Optimizing the automated production network of Swappie

Abstract

This paper delves into the intricate design and significance of global manufacturing networks, highlighting the evolving challenges and strategic considerations faced by companies in establishing resilient and efficient operational models across international markets. The paper investigates the historical progression of these networks, reflecting on how events, like the industrial revolutions and global conflicts, have changed their development and strategies. Through an in-depth analysis of Swappie's manufacturing network, this study explores the integration of automation for cost optimization and analyzes key considerations involved in expanding production sites into foreign markets.

This paper researches the challenges introduced by global and geopolitical risks, alongside supply chain disruptions, providing insights into the development of networks capable of withstanding external pressures while maintaining flexibility in the face of dynamic market and customer demands. Contemporary manufacturing trends, especially those shaping Swappie's business model, including circular economy, Industry 4.0, and the shift toward automation and robotics, are comprehensively examined.

Ultimately, a model is developed using the Python library PuLP, aimed at supporting strategic internationalization decisions by creating a minimization algorithm that considers automation in the production network. This inquiry substantiates how difficult it is for companies to create robustness in their production network without incurring high fixed costs from low utilization factories. Furthermore, it is seen how large an impact logistics lead times have on the capital tied in inventory and its impact on value depreciation of stock. Overall, the model provides Swappie with a framework to simulate different scenarios and plan their future expansion endeavors.