A5033447752- Industrial Vision Systems and Defect Detection
- Advancements in Photolithography Techniques
- Statistical Distribution Estimation and Applications
- Reliability and Maintenance Optimization
- Image and Object Detection Techniques
- Advanced Statistical Process Monitoring
- Remote Sensing and LiDAR Applications
- Integrated Circuits and Semiconductor Failure Analysis
- Software Reliability and Analysis Research
- Manufacturing Process and Optimization
- 3D Surveying and Cultural Heritage
- Fault Detection and Control Systems
- Spectroscopy and Chemometric Analyses
- Bayesian Methods and Mixture Models
- Advanced Statistical Methods and Models
- Gaussian Processes and Bayesian Inference
- Statistical Methods and Bayesian Inference
- Advanced Surface Polishing Techniques
- Neural Networks and Applications
- Image Processing Techniques and Applications
- Advanced Battery Technologies Research
Micron (Singapore)
2016-2020
Micron (United States)
2017
National University of Singapore
2014-2016
The geometric quality of a wafer is an important characteristic in the semiconductor industry. However, it difficult to monitor this during manufacturing process due challenges created by complexity data structure. In article, we propose Additive Gaussian Process (AGP) model approximate standard profile while quantifying deviations from when in-control state. Based on AGP model, two statistical tests are developed determine whether or not newly produced conforming. We have conducted...
In many applications, units from the same population exhibit heterogeneity that they degrade with different rates due to random factors. This article studies how this in degradation influences condition-based maintenance (CBM) policy. Many CBM polices are developed based on gamma process because it is popularly used characterise monotone processes. study, we also model unit's by process. To account for among units' degradation, incorporate a effect parameter Then optimal policy obtained...
In semiconductor manufacturing, various wafer tests are conducted in each stage. The analysis and monitoring of collected testing data plays an important role identifying potential problems improving process yield. There exists three variation sources: 1) lot-to-lot variation; 2) wafer-to-wafer 3) site-to-site variation, which means the measurements cannot be considered independently. However, most existing control charts for quality based on assumption that independently identically...
This article presents a Gaussian process (GP)-based approach to model tunnel's inner surface profile with high frequency sensing data provided by Terrestrial Laser Scanner (TLS). We introduce reading-surface that uniquely determines three-dimensional tunnel in Cartesian coordinate system. transforms the cylindrical two-dimensional profile, hence allowing us GP. To account for errors induced TLS, we take repeated measurements at designed coordinates. apply Taylor approximation extract mean...
With photolithography as the fundamental patterning step in modern nanofabrication process, every wafer within a semiconductor fab will pass through lithographic apparatus multiple times. more than 20,000 sensors producing 700GB of data per day across subsystems, combination light source and provide massive amount information for analytics. This paper outlines how analysis tools techniques that extend insight into traditionally had been considered unmanageably large, known adaptive...
Tunnel profile is an important quality measure for deformation monitoring throughout lifetime of a tunnel. Recently, statistical models such as cylindrical regression have been introduced to model the tunnel with help Terrestrial Laser Scanning (TLS) surveyed point cloud data. However, these cannot capture local variability surface, which monitoring. This paper presents Gaussian process (GP) based approach profile. We introduce reading-surface uniquely determines three-dimensional in...
In the advanced manufacturing, a lot of sensors are used to collect real-time process signals for statistical monitoring. Motivated by complex correlation structures these multi-channel profile signals, this paper proposes monitoring scheme their cross-correlations with help spectral network approaches. particular, we first construct model profiles extracting features based on functional PCA. The topological structure can represent profiles. Then propose monitor using its spectrum...
In addition to lithography process and equipment induced variations, processes like etching, annealing, film deposition planarization exhibit each having their own intrinsic characteristics leaving an effect, a 'fingerprint', on the wafers. With ever tighter requirements for CD overlay, controlling these variations is both increasingly important challenging in advanced integrated circuit (IC) manufacturing. For example, on-product overlay (OPO) requirement future nodes approaching <3nm,...
On Product Overlay (OPO) is a critical budget for advanced lithography. LithoInSight (LIS), an ASML application product, has proven to improve the ability of process control (APC) overlay with accurate fingerprint estimation and optimized scanner correction. It now often used as Process Record (PoR) performing chuck/lot based run-to-run (R2R) in High Volume Manufacturing (HVM) environment. In order further on-product performance given ever-tightening spec. nodes, question how reduce...
This paper proposes a state space model to describe multivariate autocorrelated zero-inflated count series. The extends the classical Poisson distribution into cases but is able impose different zero inflations on dimensions. Combing inflation with log-normal mixture of independent distribution, this allows for flexible cross-correlations multiple counts. Furthermore, By considering zero-inflation parameters as well mean latent variables evolving according models, can capture...