Optimizing warehouse operations using automation and artificial intelligence

Abstract

Modern customer requirements in different fields require companies to adapt to the ever-changing situations. The field of logistics is by no means exempt from this. Companies with warehouses around the world need to be able to react quickly to orders that could be sent halfway across the world. This thesis examines the possibilities that companies have, to optimize their operations to match the requirements of the modern world. The focus point is the optimization of operations with the usage of automation and artificial intelligence. This paper will also present examples of issues with a benchmark company that could possibly be solved by implementing automatized processes into their operations along with artificial intelligence.

The findings presented in this thesis include the adoption of automated warehouse management systems to improve the collecting efficiency. It will also demonstrate the benefits of implementing automated storage and retrieval systems that evidently reduce the amount of spoilage and improve the storage, shipping and picking accuracy. The benefits of artificial intelligence are introduced. They include optimized route planning for the collecting phase as well as increased accuracy in inventory planning.

Overall, this thesis demonstrates on a theoretical level, why adopting automation and artificial intelligence should be considered by all warehouse managers. The vast benefits and solutions that are presented in the findings from previous literature are finally compared to the operations of the benchmark company and they provide insight as to why at least the benchmark company should further investigate the possibilities of adopting automated systems along with artificial intelligence into their operations.