To path indicator Subpages of “Newsdetail“ To navigation To quick access To footer with other services
To content
Logo IPS
Faculty of mechanical engineering
Studierende sitzt am Arbeitsplatz und schaut auf den Laptop. © Aliona Kardash​/​TU Dortmund

Open-access book "Industrial Data Analysis" published with reports from science and practice

Übersicht über die Projektpartner © IPS​/​TU Dortmund
Collaborative anthology for the development of a data analysis platform for value-creating, competency-oriented collaboration in dynamic value networks. The publication of the book "Industrial Data Analysis" marks a significant advancement in the field of applied research and industrial practice. The book presents a comprehensive collection of contributions based on four years of research in the AKKORD project, addressing various aspects of the integrated and interconnected application of data analysis in dynamic value networks. In line with Open Science principles, the book is published in open-access format, meaning it is freely available.

The book "Industrial Data Analysis" presents a comprehensive compilation of contributions that illuminate the integrated and interconnected application of data analysis in dynamic value networks. With twenty contributions from over fifty authors from both academia and industry, the work offers a broad spectrum of topics and perspectives.

The contributions address various aspects of industrial data analysis, including methods and technologies, the integrated networking of production processes, innovative collaboration opportunities and business models, as well as the role of competency building and assurance in the industry. Through this diversity of topics, the anthology provides a solid foundation for further research and practical development in this field.

The research project underlying the publication of the anthology was conducted over a period of four years by fourteen consortium partners and supported by the Federal Ministry of Education and Research (BMBF) under the funding program "Industry 4.0 - Collaborations in Dynamic Value Networks (InKoWe)".

In conclusion, we would like to express our sincere thanks to all consortium partners and to all other supporting individuals and institutions. Without the diverse expertise, exceptional effort, and good cooperation, this book would not have been possible in its current form. We also extend our gratitude to all reviewers from the consortium who participated in the two-stage peer review process, thus contributing to ensuring the quality of the contributions and upholding the high scientific standards of the book.

We encourage the continued application and further development of the insights and solutions presented in the book in practice. The examples and concepts presented provide a solid foundation for shaping future developments in the field of industrial data analysis. It is our collective goal to fully harness the potential of these technologies and thereby contribute to strengthening the competitiveness of manufacturing companies. We hope that this work will contribute to advancing discourse and research in this area and look forward to further progress and developments in this field.

To top of page