Mounting of surface mounted components for the hot

2022-08-11
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Monitoring the mounting of surface mount components

this paper introduces: "to achieve the desired efficiency and reliability depends largely on the component mounting process."

the desire to increase circuit density on PCB continues to be one of the main driving forces for the progress of surface mount assembly line technology. This progress includes the use of 0201 chip packaging, closely spaced QFP, high input/output BGA, CSP and flip chip. The use of these components puts forward strict requirements for the assembly process. In particular, to achieve the desired efficiency and reliability depends largely on the component mounting process. More and more surface mount lines are using automatic, automatic and post mount inspection tools to monitor the state of the mounting process. The inspection after mounting can find defects such as component loss, polarity exchange and component position exceeding the specified error

in addition to finding defects, the post installation inspection tool can also check the process changes that affect the accuracy, quality and efficiency of the assembly process. If the process change can be found and confirmed by monitoring the component mounting accuracy, corrective action can be taken immediately to minimize the impact on efficiency. This ability requires the application of diagnostic tools for analyzing measured data, and the use of diagnosis requires a comprehensive understanding of the possible root causes of errors in the mounting process

template printing process

a possible root cause of mounting errors is the template printing process. In particular, the height, area or volume of the solder paste block may affect the mounting accuracy due to the lateral movement of the component when the pin falls into the solder paste during mounting. To test this hypothesis, a large number of boards were processed through the surface mount/flip chip assembly line located at the center for board assembly research (CBAR) of Georgia Tech, Atlanta, GA. During operation, change the scraper pressure, printing speed, snap off interval and release speed of the template printer to obtain a range value of the height, area and volume of the solder paste block. Using commercially available inspection tools, we measured the height, area and volume of solder paste blocks after printing, as well as the deviation of X and y of components after mounting

figures 1 and 2 show X and Y deviation diagrams, which are functions of solder paste block height, area and volume of 0402 element and LQFP element with 0.4mm spacing. If there is a strong correlation between offset and solder paste parameters, the charts in Figure 1 and Figure 2 will reveal this relationship. However, it can be seen from the chart that the chart is composed of clusters of points, and there is no obvious relationship. For 0402 components, the offset of X and Y in the graphic display is somewhat scattered with the increase of height, but the dispersion of values is due to the majority of data points with larger height values. The cross-correlation value calculated from the measured data is very low, which further confirms that there is no important relationship between the mounting accuracy and the height, area and volume of the solder paste block

mount on the double-sided tape

this test does not include the possible impact on the mounting accuracy caused by the deviation between the solder paste block and the pad position or by the strange or non rectangular solder paste block. In order to eliminate any factors involving solder paste blocks, we conducted another experiment, covering half of the board with double-sided tape after printing. Fiducial points are left uncovered. Then the components are pasted on the tape, so that the solder paste will not affect the mounting accuracy. The profit margin of the enterprise has been greatly reduced. It is necessary for us to stick the adhesive tape on the board printed with solder paste for the proper operation of our installed inspection tools. The other half of the board is treated in a normal way, and the components are pasted in the solder paste

the sample results are provided in figures 3 and 4, which show the average value and standard deviation of X offset, which is a function of the element type of normal plate and double-sided tape plate. Note that the standard deviation is smaller for the plate with double-sided adhesive tape, and the average value of X offset is smaller for the plate with double-sided adhesive tape except for two components

these results show that placing components in solder paste has some influence on the mounting accuracy, but from the figures in Figure 3 and Figure 4, the influence is very small. Therefore, this result is consistent with the first experiment. The template printing process has no important influence on the mounting accuracy. This statement does not mean that the quality of the template printing process has no impact on the results. In particular, the amount of solder paste blocks that realize continuous film blowing of PPC in Nantong Huasheng new materials company after printing is the main factor that determines the quality of solder joints after reflow

other error sources

mounting errors may be due to problems with the mounting equipment, including: component suction, component movement to the correct position, and component mounting

in the element suction, the wrong setting of the feeder may cause the position offset, which will affect the mounting accuracy. Although the mounting machine may use the vision system to check the position of the extracted components, errors may also occur due to the limited resolution of the imaging system or defects in the imaging process. The movement of components to the correct position requires the machine to be calibrated correctly, and the gantry system does not produce offset errors. The correct positioning of components also requires the normal operation of the mounting nozzle. Problems with component suction, movement or mounting can be checked by analyzing component offset errors

mounting error analysis

three parameters are useful in analyzing mounting offset errors:

average deviation of a series of components on a board

standard deviation of a series of components on a board

number of times the deviation of a series of components on a board exceeds the limit

a relatively large average value indicates a deviation in the process such as losing calibration. The standard deviation provides a measurement parameter of the variable degree of mounting accuracy. The number of offsets beyond a certain limit provides information about the "tailing" of the distribution of offset values

in the process of mounting, a problem can be found by analyzing these parameters as the plate moves on the production line. In addition, the root cause of a problem can be confirmed by analyzing these parameters of a specific component combination on the board. For example, the problem of a feeder can be found by calculating and analyzing these parameters of component combinations from different feeder locations. The problem of installing a suction nozzle can be found by calculating and analyzing these parameters of the combination of components installed by different suction nozzles. These parameters are used as a function of the label of the suction nozzle, and their calculation can be combined with the vacuum pressure of the suction nozzle to improve the awareness of the problem

nozzle failure detection

for the plates in the second test, we calculated the standard deviation of the X offset values of the components attached with different nozzles. Figure 5 shows the standard deviation diagram of X offset, which is used as a function of the number of suction nozzles on a plate. It can be seen from the figure that a significant peak occurs on suction nozzle 10 and a smaller peak occurs on suction nozzle 12. The peak value of No. 10 suction nozzle was observed on some other bench drawings in the test. In order to prove a problem in No. 10 nozzle, we drew the vacuum pressure diagram of nozzle mounting, which has a negative value and is a function of nozzle number (Fig. 6). Note that the vacuum on suction nozzle 10 has the smallest negative value. This value is consistent with the increase in the standard deviation of the offset of the mounting element through the No. 10 nozzle. Because the mounting vacuum pressure is small, we can expect an increase in offset variability. Combined with FIG. 5 and Fig. 6, using the microcomputer hydraulic servo universal experimental machine to test the mechanical properties of materials, we come to the conclusion that No. 10 suction nozzle is not the best operation

this problem is the intentional wrong result of using the wrong suction nozzle to suck the cylindrical 0805 element. The suction nozzle used is an element designed for rectangular shape, so a small vacuum leakage occurs due to the mismatch of the shape. The influence of nozzle mismatch and the shadow of partial blockage of nozzle in practice ③ The fixture itself is a locking mechanism, and the sound is similar. Therefore, the monitoring and analysis of deviation errors and mounting vacuum pressure should be able to find out the problems of the suction nozzle

robust inspection

in the process of monitoring parameters mentioned above, a key problem is to decide whether the process is changing and needs adjustment based on the values of these parameters. If the drawing of parameters is generated on the basis of each board and displayed in the factory workshop, an experienced equipment operator may be able to correctly determine a problem by observing the displayed information. However, an automatic process to find the existence and development of a problem will be more effective. Existing technologies, such as SPC (statistical process control), can be applied to the collection of parameter values to produce "yes/no" decisions about the existence of problems. However, this technology may not be robust enough to produce correct decisions for highly naturally changing processes, such as electronic assembly

in recent years, many efforts have been made to develop "soft decision" methods based on concepts from artificial intelligence (AI) and Bayesian probability theory. In the soft decision-making method, the probability or likelihood of the existence of a problem or defect is calculated, rather than with/without type decisions. A soft decision method can provide more robustness to get the right conclusion in a very noisy environment. Research at Georgia Institute of technology has focused on the development of soft decision-making methods for defect detection in electronic manufacturing

use of gem interface

the equipment on the assembly line of Georgia Institute of technology is connected to a host through a gem (generic equipment model) interface. Use a commercial gem based software package to collect data during assembly line operation. The software package greatly simplifies data collection and writes simple application modules for possible data processing. As a part of the processing system architecture, we write an application program, so that each board can be regarded as an object that accumulates data as it moves on the assembly line. With this setting, data from different equipment items on the assembly line can be compared or correlated to obtain results about the status of the assembly line

conclusion

the continuous promotion of higher PCB circuit density puts forward even more stringent requirements for assembly process control. Even with the improved performance of the new generation of equipment, the status of the assembly line always needs to be monitored, partly due to human errors in operating the equipment. This monitoring will show whether adjustments are needed to maintain quality. A major challenge is to develop an automatic scheme to process a large amount of measurement data to produce correct decisions about the operating state - implemented robustly in a noisy environment. The automatic processing of parameters mentioned in this paper can provide a useful tool for the operation of production line

Acknowledgements

The authors wish to thank Siemens, Speedline/MPM, Machine Vision Technology, CyberOptics, Cimetrix and Crown Simplimatic for contributing project support and/or equipment for carrying out this research..

References

Kim, B. and May, G.S. (1995). Real-time diagnosis of semiconductor manufacturing equipment using neutral networks. Proceedings of IEEE/CPMT International Semiconductor

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