Considering profiles as functional variables, two control charts are proposed for their monitoring in phase II. Due to its conformity with the nature of real-world profiles, applying functional model leads to proposed control charts obtained through functional data analysis techniques with desired features. These include simplicity in calculation and possibility of using them for different prof...

This cross-sectional study was undertaken to compare WHO and Indian Academy of Pediatrics (IAP) recommended growth charts compiled by Agarwal. 2105 children aged less than 5 years, attending 132 Anganwadi centres in Mysore city, were included by simple random sampling method. Weight and height of all children were recorded and plotted on both WHO and IAP charts. WHO charts detected more boys as...

Classical control charts are very sensitive to deviations from normality. In this respect, nonparametric charts form an attractive alternative. However, these often require considerably more Phase I observations than are available in practice. This latter problem can be solved by introducing grouping during Phase II. Then each group minimum is compared to a suitable upper limit (in the twosided...

this paper addresses the design of control charts for both variable ( x chart) andattribute (u and c charts) quality characteristics, when there is uncertainty about the processparameters or sample data. derived control charts are more flexible than the strict crisp case, dueto the ability of encompassing the effects of vagueness in form of the degree of expert’spresumption. we extend the use o...