A principal component analysis describes the variability of the input bands. The first principal component describes the most variability defined by the input bands. The second principal component describes additional variability but less than the first principal component, the third component additional variability but less than the second, and so forth. The analysis is known as a data reduction technique by describing the most variability in the least amount of bands.
If all the variability is defined by the initial bands, by definition, you cannot define more variability than that which is already present by using more than the number of bands in the input raster.
Make sure the number of principal components is less than or equal to the number of bands in the raster or Esri Grid stack.