(static) process behavior (i.e., the process mean and variance are
constant) without the influence of the dynamic behavior (i.e., an
intended or unintended drift in the process mean or variance).
Traditional SPC methods have been successfully used in steadystate
manufacturing processes, but these approaches are not
valid for use in dynamic behavior environments. The standard
assumptions in SPC are that the observed process characteristics
are normally, independently and identically distributed (IID) with
fixed mean μ and standard deviation σ when the process is
in control. Due to the dynamic behavior, these assumptions are
not always valid. This study provides a scientific approach for
evaluating the capability of cold rolling processes (as an example
of manufacturing processes that undergo many disturbances and
dynamic behavior) so that quality improvement may be attained
because of the good understanding of the nature of the processes.
The paper proposes the appropriate procedures for evaluating the
capability of the manufacturing processes, especially for those
in a dynamic behavior mode, with a comparison between the
univariate and multivariate capability indices.