Artificial Intelligence Support for Smart Logistics Systems in Industrial Environments

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Artificial Intelligence Support for Smart Logistics Systems in Industrial Environments

Nitsche, Anna-Maria / Runte, Chantal / Schumann, Christian-Andreas / Riedel, Ralph / Franke, Susanne

This paper investigates new roles of stakeholders in the context of the migration of circular value creation based on a collaborative model of logistic systems in an industrial environment. The evolving nature of supply networks and the underlying information systems as well as advances in technology drive the application of artificial intelligence (AI) in this context. The paper thus aims to harmonize and optimize the combination of classical methods with those of AI in hybrid planning and development systems.For this purpose, the connection of the design of the roles with the logistic processes in terms of a unified modeling is established. The design of the roles enables the generation of smart solutions in logistics. Aspects of data acquisition, data preparation, data storage, data analysis and data quality are considered to make qualified statements on the maturity level of AI support for logistics systems. The influence of collaboration and circular value creation on the interaction of AI and smart logistics systems in industry is investigated.In a systematic approach, based on the challenges for such smart systems, the tasks of smart logistics systems are derived, and evaluation approaches are presented. The paper thus contributes to the academic debate on approaches towards smart logistics as possibilities for the targeted use of AI methods and tools will be elaborated. For the use of the developed approaches, corresponding models and their applications in the industrial environment are selected and prepared as case examples for planning, development, and realization. Based on a complex model of logistic processes of smart systems, the preferred starting points for support by AI are shown.