In quality control assume that the distribution of their process output is normal. The
definition and estimation of (pci) indices are usually based on the assumption that the
production process under normal distribution. But, in most practical cases this assumption
is not valid and the distribution of the quality characteristics may follow non-normal
distributions such as Weibull ,Lognormal , and Exponential distribution). One can see the
difference between the non-normal process capability indices and the normal process
capability indices by overlooking its theoretical distributions .This paper provides a decision
on how to calculate the process capability indices for normal and find process capability
indices another step transformation data by (Box – Cox( and Johnson transformation and
comparison between two methods.
Ali Hadba, W. (2016). COMPARISON METHOD PROCESS CAPABILITY INDICES FOR NORMAL AND NON-NORMAL DATA BY USE SIMULATING.. Kirkuk Journal of Science, 11(4), 112-140. doi: 10.32894/kujss.2016.131068
MLA
Wakkaa Ali Hadba. "COMPARISON METHOD PROCESS CAPABILITY INDICES FOR NORMAL AND NON-NORMAL DATA BY USE SIMULATING.". Kirkuk Journal of Science, 11, 4, 2016, 112-140. doi: 10.32894/kujss.2016.131068
HARVARD
Ali Hadba, W. (2016). 'COMPARISON METHOD PROCESS CAPABILITY INDICES FOR NORMAL AND NON-NORMAL DATA BY USE SIMULATING.', Kirkuk Journal of Science, 11(4), pp. 112-140. doi: 10.32894/kujss.2016.131068
VANCOUVER
Ali Hadba, W. COMPARISON METHOD PROCESS CAPABILITY INDICES FOR NORMAL AND NON-NORMAL DATA BY USE SIMULATING.. Kirkuk Journal of Science, 2016; 11(4): 112-140. doi: 10.32894/kujss.2016.131068