Search query: plasma etching OES

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abstract: For plasma etching process, developing efficient real time fault detection systems is an active research area of semiconductor manufacturing, especially the systems using Optical Emission Spectroscopy(OES) data. Besides, as a typical multiphase process, it is promising to apply multiphase methods in the OES fault detection system. However, the process drifts existing in the system will lead to severe drifts in time direction and cause model mismatch issue when applying the multiphase methods. To cope with these problems, a real time fault detection system for multiphase plasma etching using OES, two step division and change stage alignment method is proposed in this paper. By capturing changes in process, a two step division method divides the process into stationary phases and transition phases. To better overcome the drift problem, change stage in transition phase is further aligned before MPCA modeling and online monitoring. Case studies have shown that the proposed system is more reliable and sensitive comparing to the reference model and can better overcome the model mismatch problem.
author_names: Jiayang Ren

Dong Ni
title: Real time Fault Detection System for Multiphase Plasma Etching Process using OES, Two Step Division and Change Stage Alignment Method
venue: 2019 Chinese Automation Congress (CAC)
year: 2019

abstract: As the technology node shrinks and shifts towards complex architectures, accurate control of automated semiconductor manufacturing processes, particularly plasma etching, is crucial in yield, cost, and semiconductor performance. However, current endpoint detection (EPD) methods relying on the experience of skilled engineers result in process variations and even errors. This paper proposes an enhanced optimal EPD in the plasma etching process based on a convolutional neural network (CNN) The proposed approach performs feature extraction on the spectral data obtained by optical emission spectroscopy (OES) and successfully predicts optimal EPD time. For the purpose of comparison, the support vector machine (SVM) classifier and the Adaboost Ensemble classifier are also investigated; the CNN based model demonstrates better performance than the two models.
author_names: Bobae Kim

Sungbin Im

Geonwook Yoo
title: Performance Evaluation of CNN Based End Point Detection Using In Situ Plasma Etching Data
year: 2020

abstract: In this study, the Gaussian mixture model (GMM) was modified and implemented to determine the real time endpoint of SiO2 plasma etching using optical emission spectrum analysis. Optical emission spectroscopy (OES) signals were collected from the SiO2 plasma etching processes, and the modified GMM was applied to SiO2 etching with relative areas of 8.0, 4.0, and 1.0 Consequently, the sensitivity of OES signals was improved by ~5.5 times, and the sensitivity factor of the modified GMM was increased by approximately two times, compared with those of the modified K means cluster analysis (another clustering technique) In addition, 60 peaks related to the reactants were selected out of 6144 signals to improve the sensitivity of the modified GMM with full spectrum wavelengths. The modified GMM analysis using the 60 reactant related peaks exhibited a higher sensitivity ~1.4 times) than that with 6144 full spectrum OES signals. Thus, the modified GMM can be a suitable and effective clustering technique for etching endpoint detection.
author_names: Sangin Lee

Haegyu Jang

Yongjae Kim

Sun Jung Kim

Heeyeop Chae
title: Sensitivity Enhancement of SiO2 Plasma Etching Endpoint Detection Using Modified Gaussian Mixture Model
venue: IEEE Transactions on Semiconductor Manufacturing
year: 2020

abstract: The semiconductor industry has played a crucial role in societal development over the past several decades. Plasma etching is a key processing step employed in Integrated Circuit (IC) fabrication. In order to improve product yield, Optical Emission Spectroscopy (OES) is widely used to monitor the etching process. OES generates high dimensional data, which has a large information capacity but also has significant information redundancy. Based on plasma OES characteristics, two novel data analysis methods are proposed in this thesis: the Internal Information Redundancy Reduction (IIRR) method for dimension and redundancy reduction and Similarity Ratio Analysis (SRA) for fault detection. By identifying peak wavelength emissions and the correlative relationships between them, IIRR outputs a subset of the original variables. Data dimensionality is reduced significantly by IIRR with minimal information loss. The SRA method is intended for early stage faultdetection in plasma etching processes using real time OES data as input. The SRA method can help to realise a highly precise control system by detecting abnormal etch rate faults in real time during an etching process, so less energy and materials will be wasted by faulty processing. Generally, previous research on OES measurements of plasma etching has largely focused on particular target applications and has used methods that rely on transforming the original data into an abstract variable space. In contrast, our approach operates directly in the original variable space allowing a more direct and easier interpretation of the dimension reduced data.
author_names: Jie Yang
title: Multivariable OES data analysis for semiconductor plasma etching process
year: 2014

abstract: Abstract This work presents a redeposition free process to etch silicon by CF4 plasma in a modified microwave oven reactor operated in a medium vacuum process regime (25 to 1 x 10 3 Torr) that only uses a mechanical pump which is introduced at a lower cost compared to the ICP etching system. In order to achieve the capability of the etching process provided by this system, experimental trials were conducted by varying the microwave power in the range of 360 1200 W, gas flow rate 30 90 mL/min and bias voltage at the substrate holder 100 V to 300 V. Plasma species present in the discharge were also monitored by optical emission spectroscopy (OES) for a better understanding of the mechanism of the etching process. The etched sidewalls were observed by scanning electron microscope (SEM) the etched roughness was measured by atomic force microscope (AFM) and the etched depths were measured by a stylus profiling technique.
author_names: Chupong Pakpum

Dheerawan Boonyawan
title: Redeposition free of silicon etching by CF4 microwave plasma in a medium vacuum process regime
year: 2020

abstract: Fault detection was carried out in a etcher of capacitive coupled plasma with OES (Optical Emission Spectroscopy) and impedance by VI probe that are widely used for process control and monitoring at semiconductor industry. The experiment was operated at conventional Ar and Fluorocarbon plasma with variable change such as pressure and addition of N2 and O2 to assume atmospheric leak, RF power and pressure that are highly possible to impact wafer yield during wafer process, in order to observe OES and VI Probe signals. The sensitivity change on OES and Impedance by VI probe was analyzed by statistical method including PCA to determine healthy of process. The main goal of this study is to find feasibility and limitation of OES and Impedances for fault detection by shift of plasma characteristics and to enhance capability of fault detection using PCA.
author_names: Sanghyuk Choi

Haegyu Jang

Heeyeop Chae
title: Fault Detection of Plasma Etching Processes with OES and Impedance at CCP Etcher
year: 2012

abstract: Optical Emission Spectra (OES) is a widely used signal in plasm etching. In this paper, an OES structural feature based fault detection method is proposed. Firstly, a template of normal OES curves is extracted via non negative matrix factorization. Then singular points of the curves are detected by local matching based on the template. The magnitude and occurrence time of these singular points form a structural feature vector, which is a quantitative and simplified description of the curve's shape. Lastly, one class SVM is introduced for generate a fault detection model based on structural feature vectors from normal OES curves. Experiments on an industrial benchmark dataset show that the proposed method is effective.
author_names: Lihui Zhao

Huangang Wang

Wenli Xu
title: OES structural feature based fault detection method for plasma etching
venue: 2012 International Conference on Systems and Informatics (ICSAI2012)
year: 2012

abstract: Abstract Surface texturing of a carbon based thin film is the critical technology in the development of functional surface for many kinds of sensors. This study explored the possibilities of processing the carbon film's surface by means of plasma etching to produce micro pillars. Circular dots with a diameter of 25 mm, 50 mm, and 100 mm were printed on a thick carbon film. A high density oxygen plasma was generated by a combination of RF and DC power in a vacuum chamber. The high density plasma was applied onto the surface of a diamond like carbon film. The printed pattern serves as a mask like in the lithography technique. The oxidation reaction was expected on the exposed surface, i.e. the area surrounded the dots. The results show the oxidation effectively removed the carbon on the unmasked area producing 3D circular patterns. The plasma processing, which was carried out for 2 h, was monitored and diagnosed using optical emission spectroscopy (OES) The oxidation was controlled by atomic oxygen which was the dominant species observed in the plasma. The removal (etching) rate was 9 mm/h with 91% 98% and 99% pattern accuracy related to the larger diameter studied in this work. Observations using a Raman spectroscopy confirmed that the printed mask effectively protects the DLC from the etching process and other indirect processes.
author_names: J D H Dionysius Santjojo

W Sukma Fitriani

P Setyawan Sakti
title: Fabrication of Micro Pillar by plasma etching texturing of Carbon Based thin film
year: 2021

abstract: In this study, we evaluate the defects and charges caused by the ultraviolet (UV)/vacuum ultraviolet (VUV) irradiation in the high k/metal gate stack structure, especially in HfO2 layer and at Si/HfO2 interface. First, we measured the photons irradiating to the surface in the neutral beam etching (NBE) system and in the conventional inductively coupled plasma (ICP) system through optical emission spectroscopy (OES) respectively. By using this method, we evaluate the ability of reducing UV/VUV irradiation damage in the NBE system. As a result, photon intensity detected in the ICP system shows larger magnitude as compared to the NBE system, which indicates the UV/VUV irradiation is more severe in the ICP system. Moreover, in order to understand the twisting of electrical characteristics caused by UV/VUV irradiation, we set the prefabricated metal oxide semiconductor (MOS) capacitors in both systems to absorb the irradiation of UV/VUV photons respectively. The electrical characteristics of the etched MOS capacitors and its related plasma induced damage model are discussed. The result of the devices exposed in the ICP system reveals a greater electrical characteristics shift compared to the devices in NBE such as the interface trap density (Dit) in case of NBE is 3.55621x1012 cm 2eV 1 and in case of ICP is higher i.e. 4.19961x1012 cm 2eV 1.
author_names: Si-Qi Zeng

K C Chuang

Ashish Kumar

Wen-Hsi Lee
title: Influence of Plasma Ultraviolet/Vacuum Ultraviolet Irradiation Damage on Silicon Metal Oxide Semiconductor Capacitor During Etching.
venue: Journal of nanoscience and nanotechnology
year: 2021

abstract: Abstract Theendpointdetection(EPD)isthemostimportanttechniqueinplasmaetchingprocess.Inplasmaetchingprocess,theOpticalEmissionSpectroscopy(OES)isusuallyusedtoanalyzeplasmareaction.AndPlasmaImpedanceMonitoring(PIM)systemisusedtomeasurethevoltage,current,power,andloadimpedanceofthesuppliedRFpowerduringplasmaprocess.Inthispaper,anewdecisionmakingalgorithmisproposedtoimprovetheperformanceofEPDinSiOxsinglelayerplasmaetching.Toenhancetheaccuracyoftheendpointdetection,bothOESdataandPIMdataareutilizedandanewlyproposeddecisionmakingalgorithmisapplied.Theproposedmethodsuccessfullydetectedendpointofsiliconoxideplasmaetching. yo yag peulrajeumasiggaggongjeongeseosiggagjongryojeomgeomculeunjungyohanyosoida.OpticalEmissionSpectroscopy(OES)neunpeulrajeumabaneungeulbunseoghaneundesayonghanda.geurigoPlasmaImpedanceMonitoring(PIM)eunpeulrajeumagongjeongjungeRFpowereyihanvoltage,current,power,impedancereulbunseoghaneundesayonghanda.bonnonmuneseoneunsaerojeanhaneunyisagyeoljeongalgorijeumeuliyonghayeosinglelayersanhwamagpeulrajeumasiggageseosiggagjongryojeomgeomculyiseongneungeulhyangsangsikineungeoseuljeanhanda.siggagjongryojeomgeomculyijeonghwagdoreulnopigiwihaeOESdeiteowaPIMdeiteodeuleulyisagyeoljeongalgorijeumemodujeogyonghayeosayonghanda.jeandoenbangbeobeunSiOxpeulrajeumasiggageseosiggagjongryojeomeuljeonghwaghagegeomculhanda.Keywords:EndpointDetection(EPD),DecisionMakingAlgorithm,OpticalEmissionSpectroscopy(OES),PlasmaImpedanceMonitoring(PIM),HiddenMarkovModel(HMM)ISSN: 1226 7244 (Print)ISSN: 2288 243X (Online)nonmunbeonho 16 01 02
author_names: Ho-Taek Noh

Young-Kook Park

Seung-Soo Han
title: Real Time Endpoint Detection in Plasma Etching Using Decision Making Algorithm
year: 2016