The Taguchi method, Mahalanobis distance, and Plackett-Burman design are all Indian mathematical methods that have been successfully applied in industrial quality control.

The Taguchi method is a statistical method for designing experiments to optimize product quality. It is based on the idea of using orthogonal arrays to reduce the number of experiments required to achieve a desired level of accuracy.

The Mahalanobis distance is a measure of the distance between two data points in a multidimensional space. It is calculated by taking the square root of the sum of the squared differences between the two data points, divided by the covariance matrix of the data set.

The Plackett-Burman design is a type of experimental design used to screen a large number of factors. It is a two-level factorial design that allows for the estimation of the main effects of the factors, as well as the interaction effects between the factors.

Indian mathematical methods can be used to improve industrial quality control by reducing the number of experiments required to achieve a desired level of accuracy, identifying the most important factors affecting product quality, and optimizing the process parameters to achieve the desired level of quality.