• Proceedings of the Safety Management and Science Conference
• /
• 2011.04a
• /
• pp.675-693
• /
• 2011

We compare three Techniques control systems with The Investigate Study on the relation between Multivariate SPC and Autoregressed Algorithm. We also investigate Autoregressed Algorithm with relevant EWMA, CUSUM, Shewhart chart, Precontrol chart and Process Capacity.

• Journal of the Korea Safety Management & Science
• /
• v.13 no.4
• /
• pp.225-235
• /
• 2011

Autoregressed Controller, which have trend algorithm, seeks to minimize variability by transferring the output variable to the related process input variable, while multivariate process control techniques seek to reduce variability by detecting and eliminating assignable causes of variation. In the case of process control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We also investigate algorithm with relevant Shewhart chart, Theoretical control charts, precontrol and process capability. To help the people who want to make the theoretical system, we compare the main techniques in "a study on the relation between multivariate process control techniques and trend algorithms".

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.1
• /
• pp.91-100
• /
• 2016

Fuzzy matching is proposed to make propensities of two groups similar with their propensity scores and a way to select control variable to make propensity scores with a process that shows how to acquire propensity scores using logic regression analysis, is presented. With such scores, it was a method to obtain an experiment group and a control group that had similar propensity employing the Fuzzy Matching. In the study, it was proven that the two groups were the same but with a different distribution chart and standardization which made edge tolerance different and we realized that the number of chosen cases decreased when the edge tolerance score became smaller. So with the idea, we were able to determine that it is possible to merge groups using fuzzy matching without a precontrol and use them when data (big data) are used while to check the pros and cons of Fuzzy Matching were made possible.