An integrated System Dynamics model for strategic capacity planning in closed-loop recycling networks: A dynamic analysis for the paper industry

Recycling activities have demonstrated a remarkable increase over the last decade due to the economic and environmental dimensions of sustainability. In particular, capacity planning in production facilities has become a strategic issue of key importance affecting the profitability of the recycling industry.By integrating the simulation discipline and the feedback control theory into a dynamic consideration of recycling networks, this paper proposes a System Dynamics (SD) model for strategic capacity planning in the recycling industry. The decision-making process is based on a balanced tradeoff between profit and capacity utilization for a single producer with closed-loop recycling activities. The SD model captures physical stocks and flows apparent in real-world recycling networks and includes the feedback mechanisms which regulate these flows. When used as an “experimental tool”, the model tests alternative capacity planning policies and demonstrates policy suggestions for the forward and reverse channels, which maximize profitability over a strategic planning horizon. This experimentation is illustrated by using data from a paper producer with recycling activities, as a real-world test case. Extensive simulation runs, investigate the efficiency of a wide range capacity acquisition decisions, using total company profit as the measure of performance. Although such an analysis may differ from one recycling network to another, it has been kept as generic as possible to facilitate its applicability to a wide-spectrum of real-world local, regional or global networks.

► A System Dynamics model for closed-loop recycling networks is proposed.
► The SD model integrates strategic capacity planning and tests policy efficiency.
► The SD model is applied for the case of a paper producer with recycling activities.
► Simulation experimentation reveals best policies for forward and reverse channel.
► Additional simulation runs reveal insights about the total company profit.