Subscribe Now Subscribe Today
Research Article
 

Problem Analysis at a Semiconductor Company: A Case Study on IC Packages



K.A.Z. Abidin, K.C. Lee, I. Ibrahim and A. Zainudin
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail
ABSTRACT

Integrated Circuits (IC) are used in applications such as power supply, mobile phones, lighting, computing, consumer and automotive applications. Defects are a main concern in the IC packages making industry as these could occur at various stages of production and result in huge losses. Problem solving tools have been used to identify the causes of the defects and to formulate practical solutions for the problems. These may include relatively simple visual tools like the Ishikawa diagram and stratification, statistical tools like the Pareto analysis, or more technical tools like the Taguchi design of experiments. This paper demonstrates the effective use of such tools in a semiconductor company and charts the route of a problem analysis to reduce defects. It will be shown that the effectiveness of the process stems from a logical approach which facilitates replication in other departments. The project focused on one major process involving the most valuable IC package in the production where the defects were caused by the machine parameter, process flow, compound type and other non-human causes.

Services
Related Articles in ASCI
Similar Articles in this Journal
Search in Google Scholar
View Citation
Report Citation

 
  How to cite this article:

K.A.Z. Abidin, K.C. Lee, I. Ibrahim and A. Zainudin, 2011. Problem Analysis at a Semiconductor Company: A Case Study on IC Packages. Journal of Applied Sciences, 11: 1937-1944.

DOI: 10.3923/jas.2011.1937.1944

URL: https://scialert.net/abstract/?doi=jas.2011.1937.1944
 
Received: October 22, 2010; Accepted: November 01, 2010; Published: April 18, 2011



INTRODUCTION

The semiconductor company in this case study is a leading international provider of IC packages that powers the products consumers use every day. The company was facing one of its greatest challenges. Defects have occurred in daily production and affect the daily production of IC packages in end of line as shown in Fig. 1. Some of the types of defects are voids, cracks, incomplete mold, fail stand-off height, broken package and marking defects. Appropriate actions are needed to identify root causes, workout and execute solutions. The management decided to confine the project on the end of line process of micro department. The lessons learnt from this pilot project will be implemented in other projects involving other departments. For effective problem analysis, it is important to follow a logical approach using specific tools to arrive at root causes. At each stage, a tool is chosen for the appropriate circumstances to generate answers. These answers may then generate other questions or clues on the problem analysis trail and other sets of answers are found. This investigative process continues until the root causes are finally determined. It should be noted that choosing the wrong tool at any stage on the problem analysis trail may lead to dead ends (Kumar and Sosnoski, 2009; Ho, 1993; Gwiazda, 2006; Hagemeyer et al., 2006). As a simple guide to choosing the appropriate tool, one should begin to understand the outcome of using any particular problem solving tool and the information that is available at the time to make the use of the tool applicable (Bruce, 1990; Juran, 2009). For example the Ishikawa Diagram is used to identify many possible causes for a known effect or problem.

It organizes ideas into helpful categories that are used to identify possible causes for a problem. Stratification is a technique used in combination with other data analysis tools. When data from a variety of sources or categories have been lumped together, the meaning of the data can be impossible to see. This technique separates the data so that patterns can be seen. The process map or flow chart is one of the oldest, simplest and most valuable techniques for depicting and organizing work. It is used to show the sequence of events to build a product. The pareto analysis is a statistical technique that is used for the selection of a limited number of tasks which produce significant overall effect. It employs the 20/80 rule, the idea that by doing 20% of the work one can generate 80% of the benefit of doing the whole job. Or in terms of problem analysis, a large majority of problems or defets (80%) are actually caused by a few vital causes (20%) (Juran, 2009).

Fig. 1: Process for IC packages in end of line

Another useful problem analysis tool, the Taguchi method, can be employed as a mechanism for evaluating and implementing improvements in products, processes, materials, equipment and facilities. As a result of studying the key parameters that control a process, improvements can be realised for desired characteristics that can substantially reduce the number of defects (Klein, 1996; Anthony, 2006; Tong et al., 1997). The tools mentioned thus far, were used to analyse the problem, identify possible causes and formulate solutions to effectively reduce the defects in the IC packages.

MATERIALS AND METHODS

The overall methodology has been summarized in Fig. 2. IC packages were inspected under 30x scopes after each process and the data of defects were collected.

Fig. 2: Methodology

Table 1: L25 Orthogonal Array

The data for IC packages with the most defects were stratified to highlight patterns if any in the defects. Next, pareto analysis was carried out to segregate major contributing defects categories. The Ishikawa diagram was then used to draw out possible causes for the major defect. To understand the effect of the combination of contributing parameters for the identified possible cause, the Taguchi method was then employed.

Table 2: Values of parameters set for each experiment

Experiments were conducted with 6 parameters and 5 levels. The appropriate orthogonal array is L25 as shown in Table 1.

For the experiment, the following factors are assumed:

Other variables besides mold parameters are assumed constant
The experiments are carried out on a fixed auto mold machine
The surrounding condition is assumed to be constant
The same operator was assigned to operate the machine
The experiment is conducted on dummy frame (without die)

The conditions set for each experiment are listed in Table 2.

RESULTS AND DISCUSSION

The result from defects inspection of all the packages is summarized in Table 3. Three IC packages, 6SOT23M, 5SC70M and 6SC70M were identified to have the highest number of defects. These 3 packages in fact make up a substantial 70% of the company output from Micro End-of-Line and therefore deserves more focus. To facilitate a closer inspection of the 3 packages, stratification was employed. Figuer 3-5 summarize the stratification exercise.

Table 3: Defects according to package type

From the 3 stratification charts above, the defects were categorized into process specified defects. As shown in Table 4, 5 and 6, there are only 5 manufacturing processes in micro end of line. These are molding, laser mark, high pressure water jet, plating and trim, form and singulation. The others are inspection and packing processes. Defects such as incomplete mold, void, fail vertical offset, flashes, compound leaking, flake surface and unclean package are categorized under molding processes defects. Lead width, fail stand-off height, bent lead, missing lead and no forming are categorized under trim, form and singulation process defects. Marking defect comes under its own category and originates from the laser marking process. While chip, dented lead, crack and broken package is categorized under other group because these defects can be caused by various processes or combination of a few processes.

Fig. 3: Stratification of defects for 6SOT23M

Fig. 4: Stratification of defects for 5SC70M

Fig. 5: Stratification of defects for 6SC70M

Fig. 6: Pareto diagram of defects for 6SOT23M

Table 4: Pareto table of defects for 6SOT23M

Fig. 7: Pareto diagram of defects for 5SC70M

Table 5: Pareto table of defects for 5SC70M

Fig. 8: Pareto diagram of defects for 6SC70M

Table 6: Pareto table of defects for 6SC70M

Table 7: Consequences when mold parameter out of control

Using the Pareto analysis, it was also observed that molding is the process that contributes most to the defects of the 3 types of packages which cover 62.96% of 6SOT23M, 57.14% of 5SC70M and 73.91% of 6SC70M as shown in Fig. 6, 7 and 8. Therefore, the company then decided to look at the molding process in more detail as out of control mold parameters produce consequences as shown in Table 7.

Ishikawa analysis of incomplete mold of 6SOT23M drew out possible causes. These were verified as shown in Table 8. To optimize the mold parameters the Taguchi method was employed. The results of the experiment are shown in Table 9.

It can be seen that experiment No. 15 has the lowest defect number yield. This mold parameters configuration was suggested to be used instead of the current mold parameters because it yields the least number of defects. Shown below is the sample calculation and tabulation of the SN ratio.

(1)

(2)

(3)

(4)

(5)

Table 8: Verification of possible causes for incomplete mold of 6SOT23M

Table 9: Data collected from experiments

Table 10: SN ratio values

The other values of SN ratio are calculated as above and tabulated in the Table 10. The response table to calculate an average SN value for each factor is shown in Table 11.

A sample calculation for Factor B (Clamp Pressure) is shown below:



Table 11: Average SN values

Table 12: Values of SN and ranking

The value of SN for each factor and value of the effect of the factor is shown in Table 12. It can be seen that clamp pressure has the largest effect on the defect number and transfer pressure has the smallest effect on defect number.

The effect of this factor is then calculated by determining the range.

CONCLUSION

The processes in Micro End of Line produced a certain amount of defects. The problem analysis identified all the defects and categorized them into different categories as well as reported the identified possible causes. The investigation zoomed into the molding process because the evidence showed this process was contributing the most defects. The use of the Ishikawa Diagram and the Taguchi method successfully identified the more critical parameters as well as the best parameter configuration that produced the least number of defects. It can therefore be concluded that the mentioned problem analysis tools can be effectively used to reduce the number of defects in IC packages provided they are employed appropriately.

REFERENCES
1:  Klein, I.E., 1996. Application of taguchi methods to the production of integrated circuits. Microelectronics Int., 13: 12-14.
CrossRef  |  

2:  Antony, J., 2006. Taguchi or classical design of experiments: A perspective from a Practitioner. Sensor Rev., 26: 227-230.
CrossRef  |  

3:  Kumar, S. and M. Sosnoski, 2009. Using DMAIC six sigma to systematically improve shopfloor production quality and costs. Int. J. Productivity Performance Manage., 5: 254-273.
CrossRef  |  

4:  Ho, S.K.M., 1993. Problem solving in manufacturing. Manage. Decision, 31: 31-38.
CrossRef  |  

5:  Tong, L.I., C.T. Su and C.H. Wang, 1997. The optimisation of multi-response problems in Taguchi method. Int. J. Qual. Reliabil. Manage., 14: 367-380.

6:  Gwiazda, A., 2006. Quality tools in a process of technical project management. J. Achieve. Mater. Manuf. Eng., 18: 439-442.
Direct Link  |  

7:  Bruce, R., 1990. Simple tools solve complex problems. J. Qual., 29: 50-50.

8:  Hagemeyer, C., J.K. Gershenson and D.M. Johnson, 2006. Classification and application of problem solving quality tools: A manufacturing case study. TQM Magazine, 18: 455-483.
CrossRef  |  

9:  Juran, J.M., 2009. Juran's Quality Control Handbook. McGraw-Hill, New York.

©  2021 Science Alert. All Rights Reserved