NUMERICAL STUDY AND CASE STUDY ABOUT MULTIVARIATE CONTROL CHARTS USING MEWMA AND MCUSUM PROCEDURE
Statistics is very important thing in industry world. In production process, the industry want to produce good product and reduce the probability to produce the product that not meet the industry requirements. One of the ways to control the production process is using the Statistical methods calls S...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/23369 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Statistics is very important thing in industry world. In production process, the industry want to produce good product and reduce the probability to produce the product that not meet the industry requirements. One of the ways to control the production process is using the Statistical methods calls Statistical Process Control (SPC). In producing a product, there are several characteristic quality that can influence the product in terms of good or bad product. To control that several characteristic quality, we used Multivariate Statistical Process Control (MSPC). In this thesis, will be explained about 2 MSPC procedure that often used in industry, Multivariate Exponentially Weighted Average (MEWMA) and Multivariate Cumulative Sum (MCUSUM). We will explained how to build the control charts using MEWMA and MCUSUM procedure step by step and comparing MEWMA and MCUSUM procedure. Methods that used to find the parameter of control charts are Bootstrap resampling and Average Run Length (ARL). The result we will see which control chart can detect the shift better. |
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