TFT-LCD Manufacturing Process Research Articles

Sustainable scheduling of TFT-LCD cell production: A hybrid dispatching rule and two-phase genetic algorithm

TFT-LCD manufacturing process involves Array, Color Filter (CF), Cell, and Module. The Cell process is pivotal in the TFT-LCD production supply chain; it bridges the front-end (Array and CF) and back-end (Module), maintaining a balance of production capacities. Supply from the front-end is transmitted to the back-end, ensuring prompt responsiveness to customer demands. As awareness of environmental conservation grows, implementing sustainable development in the TFT-LCD manufacturing industry has become crucial. Specifically, reducing the machine setup frequency in TFT-LCD scheduling decreases energy consumption during machine operation and wait times and prolongs equipment lifespan by minimizing wear from repeated shutdowns. To tackle the intricate scheduling challenges within TFT-LCD production, this study proposes an intelligent, sustainable scheduling approach that employs a rolling dispatching and line balancing mechanism and a two-phase genetic algorithm (HDTPGA) for Cell scheduling. The goal is to minimize makespan considering product diversity, production constraints, work-in-process balancing, and machine setup frequency. This holistic approach promotes energy-efficient and sustainable manufacturing practices. According to the empirical study, the proposed HDTPGA reduces the makespan by approximately 10% compared to the baseline. Additionally, it reduces the average daily setup frequency of bottleneck stages (ODF and CCT) in the Cell process by approximately 68.25% and 66.25%, respectively. The main contribution of this paper is to propose an intelligent scheduling algorithm to optimize Cell production scheduling in practice. The HDTPGA achieves equilibrium between front-end and back-end production, utilizing an efficient line change mechanism to reduce energy consumption. The enhancement in efficiency not only restricts material waste but also reduces the environmental impact, enabling manufacturers to adopt green production practices and promoting a transition of the entire panel industry toward sustainability.

A Study on Oxidation of Tetramethylammonium Hydroxide (TMAH) using UV/Persulfate

Objective : In order to efficiently remove TMAH from the wastewater generated by the TFT-LCD manufacturing process, the oxidation of TMAH was tested by applying an UV/persulfate. The optimum reaction conditions for high concentration TMAH oxidation were investigated by evaluating and comparing the removal efficiency according to the factors affecting TMAH oxidative degradation.Methods : In this study, TMAH was decomposed by sulfate radical (SO4-∙) and hydroxyl radical (OH∙) generated from persulfate activated by UV. Factors affecting on the treatment efficiency were try to be optimized by comparing and evaluating the removal efficiency depending on the initial pH, oxidant concentration, and initial TMAH concentration.Results and Discussion : Depending on initial pH (2, 7, 12), persulfate addition (0, 50, 100, 150, 200 mM), initial TMAH concentration (100, 300, 500, 700 mg/L) degradation rates of TMAH were compared. When UV/persulfate was applied, the removal efficiency of TMAH was close to 90% regardless of the initial pH and, at initial pH 12, was the highest with 89%. It was confirmed that the generation pattern of intermediate formed were different depending on the initial pH. When the oxidizing agent was not added, there was little change in TMAH concentration. The removal efficiency was highest when 100 mM persulfate was added. However the efficiency was rather low when 150 mM persulfate was added. When the initial TMAH concentration was 100 mg/L, it was decreased within 150 minutes. As the initial concentration increased, the removal efficiency and reaction rate constant decreased.Conclusions : As a results, during the oxidation of 750 mg/L TMAH by using UV/persulfate, the removal efficiency was highest with initial pH 12 and 100 mM of persulfate addition.

Conductive particle detection via deep learning for ACF bonding in TFT-LCD manufacturing

The inspection of conductive particles after Anisotropic Conductive Film (ACF) bonding is a common and crucial step in the TFT-LCD manufacturing process since the number of high-quality conductive particles is a key indicator of ACF bonding quality. However, manual inspection under microscope is a time-consuming, tedious, and error-prone. Therefore, there is an urgent demand in industry for the automatic conductive particle inspection system. It is challenging for automatic conductive particle quality inspection due to the existence of complex background noise and diversified particle appearance, including shape, size, clustering and overlapping, etc. As a result, it lacks an effective automatic detection method to handle all the complex particle patterns. In this paper, we propose a U-shaped deep residual neural network (i.e., U-ResNet), which can learn features of particle from massively labeled data. The experimental results show that the proposed method achieves high detection accuracy and recall rate, which exceedingly outperforms the previous work. Also, our system is very efficient and can work in real time.

Surface damage behavior of polyurethane O-rings in automated material handling system for glass panels

Automated material handling systems (AMHSs) are widely utilized in general manufacturing processes. The precision motion control and wear resistance of rolling parts of an AMHS are important factors to ensure sufficient reliability of the final product. Polyurethanes are widely used in the manufacturing process due to their superior damage resistance and adequate rolling friction properties. In this work, friction and wear behaviors of polyurethane O-ring rollers sliding against a glass plate specimen were investigated with respect to sliding speed, temperature and relative humidity. A pin-on-reciprocating sample tribotester in an environmental chamber was used to assess the friction and wear properties of the polyurethane O-rings. It was found that the wear resistance increased for higher sliding speed, higher temperature, and lower relative humidity conditions. The results of this work are expected to provide optimized O-ring transfer equipment operating conditions to improve the productivity of the TFT-LCD manufacturing process.

Demerit-Fuzzy Rating Mechanism and Monitoring Chart

The relative magnitude of weights for defects has a substantial impact on the performance of attribute control charts. Apparently, the current demerit-chart approach is superior than the c-chart scheme, because it imposes different precise-weights on distinct types of nonconformities, enabling more severe defects to disclose the problems existing in the manufacturing or service processes. However, this crisp-weighting defect assignment, assuming defects are of equal degree of severity when classified into the same defect class, may be so subjective that it leads to the chart somewhat restricted in widespread applications. Since in many cases the severity of each defect is evaluated from practitioners' visual inspection on the key quality characteristics of products or services, when each defect is classified into one of several mutually-exclusive linguistic classes, a fuzzy-weighting defect assignment that represents a degree of seriousness of defects should be allotted in accordance. Therefore, in this paper a demerit-fuzzy rating mechanism and monitoring chart is proposed. We first incorporate a fuzzy-linguistic weight in response to the severe degree of defects. Then, we apply the resolution identity property in construction of fuzzy control limits, and further develop a new fuzzy ranking method in differentiation of the underlying process condition. Finally, the proposed fuzzy-demerit chart is elucidated by an application of TFT-LCD manufacturing processes for monitoring their LCD Mura-nonconformities conditions.

Optimal Yield Rate in ACF Cutting Process of TFT-LCD Module Using Orthogonal Particle Swarm Optimization Based on Response Surface Design

Anisotropic Conductive Film (ACF) is essential material in LCM (Liquid Crystal Module) process. It is used in bondingprocess to make the driving circuit conductive. Because the price of TFT-LCD is getting lower than before in recentyears, the ACF has relatively higher cost ratio. The conventional long bar ACF cutting unit is changed into short barACF cutting unit in new bonding technology. However, the new type machine was not optimized in process controland mechanical design. Therefore, the failure rate of new ACF cutting process is much higher than the one of theconventional process. This wastes the ACF material and rework cost is considerably large. How to make themanufacturing cost down effectively and promote the product quality is the main issue to maintain competitioncapability for the product. Therefore, the orthogonal particle swarm optimization (OPSO) is used to analyze theoptimal design problem. The ACF cutting yield rate is selected to be objective function for optimization. The qualitycharacteristic function for yield rate is used in orthogonal particle swarm optimization. Three control factors such asplasma clean speed, ACF peeling speed and ACF cutter spring setting are selected to study the effect of the yieldrate. Results show that the proposed method can provide good optimal solution to improve the ACF cutting processfor TFTLCD manufacturing process.

Applying Residual Control Charts to Identify the False Alarms in a TFT-LCD Manufacturing Process

Statistical Process Control (SPC) is widely applied to monitor and improve highly integrated and automated manufacturing processes. Adopting proper SPC charts and corresponding detection mechanisms is crucial for a TFT-LCD manufacturing process. This study conducts an empirical study of highly complex TFT-LCD manufacturing processes to identify the most suitable SPC method. The TFT-LCD manufacturing process is generally divided into three main procedures, namely Array Engineering to create the TFT array, Cell Engineering to join the TFT array, liquid crystal and color filter together, and Module Engineering to integrate PCB and semiconductor chips into final products. The crucial step in Cell Enginee ring is injecting the liquid crystal into the layer between the TFT array and color filter substrates and the thickness of the layer is the ma in control target. Applying traditional Shewhart and EWMA control charts to real TFT-LCD manufacturing data reveals a significan t false alarm rate, and these false alarms can adversely impact manufacturing efficiency. Based on time series analysis, this study prop oses a residual control chart using an AR(1) model to avoid false alarms that could obstruct TFT-LCD manufacturing flow. The res ults of the proposed approach provide a useful guideline for improving the TFT-LCD manufacturing.

Supplier Selection for Multiple-Characteristics Processes with One-Sided Specifications

In this paper, we consider the supplier selection problem for normally distributed processes with multiple independent characteristics based on process capability index CpU . A two-phase testing procedure based on the quotient of two statistics is proposed to deal with the problem. We obtain the sampling distribution and the probability density function of the quotient. Several tables of the critical values for the testing procedure and decision making are provided. The required sample sizes for various capability requirements, magnitude of difference of two suppliers, and given power are also presented. A real application on TFT-LCD manufacturing processes is presented to demonstrate the efficacy of the proposed method.

A Dynamic Virtual Metrology Scheme for TFT-LCD Manufacturing Processes

A Dynamic Virtual Metrology Scheme for TFT-LCD Manufacturing Processes

TFT-LCD取向层表面的针孔缺陷分析

The pinholes on the surface of alignment layer was studied, which formed during the TFT-LCD manufacturing process and caused defects of the products. Herein, a vitally typical defect, black spot, was analyzed via FIB, SEM and OMS. The analysis results of statistical software BO (Business Objects) show that the pinhole is the main cause of the blackspot. Based on theoretical analysis and further experimental results, it is found that the hydrodynamic in stability of the solution may lead to the pinholes on the alignment layer surface, and the precure time of the alignment film solution is significantly responsible for hydrodynamic instability. It is noteworthy that the instability needs times to grow full enoughand then to influence the film structure. Therefore, the pinholes on the alignment layer surface will be reduced or eliminated if the precure time is less than or equal to that time.

Optimal Improvement on Cutting Yield Rate in ACF Attach Process of TFT-LCD Module Using Response Surface Method

In TFT-LCD manufacturing process, the ACF is an essential material. To make the driving circuit conductive, the ACF attach process is used in bonding process. Since the total manufacturing cost becomes lower year by year, the ACF material occupies a great deal of manufacturing cost. The boding technology has been changed from the conventional long bar type into short bar type to save the material usage. The parameter setting of the short bar type machine was not initially optimized. The NG rate of short bar type ACF attach process is higher as compared to the long bar type. The rework cost and material cost may increase in the short bar type process. Therefore, the parameter optimization for the associated short bar type ACF attach process becomes an essential problem. The response surface method is adopted to model the problem. The yield rate is selected as objective function for study. In the analysis of response surface method, the plasma clean speed, ACF peeling speed and ACF cutter spring setting are selected three key factors for discussion. Results reveal that the yield rate can be improved up to 99.35%, which is very helpful to improve the manufacturing process.

A Processing Quality Prognostics Scheme for Plasma Sputtering in TFT-LCD Manufacturing

A novel quality prognostics scheme (QPS) for plasma sputtering in TFT-LCD manufacturing processes is proposed. The QPS consists of a conjecture model and a prediction model. The conjecture model can use processing parameters and sensor data to estimate the processing quality (sputtering thickness) in real time. This conjecture function is also called virtual metrology. On the other hand, the prediction model is capable of predicting the processing quality of the next-lot glasses. Neural networks and weighted moving average algorithms are applied to construct the QPS. In particular, a reliance index is developed such that online evaluation of whether the conjecture results of the QPS are trustworthy or not is possible. For increasing the accuracy of the QPS, a self-searching mechanism is designed to automatically search the best set of parameters and functions used by the conjecture and prediction algorithms for cases that the processing properties vary or the recipe changes. Also, an auto-adjusting mechanism is developed for tuning the system parameters of the QPS and bringing the conjecture accuracy within an acceptable bound. Thorough tests using normal and abnormal processing data on one set of plasma sputtering equipment in a TFT-LCD plant show that the values of the mean absolute percentage error of both the conjecture and the prediction results are less than 2%, which validates the effectiveness of the proposed QPS.

대면적 TFT-LCD 유리기판 이송용 복합재료 로봇 손 개발에 관한 연구

A robot hand is used to transport the glass substrate in TFT-LCD manufacturing process. Carbon/epoxy composite is one of the best materials for this kind of robot hand application, due to their lightweight, high stiffness, and good damping characteristics. Major requirement of the robot hand is given as allowable deflection under weight loading of glass substrate and robot hand itself. In this thesis, a carbon/epoxy robot hand was analyzed using finite element method and beam theory to determine the deflection of the hand under the loading that is equivalent to actual weight. Because natural frequency is one of the major interests in robot hand design for TFT-LCD manufacturing process, modal analysis is also conducted using finite element method and beam theory. A robot hand was manufactured, and actual deflection and natural frequency were measured to verify the analysis results and compliance to requirement. The test results showed good agreement with analysis results.