R help - Apr 2011 - a statistical problem - more statistical strategy for making quality control

Dear R-listers,

I would like to have your helps on make a good strategy of quality
control by several quality control variables. This means I need a good
strategy to choose cutoff for each quality control variables, or make
cutoff for all such quality control variables in one time.

For quality control, we employed several values. Each production has
each value of such variables:
(1) concordance, (float, from 0 to 1, but 0.5 is the expected best one).
(2) coverage, (integer, >=1, more large more better)
(3) base quality, (integer, 1 to 40, more large more better)

Here, concordance may be the most important variable for quality
control. The best product determined by concordance are those have
values of 0.5. Obviously, smaller ones (<0.1) and bigger ones (>0.9)
are not good. Coverage may also play an important role, like the
products which have 0.5 vale for concordance and 0.1 coverage may not
be the good calls. While, base quality is the same with converage. The
bigger base quality should be the products which are better.

Here, I want to find a good strategy to set a cutoff to our products
based on these three or just concordance and coverage variables. I
prefer a more statistical way.

Would you please give me any ideas/directions on my problems? Thanks in advance.

###########################################################
# as an example, I create a dummy data for my question.

product<-1:100
concordance<-rnorm(100, mean=0.2)
coverage<-sample(1:50, 100, replace = T)
base.quality<-sample(1:40, 100, replace = T)

dummy <- cbind(product, concordance, coverage, base.quality)

Best,

Jian-Feng, Mao