Industry is undergoing profound transformation driven by data-intensive technologies, interconnected systems and value-chains, advanced automation, artificial intelligence, autonomous digital and cyber-physical systems, and innovation. In the era of Industry 4.0 and 5.0, digital transformation is reshaping organization structures, production environments, supply networks, and business models.
Digital transformation is not only a technological endeavor. It is a continuous strategic transition that embraces culture, skills, processes, regulations, and value creation. Successful implementation requires holistic and long-term visions, covering aspects such as leadership, cross-disciplinary collaboration, technology and business alignment, technical and human resources capability development, change management, sustainability, and governance.
The goal of this research topic is to showcase cutting-edge research and theoretical insights, case studies and empirical evidence, methodologies and conceptual advances that illuminate the opportunities, challenges, and impacts of digital transformation and cognitive evolution in industrial settings from all sectors.
Topics of interest include:
1. Strategic and Organizational Issues: business models, change management, digital transformation roadmaps and related digital transformation management approaches, maturity-capability-readiness-assessment models, supporting methodologies for digital transformation, performance indicators and evaluation, sustainability, business models.
2. Technological and Integration Issues: legacy systems interoperability, vendors lock-in, technology selection, cybersecurity, Industry 4.0-5.0 enabling technologies (AI, bigdata, robotics, digital twins, cloud-fog-edge computing and data spaces, etc.), human-system-machine interactions, enterprise architecture, open architectures, digital services-based ecosystems, vertical and horizontal integration at intra- and inter-organizational levels.
3. Data and Analytics Issues: data science, real-time data processing, data standards, data models.
4. Human and Workforce Issues: skilling and training, job and working places redesign and ergonomics.
5. Smart Factories Issues: Industrial Internet of Things (IIoT), Cyber-Physical Systems, reconfigurable manufacturing systems, emergent planning, collective intelligence, collaborative systems.
6. Regulatory and Ethical Issues: compliance with industrial and data regulations, data privacy, safety, ethical use of data and automation, decisions driven by algorithms.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
Hypothesis and Theory
Methods
Mini Review
Original Research
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Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
Hypothesis and Theory
Methods
Mini Review
Original Research
Perspective
Review
Technology and Code
Keywords: digital transformation, Industry 4.0, Industry 5.0, smart factory, cyber-physical systems (CPS), Industrial Internet of Things (IIoT), digital twins, big data analytics, edge–fog–cloud computing, interoperability, AI in manufacturing, change management
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
