CN113836489A

CN113836489A - Method and apparatus for analyzing defects of ball grid array

Info

Publication number: CN113836489A
Application number: CN202111123454.4A
Authority: CN
Inventors: 赵林; 杨阳
Original assignee: Intel Products Chengdu Co Ltd; Intel Corp
Current assignee: Intel Products Chengdu Co Ltd; Intel Corp
Priority date: 2021-09-24
Filing date: 2021-09-24
Publication date: 2021-12-24

Abstract

The invention provides an analysis method for a ball grid array on a chip, which comprises the steps of obtaining detection data of defective ball grids in the ball grid array on the chip, wherein the detection data describes a reference point physical position and a physical coverage range of each defective ball grid in the chip, translating the reference point physical position and the physical coverage range into a reference pixel position and a pixel coverage range represented by pixels based on a preset pixel resolution, and generating an indication for representing the defect type of the defective ball grids based on the reference pixel position and the pixel coverage range.

Description

Method and apparatus for analyzing defects of ball grid array

Technical Field

The present invention relates to ball grid array processes, and more particularly to the analysis of defective ball grids.

Background

Ball Grid Array (BGA) is a new chip packaging form, which uses solder balls (or columns) arranged in a matrix on a bare chip as leading-out terminals, has superior characteristics to pin packaging, and thus is widely used to adapt to the development of the semiconductor industry. However, due to the limitation of the packaging technology, problems such as missing solder balls, bridging of two or more solder balls, etc. may occur in the chip ball mounting, and therefore, it is necessary to detect these possible problems to avoid the problem of chip reflow. The ball grid in which such a problem occurs is referred to herein as a 'defective ball grid'. It is also desirable to analyze detected defective ball grids to improve upon the ball-packing process or equipment to avoid or reduce the occurrence of defective ball grids.

The conventional Ball Grid Array (BGA) defect area commonality analysis at present is to manually define a defect area by using a grid and then count the number of occurrences of defects within the area. For example, a ball grid array region of the entire chip is divided into, for example, 16 regions, and then the rate of occurrence of defective ball grids in each region is counted based on defective ball grids identified in advance, thereby achieving estimation of the distribution of defective ball grids occurring on the entire ball grid array. However, it can be seen that such a statistical method inevitably has the problems of long time consumption and low classification accuracy, and the statistics on such values alone cannot accurately reflect the accurate region where the defect occurs, thereby being disadvantageous to the improvement of the ball mounting process or equipment.

Disclosure of Invention

The invention provides a scheme for counting defective ball grids based on a graphic mode, which not only can visually and intuitively present the defect types of the defective ball grids, but also can accurately determine the positions where the defects occur.

According to an aspect of the present invention, there is provided an analysis method for an on-chip ball grid array, comprising: acquiring detection data of defective ball grids in a ball grid array on a chip, wherein the detection data describes a reference point physical position and a physical coverage range of each defective ball grid in the chip; translating the reference point physical location and physical coverage into a reference pixel location and pixel coverage represented by pixels based on a predetermined pixel resolution; generating an indication characterizing a defect type of the defective ball grid based on the reference pixel location and pixel coverage.

According to another aspect of the invention, a statistical platform for automatically visualizing defective ball grids based on big data is provided, and valuable information is integrated by counting data of a large number of defective ball grids on a chip, so that a more valuable reference is provided for process improvement. The method according to the invention therefore further comprises: acquiring, for each of a plurality of chips, a plurality of first ball grid array patterns and/or second ball grid array patterns of defective ball grids exhibiting the first and second defect types; superimposing the first ball grid array pattern and/or the second ball grid array pattern to generate a thermodynamic diagram indicating problematic defects on the chip, wherein different areas on the thermodynamic diagram indicate the frequency and location of defective ball grids. In a preferred embodiment, the plurality of chips are from the same chip location in a tray used in a ball grid implant process, wherein the frequency represents a statistical distribution of the occurrence of defective ball grids at the chip location. The invention can count the statistical distribution of the defective ball grids at different chip positions in the tray, thereby improving the ball grid implantation process.

Drawings

FIGS. 1A and 1B schematically illustrate a defective ball grid;

FIG. 2 shows a flow diagram of a ball grid defect analysis method;

FIG. 3 shows a schematic diagram of the rendering of a defective ball grid on a standard template;

FIG. 4 shows a flow diagram for generating a defective ball grid representation on a standard template;

FIG. 5 shows a schematic diagram of determining defective ball grid locations;

fig. 6A and 6B show a thermodynamic diagram of a defective ball grid based on large data.

Detailed Description

The method and apparatus provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

FIGS. 1A and 1B illustrate exemplary defects occurring in a ball grid array on a chipA representation of ball grids in which missing ball grids appear in the partial view of the ball grid array shown in FIG. 1A, i.e., no solder balls are implanted at position A; while bridging ball grids appear in the partial view of the ball grid array shown in fig. 1B, with the implanted solder balls at positions B and C joined together. In defect ball grid inspection using the prior art, the defect ball grid is detected as being defined by a coverage of a reference point R, as shown in fig. 1A and 1B, wherein the coverage is represented by a rectangular frame SQ in the figure, which covers the missing solder balls, and the reference point R is a corner point of the rectangular frame. Thus the missing ball grid can be expressed as { (x)₀，y₀) (L, W) }, in which (x)₀，y₀) Representing the coordinates of the reference point R and L, W representing the side length of the rectangular range box. In one example, the inspection data is recorded in actual physical locations, e.g., coordinates of reference points and size of rectangular boxes are recorded in micrometers, and each defect ball grid coordinate is recorded with the upper left corner of the bottom view of the SoC die as a coordinate origin, e.g., fig. 1A exemplarily shows a coordinate system X-Y. For the missing solder ball in fig. 1A, its footprint is square, i.e., L ≠ W, since it covers only one solder ball, while for the bridged two solder balls in fig. 1B, for example, its footprint is rectangular, i.e., L ≠ W. Typically, the reference point R has a predetermined relative positional relationship with the associated physical coverage SQ, for example, the reference point R is a corner point of SQ in this example. The coordinates of any point within the coverage SQ, i.e. for any point (x) within SQ, can thus be determined using the coordinates of the reference point R_i，y_i) The coordinate is (x)₀+Δx_i,y₀+Δy_i) Wherein Δ x_i,Δy_iRespectively representing the distance from the reference point R to any point i in the coverage range.

FIG. 2 illustrates an analysis method for an on-chip ball grid array according to one embodiment of the present invention. In step 201, a raw inspection data set ORG _ DataSet is obtained for defective ball grids for a type of SoC chip, where each piece of data in the data set includes a reference point for identifying defective ball grids and its coverage data { (x) as described above₀，y₀)，(L，W)}。

According to this example, in order to graphically show each defective ball grid and its defect type, it is necessary to characterize the position of each defective ball grid in a pixel manner. For this purpose, each data in the detection data set DataSet expressed in physical coordinates is converted into a pixel representation. Specifically, in step 203, the original reference point physical position (x) of each defective ball grid of the inspection data set ORG _ DataSet is first detected₀，y₀) Conversion to physical location representation (x ') in second coordinate System'₀，y′₀) By way of example, FIG. 1A shows a second coordinate system X '-Y', where the origin (0, 0) is located at the lower left corner of the chip, where the conversion to coordinate system X '-Y' is done to facilitate normal viewing habits and operations. The transformation in the two coordinate systems can be realized by a transformation matrix that is substantially 180 degrees flipped for the coordinate systems X-Y and X '-Y' shown in FIG. 1A, so the transformation matrix T can be defined as follows:

the position of each reference point after conversion can thus be expressed as:

this generates a data set TRS _ DataSet at X '-Y' under coordinates. Since coverage does not change during the conversion process, for convenience of illustration, the coverage of each defect ball grid in the data set TRS _ DataSet is still represented by (L, W), and thus each defect can be represented as { (x) 'under the data set TRS _ DataSet'₀,y′₀),(L,W)}。

In step 205, the physical position and the physical coverage range { (x'₀,y′₀) (L, W) } into a reference pixel position (Px) in pixels₀And Py₀) And pixel coverage (Lp, Wp), where Lp,wp represents the lateral and longitudinal dimensions of the coverage in pixels, thus generating a Pixel data set Pixel _ DataSet of a defective ball grid.

For example, in the case where the image resolving dpi is conventionally expressed in inches, the mapping relationship of the physical position to the pixel position is as follows for the case where the physical position of each reference point R and its coverage SQ are expressed in micrometers in this example:

Px₀＝x′₀·dpi/25400

Py₀＝y′₀·dpi/25400

Lp＝L·dpi/25400

Wp＝W·dpi/25400

the above-mentioned conversion relationship of pixels is expressed in microns and in inches, and it is understood that the conversion relationship can be realized by adjusting the scale factor (25400 in this example) for the case of expressing the physical location and the pixels in other units.

In step 207, the generated reference pixel location (Px) may be translated based on step 205₀And Py₀) And its corresponding pixel coverage (Lp, Wp), generating an indication of the type of defect characterizing the defective ball grid. In this example, graphical symbols are used to indicate the defective ball grid and its defect type for visual inspection.

According to an example of the present invention, in order to clearly and contrastingly view defective ball grids from normal ball grids, the present invention uses a standard ball grid array template TP as a reference, as an example, as shown in fig. 3, for normal ball grids, the position of which is defined by the center of the ball grid, i.e., (Px, Py), and each normal ball grid is represented by a standard solid circle, as shown by arrow 1, and for bridged ball grids, as shown by arrow 2, by a special graphic representation that seamlessly connects the ball grids at the two defective ball grid positions. Similarly, for a missing ball grid, other patterns such as circles may be used for representation. Thus, the state of the entire ball grid array can be shown normatively on a standard template TP. It is noted here that fig. 3 shows a schematic view of a portion of a standard ball grid array template TP, represented as a solid circle, on which ideally all normal ball grids are marked as standard solid circles and each ball grid is located at a normal design position, also referred to herein as a standard pixel position. According to the invention, the standard template TP to be graphically displayed has a resolution dpi, so as to coincide with the pixel resolution at which the data are rendered in step 205.

It is noted here that in some implementations it is not necessary to perform a coordinate transformation of the physical position data, e.g. it is obviously not necessary to perform a transformation on the data set acquired directly under the second coordinate system X '-Y', so step 203 can be skipped directly in performing the analysis.

Fig. 4 shows a flow chart for marking defective ball grids on a standard template TP according to an example of the present invention. In step 401, Pixel data for a first defective ball grid is extracted from the data set Pixel _ DataSet, including { ((Px)₀And Py₀) (Lp, Wp) }. At step 403, the shape of its coverage contour SQ is determined based on the coverage data (Lp, Wp). Wherein when Lp is substantially equal to Wp and is close to a predetermined minimum value Vmin, it may be determined that the current pixel data characterizes a missing ball grid; when Lp>>At Wp, e.g., a ratio of Lp to Wp close to 2, it may be determined that the current pixel data is characteristic of a bridged ball grid and that bridging of two solder balls has occurred. In step 403, if it is determined that Lp is substantially equal to Wp, proceed to step 405.

In step 405, based on the reference pixel location ((Px)₀And Py₀) The exact location of the missing ball grid within the coverage SQ, in this case the center position thereof, is determined. For this purpose, as shown in fig. 5, pixel point positions ((Px) are referenced₀And Py₀) With respect to (Lp, Wp), to determine one of the points C0, which is the shortest sum of the euclidean (or gaussian) distances between the point C0 and the standard ball grid in the standard template TP whose pixel position lies outside the pixel coverage SQ, denoted by D0, i.e.:

in the formula, Px_C0＝Px₀+ΔPx_C0，Py_C0＝Py₀+ΔPy_C0And Δ Px_C0，ΔPy_C0Represents the lateral and longitudinal distance of point C0 from reference point R, where 0<ΔPx_C0<Lp,0<ΔPy_C0<And (Wp). In addition, in the formula (Px)_i，Py_i) Representing the positions of standard ball grids located outside the footprint SQ, and N representing the number of standard ball grids located outside the footprint SQ, where the point C0 with the shortest gaussian distance is defined as the center of the missing ball grid and its position data (Px)_C0，Py_C0) Stored in a memory.

According to another example of the present invention, in order to reduce the amount of computation, a range of standard ball grids outside the pixel coverage SQ may also be specified to compute the center C0 of a defective ball grid under SQ coverage, such as specifying a ball grid within a quarter of the area in a ball grid array in a standard template, or the like.

If Lp is determined in step 403>>Wp, then step 407 is proceeded to. As mentioned above, if Lp>>Wp, indicating that there are at least two bridged ball grids under the current coverage, and based on the magnitude and ratio of Lp to Wp, the number of defective ball grids under the coverage can be determined, e.g., in this case, the ratio of Lp to Wp is close to 2, and Wp is close to the minimum value Vmin, and it can be determined that there are two bridged ball grids under the current coverage. Thus, in step 407, based on the reference pixel location (Px)₀And Py₀) And its coverage (Lp, Wp), determine the central position of the two ball grids bridged. For this purpose, the reference pixel point position (Px) is still used₀And Py₀) For reference, each point within the rectangular pixel coverage defined by (Lp, Wp) is traversed to determine two points C1, C2, which are C1, C2, respectively, having the shortest and the second shortest euclidean distance, D1 and D2, to the standard ball grid in the standard template TP whose pixel location lies outside the pixel coverage (Lp, Wp). Correspondingly, the pixel positions of the defective ball grid C1, C2, namely C1: (Px)_C1，Py_C1)，C2：(Px_C2，Py_C2)。

In step 409, it is determined whether all the defective ball grid data in the data set Pixel _ DataSet has been fetched, and if not, it returns to step 401 to continue reading the next piece of data, and repeats

steps

403 and 407 until the complete piece of data is processed.

In step 411, the position data (Px) for the exact position of the defective ball grid determined in step 409 is used_C，Py_C) The standard template TP is marked with the corresponding defective ball grid and is presented with a different pattern from the standard ball grid. For example, location data (Px) for each missing ball grid stored in memory_C，Py_C) On the standard template TP by (Px)_C，Py_C) At the position of the mark, an open circle figure is created to represent the position (Px)_C，Py_C) Where ball grid missing occurs, the open circle pattern is significantly different from the solid circles used to mark standard ball grids to highlight defective ball grids. In this way, the occurrence of missing ball grids can be marked on the standard template TP of the ball grid array representing the entire chip, and therefore the ball grid missing situation can be visually checked.

For the bridged ball grid case, for example, for the two ball grids C1, C2 determined in step 407, on the standard template TP are represented by (Px)_C1，Py_C1) And (Px)_C2，Py_C2) The marked locations may be marked with a pattern that is the same as or different from the standard pattern, in this case still represented in the form of a solid circle as the normal ball grid, as shown in fig. 3. But also to illustrate bridging defects, according to an example of the invention, these two position coordinates (Px) are further processed_C1，Py_C1) And (Px)_C2，Py_C2) Interpolation calculations are performed to calculate the intermediate point between these two positions, e.g., for the intermediate point C12 between C1 and C2, its coordinates can be determined as follows:

at the same time, at the generated intermediate point C12, the same solid circle figure was created to fill the space between C1 and C2. In this way, the intermediate points between C1 and C12 and C12 and C2 were calculated, and solid circles were inserted at each calculated intermediate point to further fill the spaces between C1 and C12 and between C12 and C2. The interpolation process of the intermediate point is repeated until the space between the two solid circles representing C1 and C2 is seamlessly filled. Thus, a ball grid pattern as shown in fig. 3 is presented on the standard template, whereby two ball grids bridged and their positions can be visually seen. In this way, all the bridged ball grids that occur on the chip ball grid array can be marked on the standard template TP, forming a graphical display TP'.

It should be noted that different types of defective ball grids may be marked on the same template TP, or may be marked separately, so as to conveniently check the defect conditions.

In the above manner, each defective ball grid and its type in the data set of defective ball grids detected from a chip may be labeled onto the template TP, thereby forming a graphical display TP' reflecting the defects of the ball grid array on the chip.

In order to analyze the cause of defects caused by processes or equipment on a production line, it is necessary to analyze defects on a large data basis. In a production line, each chip is usually placed on a tray for batch ball mounting, wherein the tray is preset with a plurality of positions for placing the chips, for example, the tray may have 4 rows and 9 columns of placing positions, and 4 x 9 chips may be placed. In a further embodiment of the invention, therefore, for each placement position in the tray, for example for the 1 st row and 1 st column position, a detection large dataset DS of the M chips subjected to the ball-placement process at that placement position is acquired_1,1，DS_1,1＝{DataSet¹ _1,1,DataSet² _1,1,……DataSet^M _1,1And acquiring a detection large data set DS of M chips subjected to ball planting processing at the bearing position for the 1 st row and 2 nd column positions_1,2，DS_1,2＝{DataSet¹ _1,2,DataSet² _1,2,……DataSet^M _1,2In this way, until acquisition is at the firstLarge detection data set DS of M chips subjected to ball planting treatment on 4 rows and 9 columns of bearing positions_4,9，DS_4,9＝{DataSet¹ _4,9,DataSet² _4,9,……DataSet^M _4,9}. It is to be noted here that the number of samples M in the data set acquired per receiving position may be the same or different.

According to an example of the present invention, for a large data set DS obtained at each of the hosting locations, a corresponding ball grid array graphical display TP' may be generated for each data set DataSet in the large data set DS based on a specific defect type, e.g., for missing ball grids₁′-TP_M', then superimpose the M TP' patterns to form a specific pattern that reflects missing ball grids on the M chips at the loading position, such as a thermodynamic diagram, which is superimposed as follows: if the standard pattern (such as a solid circle) is a normal ball grid at the same position on the two superposed graphs, the solid circle of the same pattern is kept unchanged. If a figure (such as an open circle) representing a missing ball grid is arranged at the same position on the two superposed figures, the figure is kept unchanged, but the grey scale of the figure is increased or the color of the figure is changed to show that the situation that the missing ball grid appears at the position is increased. If the figure at the same position on the two superimposed graphs is different, for example, the position of the former graph is a solid circle, and the position of the latter graph is an open circle, the figure at the position is changed into a figure representing a missing ball grid, namely, an open circle, in the superimposed graph to represent that the missing ball grid appears at the position. In this way, the superimposed graphic is compared to the TP₃′、TP₄'… are re-superimposed to form a big data complex map with M TP' maps superimposed, as shown in fig. 6A. FIG. 6A is a schematic diagram showing the distribution and extent of missing ball grids based on the inspection data of a large number of chips on a complete standard template, wherein different gray levels represent the extent of ball grid missing at that location; or in another example, a different gradient color may be used to represent the degree of ball grid missing. FIG. 6B shows a system based on inspection data for a large number of chips on a complete standard templateSchematic illustration of the distribution and extent of the bridged ball grid is made. In fig. 6A, 6B, the right graph represents a gray level indicator.

It is noted here that the complete template shown in fig. 6A is made based on an image of a bare substrate of an actual chip, on which a ball grid array, a capacitive area in the middle area, an edge calibration area, etc. are distributed, according to a predetermined resolution rpi. In the process of manufacturing the template based on the bare bottom image, areas such as a capacitor area, a calibration area and the like which do not contain the ball grid are removed through image recognition processing, and therefore a complete ball grid array image for the type of chip is obtained. On the basis, the complete standard template TP is obtained by carrying out noise filtration and binarization processing on the complete ball grid array image. The binarization here means: for the background, a 0 value process is used, and for each ball grid in the background, a standard graphical representation represented by a 1 value is used, or vice versa.

In the above manner, the quality of ball grid array implantation at a fixed receiving position on the tray can be statistically analyzed, and further the implantation process at the position can be improved according to the statistical result. And the ball mounting process of a batch of chips on the tray can be visually checked, so that the ball mounting process of the whole tray can be checked and improved.

The analysis method according to the present invention may be implemented by a central processing unit CPU or a processor executing a computer readable program or instructions stored in a memory, wherein the processor implements the method of the present invention by executing the instructions in the memory and the analysis results are graphically presented on a display.

While the invention has been shown and described in detail in the drawings and in the preferred embodiments, it is not intended to limit the invention to the embodiments disclosed, and it will be apparent to those skilled in the art that various combinations of the code auditing means in the various embodiments described above may be used to obtain further embodiments of the invention, which are also within the scope of the invention.

Claims

1. An analysis method for an on-chip ball grid array, comprising:

acquiring detection data of defective ball grids in a ball grid array on a chip, wherein the detection data describes a reference point physical position and a physical coverage range of each defective ball grid in the chip;

translating the reference point physical location and physical coverage into a reference pixel location and pixel coverage represented by pixels based on a predetermined pixel resolution;

generating an indication characterizing a defect type of the defective ball grid based on the reference pixel location and pixel coverage.

2. The assay of claim 1, further comprising:

acquiring detection raw data of a defective ball grid in the ball grid array on the chip, wherein the raw data comprises an original reference point physical position of the defective ball grid expressed under a first coordinate system and the physical coverage range;

and converting the original reference point physical position of the defect ball grid into the reference point physical position in a second coordinate system.

3. The assay of claim 2, further comprising: determining the defect type of the defect ball grid based on the characteristic type of the physical coverage.

4. The assay of claim 3, further comprising:

obtaining a standard template of a graphic symbol of a standard ball grid array of the chip, the standard template including standard pixel position data and a standard graphic symbol of each standard ball grid, wherein the graphic symbol of the standard ball grid array has the pixel resolution.

5. The analysis method of claim 4, wherein the physical coverage has a first characteristic type,

the analysis method further comprises:

traversing each point within the pixel coverage area by taking the reference pixel position as a benchmark to determine at least two points, wherein the Gaussian distance between each point of the at least two points and a standard ball grid of which the standard pixel position is positioned outside the pixel coverage area in the standard template is shortest;

marking the at least two points as first confirmed locations of a defective ball grid of a first defect type and storing pixel location data for the first confirmed locations.

6. An analysis method as claimed in claim 4, wherein the physical coverage is of a second characteristic type,

the analysis method further comprises:

traversing each point in the pixel coverage range by taking the reference pixel position as a benchmark to determine one point, wherein the Gaussian distance between the one point and a standard ball grid of which the standard pixel position is positioned outside the pixel coverage range in the standard template is shortest;

marking the one point as a second confirmation position of a defective ball grid of a second defect type and storing pixel position data of the second confirmation position.

7. The method of claim 5, further comprising: iteratively performing interpolation calculations of two-point intermediate values between said first identified positions of said at least two points, wherein each interpolation represents an interpolated point between said first identified positions until the space between two standard graphical symbols representing said at least two points is completely filled by standard graphical symbols representing the inserted points to form an indication of said first type of defect.

8. The assay of claim 7, further comprising:

and presenting the first type of defect ball grids filled by the standard graphic symbols on the standard template to cover the standard ball grids corresponding to the pixel positions of the first confirmation positions in the standard template so as to obtain a first ball grid array graph.

9. The analysis method of claim 6, further comprising presenting defect balls grids of the second defect type on the standard template with another graphical symbol to overlay standard balls grids in the standard template corresponding to pixel locations of the second verification location to obtain a second ball grid array pattern, wherein the other graphical symbol is different from the standard graphical symbol and is indicative of the second type of defect.

10. The assay of claim 8 or 9, further comprising:

acquiring, for each of a plurality of chips, a plurality of first ball grid array patterns and/or second ball grid array patterns of defective ball grids exhibiting the first and second defect types;

superimposing the first ball grid array pattern and/or the second ball grid array pattern to generate a thermodynamic diagram indicating problematic defects on the chip, wherein different areas on the thermodynamic diagram indicate the frequency and location of defective ball grids.

11. The method of claim 10, wherein said plurality of chips are from a same chip location in a tray used in a ball grid implant process, wherein said frequency represents a statistical distribution of occurrences of said defective ball grids at said chip location.

12. The method of claim 7, further comprising counting a statistical distribution of occurrences of said defective ball grids at different chip locations in said tray.

13. The method of claim 7 or 8, wherein said statistical distribution is usable to improve said ball grid implant process.

14. The assay of claim 4, further comprising generating the standard template by:

acquiring an image of a chip containing the ball grid array;

preprocessing the image, including:

identifying and eliminating areas of the image not associated with a ball grid array to form a ball grid matrix;

filtering the ball grid array to eliminate noise;

carrying out binarization processing on a ball grid array region in the image to obtain a binarization image of the ball grid array;

establishing the second coordinate system for the image, determining the central point position coordinate of the binarized image of each ball grid in the second coordinate system, and representing the standard ball grid positioned at the central point position coordinate by using the standard graphic symbol.

15. An apparatus for analyzing defective ball grids, comprising:

a display;

a memory having a computer readable program stored therein,

a processor for executing the readable program to implement the method of one of claims 1 to 14.