Identification Of Causes Of Varation In The Semiconductor Manufacturing Processes By Statistical Analysis A Six Sigma Approach

Gunasegaran, Vijaya Kumaran (2010) Identification Of Causes Of Varation In The Semiconductor Manufacturing Processes By Statistical Analysis A Six Sigma Approach. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Six Sigma is an improvement process, developed by Motorola in 1985 that continually strives for perfection by reducing variation in the production processes. In semiconductor industry, the output of production is important. Increasing the output without maintaining the quality would lead to increase in variation in the process. By reducing this variation, it will improve the quality of the product. The objective of this project is to detect and find possible ways to reduce the variation in semiconductor manufacturing production of IC (Integrated Circuit). Production data from the industry will be analyzed to detect data variation. From here, a possible solution will be proposed to the industry. Causes of variation can be classified as common and special causes. In this case, special causes of variation are taken as subject to do the analysis. Wrong ingredient, wrong process setting, or an untrained operator is example of special causes.To observe and analysis the variations of the data, the Process Capability (Cp) method is use. Process capability is a method by compress the output of an in-control process to the specification limits by using capability indices. The target to achieve in this analysis is to detect and find possible ways to reduce the special cause’s variation in manufacturing of IC(Integrated Circuit). All products and services are a result of some process. Also, Six Sigma benefits others beside customers. Six Sigma not only treats manufacturing as parts of a large system, it removes the narrow, inward focus of the traditional approach. A thorough literature study on Six Sigma, Statistical Process Control tools and the implementation of Six Sigma in the semiconductor industry will be performed.

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