Six Sigma quality management relies on Six Sigma quality tools, leaving the Six Sigma quality management quality tools it takes to become their table. Here several common quality tools to make some simple introduction. 1, the basic statistical analysis tools mainly for statistical characteristic quantities of samples for analysis, including sample mean, median, mode, variance, range, standard deviation and oblique twist resistance, skewness, kurtosis characteristics of the volume analyzed, and histogram of the sample. Conduct distribution fitting. ?? 2, correlation and regression analysis, a major research tool for variable y a mathematical relationship between the tool and the other several variables X, which is in the experimental or observational data on a group basis. Dependencies are looking to cover up the randomness of variables. Roughly speaking, can be understood as a function of a deterministic approximation to replace the more complex relationship, this function is called the regression function, in practical problems is called the empirical formula. Regression analysis of the main problems is how to take advantage of research variables X, Y observations (sample), the regression function of statistical inference, including its estimation and hypothesis testing with it and other relevant. 3, analysis of variance ANOVA tools of Six Sigma is an effective tool for test data analysis of industrial and agricultural production and scientific research, but also to carry out the mathematical basis of experimental design, parameter design and tolerance design. There are many complex factors that things tend to restrain and mutually interdependent. The purpose of the analysis of variance is to find things factors have a significant effect, the interaction between various factors, as well as the optimal level of other significant factors in the data analysis. 4, measurement systems analysis tools (MSA) Six Sigma measurement system analysis tools are a few characteristics of the measurement system (accuracy, repeatability, reproducibility and stability, linearity, resolution) were analyzed in order to confirm the overall error, measurement system error and staff size measuring instrument error of measurement, and the usefulness of the measurement system to make judgments. ? ?? 5, statistical process control tools (SPC) Six Sigma Statistical Process Control (SPC: Statistical Process Control) is abnormal by control charts, process control and diagnostics via theory (SPCD) to find out the reasons for the exception and be excluded. Commonly used Shewhart control chart has a very poor Mean (xR) control charts, the mean one standard deviation (xS) control charts, a poor median (xR) control charts, the value of a single moving range (x-Rs ) control charts and nonconforming rate (P) control chart, the number of nonconforming product (Pn) control chart, the number of defects (C) control charts, defects per unit (u) control maps. SPC is to maintain stable production lines, a powerful tool to reduce quality fluctuations. 6, Taguchi experimental design tools (DOE) Six Sigma Taguchi experimental design includes three design, the system design, parameter design and tolerance design. Taguchi experimental design analysis tools mainly for parametric design. The basic idea of ??the design parameters of the system by selecting all parameters (including raw materials, parts and components) of the optimal level of portfolio to try to reduce the effect of three kinds of interference between the external, internal and products, product quality and characteristics of the design fluctuation is small, good stability. In addition, the parameters of the design stage, is generally used to meet the environmental conditions of the lowest quality level of components and cost-effective to design precision, so that the quality and cost of the product in terms of both improved. Contact: Mr Tsang Company Name: Heaven Enterprise Management Consultants Ltd. For more please visit: Sigma www.lxgmgl.com