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.

Industry 4.0 has attracted the attention of manufacturing companies over the past ten years. Despite efforts in research and knowledge transfer from research to practice, the introduction of Industry 4.0 concepts and technologies is still a major challenge for many companies, especially small and medium-sized enterprises (SMEs). Many of these SMEs have no overview of existing Industry 4.0 concepts and technologies, how they are implemented in their own companies, and which concepts and technologies should primarily be focused on future Industry 4.0 implementation measures. The aim of this research was to develop an assessment model for SMEs that is easy to apply, provides a clear overview of existing Industry 4.0 concepts, and supports SMEs in defining their individual strategy to introduce Industry 4.0 in their firm. The maturity level-based assessment tool presented in this work includes a catalog of 42 Industry 4.0 concepts and a norm strategy based on the results of the assessment to support SMEs in introducing the most promising concepts. For testing and validation purposes, the assessment model has been applied in a field study with 17 industrial companies.

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Industry 4.0 (I4.0) approaches, frameworks, and technologies have gained an increasing relevance in order to gain sustainable and competitive advantages for industrial enterprises and for small and medium enterprises (SMEs), as well. Contrary to previous studies, which are mainly focused on companies, we conducted a questionnaire-based survey on inhabitants, in an attempt to examine general awareness about I4.0 concepts, in the region of South India. Our findings revealed a rather poor informational level of I4.0 concept and its components, which consequently leads to inadequate future actions and expectations. Moreover, respondents with prior information about I4.0 framework tend to have rather positive opinions and expectations of possible future trends. We emphasize that insufficient knowledge of the potential workforce regarding I4.0 concepts, especially in a region with ascending demographic development, can be considered as one of the main barriers for a successful and sustainable future development towards the 4th industrial revolution.

Zusammenfassung: 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.