Roadmap to Digital Factories in Industry 4.0: Insights from multiple case studies

Abstract

This study investigates the transformation process toward Digital Factories (DF) in the context of Industry 4.0. Specifically, it examines how companies may structure and segment the DF adoption process, how specific organizational objectives influence implementation, and what a recommended roadmap looks like for different DF types. A multiple case study analysis was conducted with 21 companies, including manufacturers and technology providers. Data collection was based on semi-structured interviews, document analysis, and direct observations, with a content analysis approach used to identify patterns, relationships, and technological enablers across the cases. The findings present a conceptual model linking supportive technologies, complexity levels, and organizational objectives, identifying four types of DF: Digital Model (DM), Digital Shadow (DS), Digital Twin (DT), and Industrial Metaverse (IM). The study demonstrates that companies adopt modular digital transformation strategies, integrating key technologies such as IoT, real-time analytics, AI, and extended reality in a structured sequence. The IM is introduced as a cross-cutting element that enhances human interaction and collaboration at any DF type. This study contributes to the literature by providing a structured framework for DF implementation and empirically validating DF classifications through real-world cases. The introduction of IM extends existing models, emphasizing a human-centered digital transformation. The proposed roadmap serves as a strategic guide for managers, helping them assess digital maturity, align DF adoption with business objectives, and prioritize technological investments.