Production Flow Analysis (PFA) is a manual method that helps a company to i
dentify sources of delay in material flows due to complex operation sequenc
es, size of parts population, variety of machines (or number of departments
), poorly designed facility layouts, incorrect choice of machines for opera
tions, etc. This paper describes a set of algorithms which seek to automate
the different phases of analysis in this classical design method for Cellu
lar Manufacturing and Facility Layout. The algorithms for PFA use a variety
of forms of input data-Travel Chart, Operation Sequences or a Machine-Part
matrix. In particular, this paper describes an enhanced machine-part matri
x clustering (MPMC) algorithm to automate the Group Analysis phase of PFA.
The improved clustering effectiveness and computational benefits due to the
enhancements in this MPMC algorithm are demonstrated. Extensive experiment
s using test matrices from the literature and industry have been conducted.