Background: The short life cycle of the product, unpredictable demand patterns and the everincreasing reduction of time to market have caused manufacturing companies to be under pressure.
For this purpose, to face these complex production scenarios, these companies have turned to
implementing cellular manufacturing systems (CMs), which reduce production costs, increase
flexibility and quick response to market demand.
Aim: One of the important issues in CMs is the dynamic nature of the system due to the different
product mix or change in the demand volume, which has led to the introduction of the dynamic
cell formation problem. For this purpose, in this study, the design of dynamic cell formation by
considering unreliable machines and production planning has been discussed. The studied problem
seeks to minimize the costs of intra- and inter-cell transportation, reconfiguration, machine
breakdowns, part production, part storage in the warehouse, and part back order in production
periods.
Methodology: At first, a mixed integer nonlinear programming mathematical model was
presented for the considered problem. Then, it was linearized and validated with a case study in
GAMS software with GUROBI solver. In the following, the impact of moving machines between
periods and the sensitivity analysis of the number of breakdowns were discussed.
Conclusions: The results show the correctness and validity of the model. The findings of the
research showed that flexibility in routing, optimal grouping of machines in each period and
optimal location of cells improves the objective function from the existing state to the desired state
by 3.2 percent. Next, the sensitivity analysis of MTBF showed that the number of failures has an
effect on the system performance and the amount of meeting customer demand