Management of technology: a case study of cost deduction in multi - site testing for the semiconductor industry

• Main Author: Khoo, Voon Ching
• Format: Thesis
• Language: English; English
• Published: 2013
• Subjects: HD28 Management. Industrial Management
• Online Access: http://ur.aeu.edu.my/120/1/Management%20of%20technology%3B%20a%20case%20study%20of%20cost%20deduction%20in%20multi%20-%20site%20testing%20for%20the%20semiconductor%20industry-1-24.pdf; http://ur.aeu.edu.my/120/2/Management%20of%20technology%3B%20a%20case%20study%20of%20cost%20deduction%20in%20multi%20-%20site%20testing%20for%20the%20semiconductor%20industry.pdf; http://ur.aeu.edu.my/120/

With the increasing demand for high-complexity consumer Electronic products, the design of New Semiconductor chips needs to provide the required flexibility and speed. This trend shows that the functionality built into a single Semiconductor chip has continuously improved compared to the functionality 20 years ago. In contrast, Testing Costs in Semiconductor industries today can reach a substantial percent of the total Manufacturing Cost, thus affecting the Profit Margin. Numerous approaches have been introduced to lessen Testing Costs; one of them is the Multi-site Testing. Two case studies were conducted to determine the effectiveness of Multi-site Testing in reducing Testing Costs. To achieve the research goal, a Multi-site test Cost Model and Profit Model was developed using the test Cost economic Model developed by Evan (1999) based on the economic theory of the firm, and by integrating important elements including economic Profit Margin and technology Multi-site efficiency. These models enabled the researcher to measure the capabilities of the Multisite Testing for the Cost of Test Deduction and it effectiveness in relation to improving the Profit Margin. The case studies were conducted on two types of Test-equipment, namely, Wafer-Ring and Pick-and-Place Test-equipment setup. Five Multi-site configurations were configured on both Test-equipment setups for comparison. Testing time, Indexing time, and Test yield-data were collected for the purpose of establishing the Testing Cost and calculating the Profit Margin. Four hypotheses were tendered to analyze the performance of the Testequipment setup, including Multi-site versus Multi-site efficiency, Multi-site versus Testing throughput, Multi-site versus Testing Cost, and Multi-site versus Profit Margin improvement. The findings were analyzed using one-way ANOVA, Post-hoc test, and factorial ANOVA. This research established that increasing the number of test sites is not sufficient to guarantee reduced Testing Cost while maintaining Profit Margin because, once the number of test sites increases correspondingly, the Testing time will increase as well. It is therefore proposed that future work be conducted on the Multi-site Testing Approach together with other Testing Approaches that can reduce Testing time, such as concurrent Testing.