A new whitepaper produced as part of the Center of Excellence now presents the basics of AI as well as current developments and future fields of application for AI in logistics and discusses them in terms of application maturity. Particularly exciting for practitioners are also the examples of machine learning in the areas of »analysis tasks in logistics«, »planning and decision tasks in logistics« and »execution tasks in logistics«. A short »checklist« shows how companies in particular can best start machine learning projects – based on the experience gained from numerous practical cases and, not least, the now »avoidable errors« associated with them.
Providers of commercial solutions and research institutions promise that Artificial Intelligence (AI) – especially Machine Learning (ML) – can be used to perform a wide range of tasks in logistics more economically and with fewer resources. In their paper, the authors Anike Murrenhoff, Martin Friedrich and Dr. Markus Witthaut, all from the Fraunhofer Institute for Material Flow and Logistics IML, thus also come to the conclusion that the potential applications of AI in logistics are as diverse as the tasks of logistics itself: »The opportunities for using resources more efficiently, improving logistics services and enabling new business models through AI in logistics are considerable. It is important to increasingly bring this potential into practice, especially with agile approaches.«
The whitepaper has been published in Fraunhofer IML’s »Future Challenges in Logistics and Supply Chain Management« series. The series addresses current challenges, highlights trends and focuses on novel technologies and business models.
Click here download the paper (german version only).
