Application Example TFT-LCD

LCD (liquid crystal display) is the technology used for displays in notebook and other smaller computers. Like light-emitting diode (LED) and gas-plasma technologies, LCDs allow displays to be thinner than cathode ray tube (CRT) technology. LCDs consume much less power than LED and gas-display displays because they work on the principle of blocking light rather than emitting it.

To achieve the color on a pixel in an LCD panel, a current is applied to the crystals at that pixel to change the state of the crystals. Response times refer to the amount of time it takes for the crystals in the panel to move from an on to off state. A rising response time refers to the amount of time it takes to turn on the crystals and the falling time is the amount of time it takes for the crystals to move from an on to off state. Rising times tend to be very fast on LCDs, but the falling time tends to be much slower. This tends to cause a slight ghosting effect on bright moving images on black backgrounds. Simply to say, it’s the time takes for pixels to come up (become lit) and come down (become dark). The lower the response time, the less of a ghosting effect there will be on the screen. The electronic field effect of the liquid crystal is displayed in Figure 1, when the electronic field which between the electrode started to driving, it will attract to the electronic field works to make the liquid crystal turn its direction. And the optics effects will be produced. The picture tube theorem is showed in the Figure 2, An LCD is made with either a passive matrix or an active matrix display grid. The active matrix LCD is also known as a thin film transistor (TFT) display. The passive matrix LCD has a grid of conductors with pixels located at each intersection in the grid. A current is sent across two conductors on the grid to control the light for any pixel. An active matrix has a transistor located at each pixel intersection, requiring less current to control the luminance of a pixel.The current in an active matrix display can be switched on and off more frequently, improving the screen refresh time.

Turn off the electronic field Turn on the electronic field

LC

Electrode Electrode

Electrode Electrode LC

Figure 1. The electronic field effect of the liquid crystal

Figure 2. The picture tube theorem

To illustrate which has better process capability between the two suppliers, we presented a case study on TFT-LCD manufacturing processes, which located on the Science-Based Industrial Park in Taiwan. These factories manufacture carious types of the LCD. For a particular model of the TFT-LCD investigated, the upper specification limit, USL of the response time is set to 20ms（ms，

milliseconds）. If the characteristic data does not fall under the USL, the performance of the TFT-LCD will be discounted. We will use the software

“LaCie calibration probe” to do the variable set of the LCD, then calculating the time takes for pixels to come up and come down.

5.1.1 Data Analysis and Supplier Selection

Before doing the data analysis, we set two factors first, (1) the minimum of Cpu (2) the minimal difference of C_pu between these two suppliers,δ =C_pu2−C_pu1, then we can know how many sample sizes we should sample with determined power by the selection method. In this example, we set the minimum of C_pu=1.00 and the minimal difference of C _pu between these two suppliers, δ =0.25, the determined selection power = 0.95, then we can know we have to take 257 samples by checking Table 1. Then we present the data drew from these two suppliers in Table. In order to affirm these data as normal distributed, we show the distribution of these data in Figure 3-4. And we set these data to be a histogram in Figure 5-6.

LC

Vertical Polarizer Plate

Vertical Polarizer Plate

Horizontal Polarizer Plate

Horizontal Polarizer Plate Electrode

Electrode

LC

Electrode

Electrode Back

Light

Back Light

Glass

Glass

-3 -2 -1 0 1 2 3 Normal Distribution

18.0 18.5 19.0 19.5 20.0

data1

Figure 3. Normal probability plot for response time data of Supplier I.

-3 -2 -1 0 1 2 3

Normal Distribution 18.0

18.5 19.0 19.5

data2

Figure 4. Normal probability plot for response time data of Supplier II.

Figure 5. Histogram for supplier I. Figure 6. Histogram for supplier II.

5.1.2 Phase I－Supplier Selection

We will test H₀:C_pu1 ≥C_pu2 versus H₁:C_pu1 <C_pu2 by comparing these test statistics ˆ ₁

Cpu , ˆ ₂

Cpu , and the selection value A &c based on the test statistic and the required sample sizes. If ˆ ₁ ˆ ₂

pu

pu C

C < and A< then we conclude that c the process capability of the new supplier better than that of the present supplier.

The calculated sample statistics for two suppliers are summarized in Table1.

Table 1. The calculated sample statistics for two suppliers.(Cpu) Population X S Cˆ_pu

I 19.00094 0.3072499 1.083872 II 18.97955 0.2724119 1.248655

18.118.218.418.518.718.819.019.119.319.419.619.719.8 data1

0.0 0.4 0.8 1.2

18.1 18.2 18.4 18.5 18.7 18.8 18.9 19.1 19.219.419.519.719.8 data2

0.0 0.4 0.8 1.2

Based on the selection method, the values 083872ˆ 1.

1 = Cpu

and ˆ 1.248655

2 =

Cpu . In this case one only need to compare the test statistic ˆ 1

Cpu and ˆ 2

Cpu , by A=0.1102599 and c=0.2585227 , the outcome presents

2

1 ˆ

ˆpu Cpu

C < and A<c, then we conclude that the process of this new supplier is capable.

5.1.3 Phase II－Magnitude Outperformed Detection

To realize the lower bound value of the magnitude, h, we will test

2 1

0:C_pu h C_pu

H + ≥ versus H1:C_pu1+h<C_pu2. By comparing these test statistics ˆ 1

Cpu , ˆ ₂

Cpu , and the selection value A &c based on the test statistic and the required sample sizes. From the estimation of Phase I, we list the obtained selection values A and c and the decision based on the selection procedure for

h = 0.01, 0.03(0.001)0.035 in Table 2.

Therefore, from the analysis of magnitude outperformed detection based on sample statistics, the magnitude of the difference between the two suppliers is h = 0.034. By the way, we can conclude that the new supplier is more capable than the present supplier at least a magnitude, h=0.034.

Table 2. Magnitude outperformed detection of selection procedure. (Cpu) ˆ 1

Cpu 1.093872 1.113872 1.116872 1.117872 1.118872 ˆ 2

Cpu 1.248655 1.248655 1.248655 1.248655 1.248655

h 0.01 0.03 0.033 0.034 0.035

A 0.1449597 0.2361393 0.2523842 0.2579458 0.2635801

c 0.2585227 0.2585227 0.2585227 0.2585227 0.2585227 Decision Reject Ho Reject Ho Reject Ho Reject Ho Don’t Reject Ho