J
JAltmann
My company has recently started utilizing FTY data for our internally produced products, but these processes currently produce at varying levels per time period, ie week, month etc.
We wish to track the data and compare for improvement, ut if week 1 has 2 failures out of 50 pieces and week 2 has 2 failures out of 45 pieces we are no longer comparing at even rates.
Would normalizing the data such as week 1 of (48/50)= 96% => (.96)^(1/50)=99.92% and week 2 FTY=(43/45)=95.56% => (.9556)^(1/45)=99.90% be a better way of comparing the data for varying production sizes?
Or is their another or better method of comparing varying size lots? Should i possible treat the data as continous? ie continue to total created divided by the number of good parts?
We wish to track the data and compare for improvement, ut if week 1 has 2 failures out of 50 pieces and week 2 has 2 failures out of 45 pieces we are no longer comparing at even rates.
Would normalizing the data such as week 1 of (48/50)= 96% => (.96)^(1/50)=99.92% and week 2 FTY=(43/45)=95.56% => (.9556)^(1/45)=99.90% be a better way of comparing the data for varying production sizes?
Or is their another or better method of comparing varying size lots? Should i possible treat the data as continous? ie continue to total created divided by the number of good parts?
