Semiconductor Production Process Research Articles

Intelligent Fire Suppression Devices Based on Microcapsules Linked to Sensor Internet of Things

Most fire spread is caused by the absence of suppression means at the beginning of the fire. This results in the missed golden time. There are various factors that cause initial fires, such as electrical outlets, general distribution circuits, and oil–vapor–gas cluster spaces. In most cases, these places are out of reach of human hands or they lose the initial suppression time when a fire occurs, causing the spread of fire. This study implements an intelligent fire suppression device that connects sensor IoT based on microcapsules to secure initial fire suppression and golden time in the event of a fire in blind spots that cannot be seen by humans or at a time when it is difficult to recognize a fire. The microcapsule is a micro-collection unit that collects Novec 1230 gas generated in the semiconductor production process. The microcapsule is molded into a form with a fire suppression function and, when a fire occurs, the molded body explodes and absorbs ambient oxygen to suppress the fire. The complex-sensor IoT executes smoke and heat detection generated when a fire is suppressed within 10 s, which ensures the reliability of the detector by notifying of the fire and detecting the ignition point through communication linkages such as Ieee 485 and WiFi or LoRa.

Applications of CMOS image sensors: Applications and innovations

As semiconductor production processes continue to advance, CMOS image sensors are becoming increasingly popular and are gradually replacing traditional CCD sensors as the mainstream option in the market. Because CMOS image sensors adopt the standard CMOS semiconductor production process, which provides advantages such as low static power consumption, large noise tolerance, strong anti-interference ability, and fast working speed. This article is going to provide an overview of CMOS image sensors and examine their various applications. To achieve this, this article will provide some background information on CMOS image sensors, including a discussion of their structure, components, and working principles. A comprehensive literature review was conducted to explore the characteristics and benefits of CMOS image sensors in applications such as intelligent surveillance systems (ISS), space, and medical. This paper also discusses recent advances in CMOS image sensor technology, namely backside illumination, global shutter, and 3D imaging, and their impact on various industries. Despite the advantages of CMOS image sensors, they still have some limitations and shortcomings. Therefore, further progress in industrial development is necessary to improve the quality of these products.

Development of a Magnetic Levitation Wafer Handling Robot Transfer System with High-Accuracy and High-Cleanliness: Experimental Evaluation

Magnetic levitation can reduce particulate contamination that occurs during wafer transportation in the semiconductor manufacturing process. This technology radically eliminates contact between the wafer and the transport system, reducing friction, wear, and particle generation. Therefore, it is suitable for achieving high cleanliness in the ultra-fine line-width semiconductor production process and solving the need for particle removal in a vacuum environment. In this study, the roller and linear motion guide components of the wafer transfer system were replaced with a magnetic levitation module, and a robot arm was installed on top to transport a single wafer. A posture controller and a current controller were designed, and test equipment simulating the wafer transfer system was also manufactured and tested. Regarding mover and system identification, a sine sweep test was performed on the motion axis of the five degrees of freedom. Through the obtained system identification, it was possible to design the posture controller more precisely. Moreover, through levitation in standstill experiments and high-speed operation experiments, the wafer transport system can be used to verify dust-free high-speed transport and accurate positioning performance.

Pattern Wafer x/y Auto Align System using Machine Vision

The paper proposes an Automatic Semiconductor Measurement System using Wafer Auto Align using Pattern for semiconductor wafer measurement. The measurement of semiconductors is crucial for the semiconductor industry, and the proposed model aims to improve the semiconductor production automation process. The proposed system consists of three main components: the stage, the vision system, and the pattern alignment algorithm. The stage includes theWafer holder, Ellipsometer, and controller, and plays a critical role in aligning the X and Y axes of the Wafer to 100 mm/s after pattern analysis. The vision system captures highquality images of the Wafer and analyzes the patterns on the Wafer to detect any defects or deviations from the standard. The pattern alignment algorithm uses the information obtained from the vision system to align the Wafer accurately. The Auto align process is fully automated and does not require any user intervention. The process operates in three major steps: selecting the Wafer Recipe, photographing the pattern of the designated recipe, and executing the Auto align. The proposed system offers a comprehensive and automated solution for Wafer alignment and measurement, providing high accuracy and efficiency, while also reducing the risk of errors and improving the semiconductor production process.

Composite Membrane Based on Melamine Sponge and Boehmite Manufactured by Simple and Economical Dip-Coating Method for Fluoride Ion Removal.

The wastewater generated from the semiconductor production process contains a wide range and a large number of harmful substances at high concentrations. Excessive exposure to fluoride can lead to life-threatening effects such as skin necrosis and respiratory damage. Accordingly, a guideline value of fluoride ions in drinking water was 1.5 mg L-1 recommended by the World Health Organization (WHO). Polyvinylidene fluoride (PVDF) has the characteristics of excellent chemical and thermal stability. Boehmite (AlOOH) is a mineral and has been widely used as an adsorbent due to its high surface area and strong adsorption capacity for fluoride ions. It can be densely coated on negatively charged surfaces through electrostatic interaction due to its positively charged surface. In this study, a composite membrane was fabricated by a simple and economical dip coating of a commercial melamine sponge (MS) with PVDF and boehmite to remove fluoride ions from semiconductor wastewater. The prepared MS-PVDF-Boehmite composite membrane showed a high removal efficiency for fluoride ions in both incubation and filtration. By the incubation process, the removal efficiency of fluoride ions was 55% within 10 min and reached 80% after 24 h. In the case of filtration, the removal efficiency was 95.5% by 4 cycles of filtering with a flow rate of 70 mL h-1. In addition, the removal mechanism of fluoride ions on MS-PVDF-Boehmite was also explored by using Langmuir and Freundlich isotherms and kinetic analysis. (R2-1) From the physical, chemical, thermal, morphological, and mechanical analyses of present materials, this study provides an MS-PVDF-Boehmite composite filter material that is suitable for fluoride removal applications due to its simple fabrication process, cost-effectiveness, and high performance.

Using intelligent technology and real-time feedback algorithm to improve manufacturing process in IoT semiconductor industry

To enable the Internet of things, the semiconductor manufacturing process has progressed from the micron to the deep submicron level. Quality improvement is one of the great challenges in wafer fabrication. Computer-integrated manufacturing (CIM) has arisen as a means by which to reduce wafer rework and continuously improve the semiconductor production process. This study uses statistical process control (SPC) and data mining technology to analyze the collected semiconductor process data. A real-time feedback algorithm is employed to ensure that each product lot is manufactured using optimized process parameters. This maximizes production capability, increases the semiconductor yield rate and reduces the cost of manufacturing. This paper focuses on wafer fabrication facilities (often called “fabs,” or “foundries”). The data mining architecture is implemented between CIM and the manufacturing execution system. Association rules and the k-means clustering algorithm are used together with real-time feedback control analysis to extract and analyze each parameter that affects the semiconductor production yield. This combination of real-time feedback and SPC using historical process data allows the system to predict the optimum process parameters for the next lot. The system compensates dynamically to accommodate differences among various machines and products, giving each machine a level of flexibility in manufacturing the product. The proposed semiconductor system can be applied to traditional manufacturing industry process analysis. Our results show how our system can improve the semiconductor manufacturing process in terms of processing capability, yield rate, stability and flexibility, while reducing costs, thus creating a competitive advantage for the wafer fab.

Compensating Misalignment Using Dynamic Random-Effect Control System: A Case of High-Mixed Wafer Fabrication

It is vital to have an exclusive modification in semiconductor production process because of meeting differentiated customer demands in dynamic and competitive global minuscule semiconductor technology market and the highly complex fabrication process. In this paper, we propose a control system based on the dynamic mixed-effect least-square support vector regression (LS-SVR) control system for overlay error compensation with stochastic metrology delay to minimize the misalignment of the patterning process. Moreover, for the stability of the control system in the presence of metrology delay and to deal with nonlinearity among the overlay factors, the novel Lyapunov-based kernel function is merged with the LS-SVR controller. The proposed controller’s operation has been validated and implemented by a major semiconductor manufacturer in Taiwan. The experiments are verified that mixed-effect LS-SVR controller has the higher validity and higher efficiency in comparison with the exponentially weighted moving average (EWMA) and threaded EWMA controllers which had been previously implemented at the company or applied in similar studies. Note to Practitioners —Due to high production complexity in semiconductor manufacturing process, a meticulous and intelligent process control is needed to achieve higher throughput and customer satisfaction. Monitoring a complex system is challenging because the process components and variables operate autonomously and interoperate with other manufacturing segments. This paper proposes a novel run-to-run (R2R) control system to compensate the overlay error during the photolithography process that efficiently deals with the high-mixed manufacturing environment and metrology delay.

Development of Machine Vision Monitoring System for Semiconductor Package Sorter

The sorter working at high speed in semiconductor production process has been a main reason for productivity failure, causing equipment failure and process halt as socket full or full status of the semiconductor package is not monitor in loading and unloading work of the semiconductor package of test socket board. Furthermore, it is necessary to promptly control vacuum to load and unload semiconductor package at high speed, but delicate on/off control error and limitation of engineer's bare eye checking are not free form error to package sorting. Therefore, the present study developed sorter process-focused image (video) processing algorithm and hardware-based MVMS to apply to production lines.

Quantitative assessment of touch-screen panel by nondestructive inspection with three-dimensional real-time display optical coherence tomography

We investigated the use of optical coherence tomography (OCT) to measure several materials immersed in optical adhesives. The effects of variations in the concentration, physical characteristics, and thickness of the materials were studied, and these parameters were found to significantly affect the OCT measurement. The materials were selected for their distinct spectral properties in the infrared region. To ensure reliability, we acquired images using a scanning electron microscope after performing the semiconductor production process. We verified the feasibility of the application of OCT for defect inspection and product verification of touch-screen panels.

The Negative Binomial Exponentially Weighted Moving Average Chart with Estimated Control Limits

The control chart based on the compound Poisson distribution (the negative binomial exponentially weighted moving average (EWMA) chart) has been shown to be more effective than the c‐chart to monitor the wafer nonconformities in semiconductor production process. The performance of the negative binomial EWMA chart is generally evaluated with the assumption that the process parameters are known. However, in many control chart applications, the process parameters are usually unknown and are required to be estimated. For an accurate parameter estimate, a very large sample size may be required, which is seldom available in the applications. This article investigates the effect of parameter estimation on the run length properties of the negative binomial EWMA charts. Using a Markov chain approach, we show that the performance of the negative binomial EWMA chart is affected when parameters are estimated compared with the known‐parameter case. We also provide recommendations regarding phase I sample sizes, smoothing constant and clustering parameter. The sample size must be quite large for the in‐control chart performance to be close to that for the known‐parameter case. Finally, a wafer process example has been used to highlight the practical implications of estimation error and to offer advice to practitioners when constructing/analysing a phase I sample. Copyright © 2013 John Wiley & Sons, Ltd.

A new strategy for defect inspection by the virtual inspection in semiconductor wafer fabrication

The defect of process equipments is a major factor that impairs the yields in the mass production of semiconductor wafer fabrication and it is a main supervision means to use high-resolution defect inspection tools to detect and monitor the defect damage. Due to the high investment costs of these inspection tools and the resulting decrease in the throughput, how to improve the sampling rate is an important issue for the associated inspection strategy. This paper proposes a new concept and implementation of virtual inspection (VI) to enhance the detection and monitoring of defect in semiconductor production process. The underlying theory of the VI concept is that the state variables identifications (SVIDs) of process equipments can reflect the process quality effectively and loyally. The approach of VI is to combine the application of the fault detection and classification (FDC), and the defect library and the re-engineering of inspection procedure to reach the full-scope of strategic objective. VI enables the defect monitoring to enter a new era by promoting the monitoring level of defect inspection from the previous lot-sampling basis to the wafer-sampling level, and hence upgrades the sampling strategy from random-sampling to full and right-sampling. In this study, various typical defect cases are utilized to illustrate how to create VI models and verify the reliability of the proposed approach. Furthermore, a feasible architecture of the VI implementation for mass production in semiconductor factory is presented in the paper.

Using EWMA control schemes for monitoring wafer quality in negative binomial process

The traditional control chart for nonconformities (called C control chart) assumes that process nonconformities follow a Poisson distribution. In actuality, however, the occurrence of nonconformities does not always observe Poisson distribution. For example, when nonconformities of wafers have clustering phenomenon in semiconductor production process, the process control based on Poisson distribution always underestimates the true average nonconformities and process variance. If the compound Poisson process is taken as the basis for process control, the quality feature could be described more accurately. When the process has minor variation, the sensitivity of the exponentially weighted moving average (EWMA) control chart is higher than the C control chart and more accurately reflects the current situation of the process on the control chart. Hence, this study considers Poisson–Gamma compound distribution for the failure mechanism, and takes the Markov chain approach to calculate the average run length produced by the EWMA control chart with different design parameters. Moreover, the EWMA control chart based on Poisson–Gamma compound distribution was constructed and actual data from a wafer plant were employed to illustrate the operation of the model. This study could be useful for detecting minor process variations in wafer plants and improving the process quality.

반도체 공정의 생산성 향상을 위한 실시간 대용량 데이터의 효율적인 저장 기법

반도체 산업이 발전함에 따라 생산 효율을 높이기 위해 무인 자동 생산 공정이 요구되고 있다. 이러한 무인자동화 생산 관리 시스템은 생산성 향상을 위해 생산 공정에서 발생하는 대량의 실시간 데이터 분석 및 관리를 필요로 한다. 따라서 실시간으로 발생하는 대용량 데이터를 저장하기 위한 저장 관리 시스템이 요구된다. 기존의 저장 관리 시스템으로 오라클, MY-SQL, MS-SQL 등의 디스크 기반 DBMS가 있다. 하지만 기존의 디스크 기반 DBMS는 반도체 장비로부터 실시간으로 발생하는 대용량 데이터 처리에 한계가 있다. 본 논문에서는 대용량 데이터를 저비용으로 실시간 저장하기 위해 블록 단위 삽입 트랜잭션을 이용한 압축-합병 저장 기법을 제안한다. 제안 기법은 블록 단위 트랜잭션을 이용하여 실시간 데이터를 빠르게 저장하며 데이터를 압축하고 압축된 데이터를 합병하여 저장하기 때문에 보다 적은 디스크 공간을 사용하여 저장할 수 있다. 따라서 반도체 공정에서 빠르게 발생하는 대용량 데이터를 기존 DBMS보다 빠르게 저장이 가능하고 저장 공간 비용을 감소시킨다. 【Automatic semiconductor manufacturing systems are demanded to improve the efficiency of the semiconductor production process. These systems include the functionalities such as the analysis and management schemes for very large real-time data in order to enhance the productivities. So, it requires the efficient storage management system to store very large real-time data. Traditional database management systems(e.g. Oracle, MY-SQL, MS-SQL) are based on disk. However, previous DBMS's have the limitation on the low storing performance. In this paper, we propose a compress-merge storing method of very large real-time data using insert transaction of a block unit. The proposed method shows better processing performances compare to conventional DBMS's. Also compress-merge method makes it possible that it can store large real-time data on low storage cost. Therefore, the proposed method can be applied to an efficient storage management system in the semiconductor production process.】

Effective tool design of three-rank form as precision removal-process of ITO thin-films

A new effective tool design of three-rank form of electroremoval was present using a precision recycle system offering faster performance in removing the indium-tin-oxide(ITO) thin-films on color filter surface of displays. Higher electric power is not required since the three-rank form tool is adopted as a feeding mode to reduce the response area. The low yield of ITO persists throughout the entire semiconductor production process. By establishing a recycle process of ultra-precise removal of the thin-film nanostructure, defective products in the optoelectronic semiconductors industry can be effectively recycled, decreasing both production costs and pollution. A 5th generation TFT-LCD was used. The design features of the removal processes for the thin-films and the tool design of three-rank form were of major interest. For the precision removal processes, a pulsed current can improve the effect of dreg discharge and contributes to the achievement of a fast workpiece (displays' color filter) feed rate, but raises the current rating. High flow velocity of the electrolyte with a high rotational speed of the tool electrodes elevates the ITO removal effect. A displays' color filter with a fast feed rate is combined with enough electric power to provide highly effective removal. A small thickness of the rank and a small arc angle of the negative-electrode correspond to a higher removal rate for ITO-film. An effective three-rank form negative-electrode provides larger discharge mobility and better removal effect. It only needs a short period of time to remove the ITO easily and cleanly.

Design of Three-Stratum Tool in Indium-Tin-Oxide Removal

A design of three-stratum tool is presented as a machining tool for removing the Indium-tin-oxide (ITO) thin-films from displays' color filter surface of TFT-LCD in electrochemical etching process. The low yield of ITO persists throughout the entire semiconductor production process. For the precision re-moval processes, a narrow width of the three-stratum tool and a short height between the three-stratum tool and the displays' color filter surface provides an effective removal performance. A pulsed current can improve the effect of dreg discharge and contributes to the achievement of a fast workpiece (displays' color filter) feed rate, but raises the current rating. A displays' color filter with a fast feed rate is combined with enough elec-tric power to provide highly effective removal. An effective de-sign of the three-stratum tool and a low-cost recycle processes using the just needs quite short time to make the ITO thin-films remove easily and cleanly.

Vision for industry

Vision systems are used on everything from controlling the semiconductor production process to number plate recognition for the London congestion charge, but lack of appropriate training by universities is seriously damaging future development and application of the technology.

Development of a MeV proton beam irradiation system

A proton beam irradiation system for the application of the MeV class proton beam, such as an implantation for a power semiconductor device and a smart-cut technology for a semiconductor production process, has been developed. This system consists of a negative ion source, an Einzel lens for a low energy beam transport, accelerating tubes, a gas stripper, a Cockroft-Walton high voltage power supply with 1 MV, a vacuum pumping system, and a high pressure insulating gas system. The negative hydrogen ion source is based on TRIUMF's design. Following the tandem accelerator, a pair of magnets is installed for raster scanning of the MeV proton beam to obtain a uniform irradiation pattern on the target. The system is 7 m long from the ion source to the target and is optimized for the proton beam irradiation. The details of the system development will be described.

Local Agglomeration and Global Networks Of the Semiconductor Industry: a Comparative Study of U.S. and Japanese Firms

The objective of this study is to examine the spatial organization of the U.S. and Japanese firms in the semiconductor industry. Our analyses give special consideration to the nature of the activities undertaken in the semiconductor production processes, the nature of the firm organization, the nature of the firm ownership, and the geographical area of analysis. Our approach is essentially diagrammatic in order to incorporate all the above factors. Therefore, unlike past studies, our study places special emphasis on tracing the connections between the whole spatial chain of production activities. The result is that different stages within the semiconductor production process have different geographical features, and that even the same vertically integrated sectors in the semi‐conductor industry that differ by Japanese or U.S. ownership have quite different geo‐graphical organizations.

Use of Dilute HF With Controlled Oxygen for Post Cu CMP Cleans

Wet cleaning of wafers during the semiconductor production process often requires uniform removal of a few nanometers of material. Ideally, a single cleaning chemistry can be found that etches all exposed features at a comparable rate. Etch rates near 1 nm/min are desired for batch process and near 10 nm/min for single-wafer processes. A mixture of 500:1 DHF (dilute HF) with dissolved oxygen controlled near parts-per-million (ppm) levels has been found to meet these requirements for post copper CMP (chemical-mechanical polishing) cleans with exposed SiO2 and Cu metal.

Expansion of an institutional quality control program at a comprehensive cancer center

The defect of process equipments is a major factor that impairs the yields in the mass production of semiconductor wafer fabrication and it is a main supervision means to use high-resolution defect inspection tools to detect and monitor the defect damage. Due to the high investment costs of these inspection tools and the resulting decrease in the throughput, how to improve the sampling rate is an important issue for the associated inspection strategy. This paper proposes a new concept and implementation of virtual inspection (VI) to enhance the detection and monitoring of defect in semiconductor production process. The underlying theory of the VI concept is that the state variables identifications (SVIDs) of process equipments can reflect the process quality effectively and loyally. The approach of VI is to combine the application of the fault detection and classification (FDC), and the defect library and the re-engineering of inspection procedure to reach the full-scope of strategic objective. VI enables the defect monitoring to enter a new era by promoting the monitoring level of defect inspection from the previous lot-sampling basis to the wafer-sampling level, and hence upgrades the sampling strategy from random-sampling to full and right-sampling. In this study, various typical defect cases are utilized to illustrate how to create VI models and verify the reliability of the proposed approach. Furthermore, a feasible architecture of the VI implementation for mass production in semiconductor factory is presented in the paper.