Many complex assembly lines, such as those in the automobile industry,
have dozens or hundreds of stations that are affected by customer-sel
ected options on the jobs being assembled. The various options often r
equire significantly different amounts of processing time, and the rol
e of assembly line sequencing in this context is to smooth out the flo
w of work to each station. However, most assembly line sequencing algo
rithms developed for such situations cannot consider so many stations
or options effectively. In this paper, we develop an analytical method
to compute a criticality index for each station, which can be used to
determine which stations are most important to include in an assembly
line sequencing algorithm. We report computational results using actu
al industry data which indicates that substantial improvements can be
obtained by selecting stations based upon this criticality index.