The primary benefit of a statistical tolerance approach is that the tolerance on an individual part can be increased while still maintaining acceptable assembly or system performance. In DFSS and design engineering, conventional or worst-case tolerancing assumes that all component dimensions may simultaneously occur at their extreme limits, which often forces very tight individual tolerances. Statistical tolerancing recognizes that such simultaneous worst-case conditions are unlikely when component variation is random and controlled. By considering the statistical distribution of variation across parts, designers can often allow wider tolerances on individual components without sacrificing fit, function, or reliability of the final product. This provides greater manufacturing flexibility and can reduce production cost, scrap, inspection burden, and supplier difficulty. The method does not simply duplicate conventional results, nor does it reduce design latitude. In fact, it gives the designer more practical freedom by balancing performance requirements with realistic variation behavior. In Six Sigma design work, this supports robust product design and cost-effective manufacturability. Therefore, the correct answer is that the tolerance on an individual part can be increased.

===========