Anwendungspotenziale von maschinellem Lernen in der Produktion und Logistik

Abstract

Compared to other application domains, the use of artificial intelligence methods such as machine learning processes in production and logistics has so far been less widespread. With increasing networking through newly developed information and communication technologies as well as the use of sensor technologies and cyber-physical systems, however, data from production-related and logistics processes can increasingly be recorded in high resolution. The availability of extensive operating and sensor data holds great potential for optimization, which can be tapped using modern data analysis methods. In the recent past, therefore, a steadily growing interest in methods of artificial intelligence, especially machine learning, can be observed in the areas of production and logistics. In this regard, the challenge is to select the right machine learning algorithms for these application areas. This article gives an overview of the possible applications of machine learning and examines the application intensities of various machine learning algorithms in production and logistics as part of a literature review. Further research needs are derived from the knowledge gained.