Industry 4.0 is a ubiquitous term throughout general newspapers, on company websites or in scientific journals. One of its key constructs is the smart factory, envisioned as a future state of a fully connected manufacturing system, mainly operating without human force by generating, transferring, receiving and processing necessary data to conduct all required tasks for producing all kinds of goods. Although the understanding of smart factory concepts has been sharpened in the last years, it is still difficult for industrial companies to establish a concrete strategy roadmap within the jungle of different terminologies, ideas and concepts. To generate further clarity and to consolidate the previous findings around smart factory for researchers as well as for practitioner, we conducted a systematic literature review. For this purpose, we chose a five steps approach: Scope definition, topic conceptualisation, literature search, literature analysis and synthesis, and synthesis of future research questions. During our review, we found that research within each perspective is fragmented and unequally advanced. Most publications treat single use cases with low generalizability, often rely upon machine data, typically have a technical nature and seldom incorporate impact estimations. In this paper, our key academic and practical contribution lies in the categorisation of the selected publications into eight thematic distinct perspectives within the sphere of smart factory: Decision making, cyber-physical systems, data handling, IT infrastructure, digital transformation, human machine interaction, IoT, and cloud manufacturing and services. These are further developed into the smart factory research model, stating a foundation for future research endeavors. •Systematic literature review and analysis of 106 papers within smart factory.•Research around the smart factory construct is heterogeneous and unequally advanced.•Most articles treat single use cases with low generalizability.•The articles often rely upon machine data and typically have a technical nature.•Categorisation into eight perspectives by applying qualitative coding techniques.