Our new study published in the Journal of Manufacturing Technology Management offers groundbreaking insights to help industries successfully adopt Industry 4.0 technologies. This research is conducted by Linda Angreani and Annas Vijaya, both research associates and Prof. Dr.-Ing. Hendro Wicaksono, from Constructor University. It provides insights on how companies navigate the complexities of integrating advanced technologies such as automation and the Internet of Things (IoT) into their manufacturing processes.

Key Findings:

The study introduces a comprehensive maturity model designed to assess an industry’s readiness to adopt industry 4.0. By aligning this maturity model with well-established reference architecture models (RAMs) such as RAMI4.0, NIST-SME, IMSA, IVRA, and IIRA, companies can develop more effective strategies for implementing these cutting-edge technologies.

One of the significant findings is the identification of varied interpretations of Industry 4.0 maturity models within organizations. The research highlights the critical challenge of aligning these models with established RAMs, which is essential for a successful Industry 4.0 transformation. Additionally, the study reveals that both maturity models and reference architectures often overlook human and cultural aspects, which are vital for effective implementation.

This research is unique as it is the first to explore the alignment between maturity models and reference architecture models, offering valuable insights for companies striving to enhance their Industry 4.0 adoption strategies.

Implications for Industries:

The insights from this study can help industries overcome common obstacles in their Industry 4.0 journey. By utilizing the maturity model and aligning it with RAMs, companies can better understand their readiness and formulate more robust strategies for technology adoption. This approach promises to streamline the transformation process.

For a more detailed understanding of this research, the full paper is available for download here.