In this study, a mathematical programming approach is proposed to design a layered cellular manufacturing
system in highly fluctuated demand environment. A mathematical model is developed to create
dedicated, shared and remainder cells with the objective of minimizing the number of cells. In contrast
with classical cellular manufacturing systems, in layered cellular systems, some cells can serve to multiple
part families. A five-step hierarchical methodology is employed: (1) formation of part families, (2) calculation
of expected cell utilizations and demand coverage probabilities, (3) specification cell types as
dedicated, shared, and remainder cells, (4) simulation of proposed layered systems to evaluate their performance
with respect to average flowtime and work-in-process inventory, and (5) statistical analysis to
find the best layered cellular design among alternatives. It is found that designs with higher number of
part families tend to have less number of machines. Similar results are also observed with respect to average
flowtime and work-in-process inventory measures. The results are also compared with a heuristic
approach from the literature. None of the approaches is dominant with respect to all of the performance
measures. Mathematical modeling approach performs better in terms of number of machines for most of
the alternative designs. However, heuristic approach yields better average flowtime and work-in-process
inventory for most of the designs.