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Case Analysis: General Microelectronic, Incorporated: Semiconductor Assembly Process Case Solution & Answer

Case Analysis: General Microelectronic, Incorporated: Semiconductor Assembly Process   Case Solution

Moreover, if a comparison among 6 sigma and GME’s process perform, it can be said that six sigma criteria requires 99.99966% success rate to qualify for the six sigma process. But in case of GME it can be seen that the process is only capable of performing 92.04% successful operations. Finally, it can be concluded that the overall process is not in control because the company is striving to achieve 6 sigma but the process doesn’t match the criteria.

1          Capability of the Process

The overall capability of the process has already been calculated in appendix 2 but detailed calculation are present in the excel spreadsheet labeled ‘capability’. Furthermore, the double averages of net samples were calculated afterwards, the SD of the data was calculated for every sample. Then, the capability of each process was calculated and lastly, the overall capability of the process has been calculated by taking the average of whole process. Moreover, if the value of capability is greater than one, then the company or the process can achieve six sigma. Otherwise it will remain three sigma.

The overall capability of the process is calculated in the formula

Capability=

Furthermore, the overall average is showing a capability of around 0.54 which is lesser than 1. This indicates that the process does not qualify for six sigma criterion and it will call as a three sigma company.

2          Design of Experiment (DOE) and its Results

According to design of experiment there were four major elements that were incorporated in the experiment. These elements were power, time, force and temperature. Moreover, the data of this experiment is presented in the spreadsheet namely DOE.

Furthermore, the repetition of the process for each element was also incorporated in the data and by the help of the data; the analyst calculated the effect of these repetitions on different elements. Moreover, the overall effect of these repetitions was also calculated by taking the average of each repetition and it was found that the average effect on energy was -0.6, on time it was 1, while for force it was 1.4 and finally, for temperature, it was 1.8.

However, this indicates that energy was over utilizing by the machine whereas, time management was excellent. On the other hand, labor was underutilized and finally, temperature was also less as compared to the requirement.

3          Regression Analysis

Regression analysis has also been conducted to measure the overall impact of the process on pull strength. Over here, the analyst made reps as the dependent variable and time, power, force and temperature as the independent variable. In addition, the findings of the regression suggested that all of the independent variables have a significant impact on pull strength and it will be accounted for almost 87% as per the adjusted R-Square. Moreover, the following equation was made excluding the intercept.

4          ANOVA

The ANOVA has been conducted on the process and to compare that whether the effect for all the variables is same on pull strength or not. Findings revealed that the null hypothesis has been rejected and therefore, it means that all the variables have different impact and influence on the pull strength.

        T-Test

The T-test of the variables suggested that all the variables have different intensity of impact on the overall pull strength. This also confirms the results of the Multiple Linear Regression. Furthermore, the most intense impact on pull strength is held by power as per the T-test and then the force, temp and time have impact on the overall pull strength…………….

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