF characterize both the liquid state and the solid state of CUF. Depending on the size of clearance gap, filler size must be optimized. The mechanism of stress transmission by CUF is explained.","PeriodicalId":262428,"journal":{"name":"2018 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122382590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}