Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics.

Die intelligente Steuerung von Supply Chains ist eine wesentliche Voraussetzung für die Erschließung der Potenziale neuer digitaler Technologien. Im folgenden Beitrag wird Smart Logistics als Komponente von Industrie 4.0 und in ihren Zusammenhängen zu anderen Komponenten dargestellt. Es werden Technologiekonzepte der Smart Logistics beschrieben. Darauf aufbauend werden Nutzungspotenziale und mögliche weitere Entwicklungen analysiert. Als Ergebnis eines internationalen Projektes werden weiters die Voraussetzungen dargestellt, die in Unternehmen für die Einführung von Smart Logistics gegeben sein müssen. The intelligent control of supply chains is an essential prerequisite for exploiting the potential of new digital technologies. In the following paper, Smart Logistics will be discussed as a component as well as in its relationship to other components within an Industry 4.0 framework. Technology concepts of Smart Logistics are described. Based on this, potential applications and possible further developments are analyzed. As a result of an international project, the requirements that must be met in companies for the introduction of smart logistics are presented.

Based on expert interviews and case studies, the authors investigate requirements for small- and medium-sized enterprises (SMEs) to support logistics management with Industry 4.0 concepts, in the context of mass customization and global supply chain challenges. In an exploratory field study, specific requirements of SMEs from Europe, the United States of America, and Thailand to use Industry 4.0 concepts in their logistics management are analyzed. By using Axiomatic Design, customer needs for the design of smart and intelligent logistic systems can be translated into a hierarchy of functional requirements and corresponding physical solutions while maintaining functional independence and minimizing information content. The determined functional requirements are used as a basis to define design guidelines for suitable Industry 4.0 concepts to support the logistics management process. Keywords Small- and medium-sized enterprises SME Industry 4.0 Requirement analysis Logistics

Industry 4.0 technologies enable the automation of information and material flow processes in logistics systems. Automation strategies can be used to increase the efficiency of internal transport, transition, and storage processes, and, moreover, improve service levels and thus strengthen competitiveness. Besides the material flow processes, automation based on state-of-the-art technologies, e.g., cyber-physical system (CPS), Internet of Things (IoT), and physical internet (PI), serves to optimize information flow in logistics processes. This chapter analyzes the importance and potential of effective and efficient logistics operations and outlines enabling technologies for automation in logistics systems. Based on a literature review, the authors discuss both technologies that have already reached market maturity and technologies which have high potential but still require future research and development.