Systematic Digitalization of a Value Chain from Raw Material to Recycling
Research output: Thesis › Doctoral Thesis
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2023.
Research output: Thesis › Doctoral Thesis
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TY - BOOK
T1 - Systematic Digitalization of a Value Chain from Raw Material to Recycling
AU - Sorger, Marcel
N1 - no embargo
PY - 2023
Y1 - 2023
N2 - The introduction of Industry 4.0 in 2011 resulted in a paradigm shift in the industry that continues to this day. In the course of this digital transformation, established or newly developed technologies have been implemented in the industry and corresponding concepts have been discussed scientifically, yet specific digitalization approaches for the metal forming industry are not sufficiently addressed. As an initial step, a literature review on the state of the art was conducted to evaluate the current state of digitalization and digital transformation in the manufacturing industry in relation to the value chain and individual companies. The lower level of digitalization in Small and Medium Sized Enterprises (SMEs) compared to other industries is due to machinery that is often no longer up to date, the digitalization of which nevertheless is economically sensible. To also be able to integrate SMEs into a digitalized value chain, standardized yet individual digitalization concepts must be developed, which is why the MUL 4.0 project was initiated - an interdisciplinary cooperation to depict the digitalization of an industry-related value chain. In order to best design the digitalization solutions for SMEs, the machines and aggregates were equipped with suitable low-cost sensors, data acquisition systems and software for process simulation and prediction, transforming them into Cyber Physical Production Systems. Due to the high complexity and high diversity of forming operations, different process modeling approaches were applied, which were realized by specially developed real-physics numerical simulations and data-driven Machine Learning models. Furthermore, Graphical User Interfaces were developed to enable Human Machine Interaction, visualizing relevant information and thus supporting the decision-making process. In order to be able to map the digitalized value chain and to ensure the data governance and interoperability of the cooperating entities, a superordinate production network incorporating a Data Base Management System was implemented. For all solution approaches, open-source programming language were used to the highest possible extent due to the high interoperability and connectivity to other software solutions, avoiding interface problems and the resulting proprietary solutions. As a result of this work, a standardized framework was developed, applicable for the digitalization of SMEs in the metal forming industry. This framework was developed with a special focus on open-source programming languages, cost-effectiveness, standardization and resilience to support SMEs in this industry with the implementation of Industry 4.0, to increase the sustainability of products and processes, and to ensure economic competitiveness in the future.
AB - The introduction of Industry 4.0 in 2011 resulted in a paradigm shift in the industry that continues to this day. In the course of this digital transformation, established or newly developed technologies have been implemented in the industry and corresponding concepts have been discussed scientifically, yet specific digitalization approaches for the metal forming industry are not sufficiently addressed. As an initial step, a literature review on the state of the art was conducted to evaluate the current state of digitalization and digital transformation in the manufacturing industry in relation to the value chain and individual companies. The lower level of digitalization in Small and Medium Sized Enterprises (SMEs) compared to other industries is due to machinery that is often no longer up to date, the digitalization of which nevertheless is economically sensible. To also be able to integrate SMEs into a digitalized value chain, standardized yet individual digitalization concepts must be developed, which is why the MUL 4.0 project was initiated - an interdisciplinary cooperation to depict the digitalization of an industry-related value chain. In order to best design the digitalization solutions for SMEs, the machines and aggregates were equipped with suitable low-cost sensors, data acquisition systems and software for process simulation and prediction, transforming them into Cyber Physical Production Systems. Due to the high complexity and high diversity of forming operations, different process modeling approaches were applied, which were realized by specially developed real-physics numerical simulations and data-driven Machine Learning models. Furthermore, Graphical User Interfaces were developed to enable Human Machine Interaction, visualizing relevant information and thus supporting the decision-making process. In order to be able to map the digitalized value chain and to ensure the data governance and interoperability of the cooperating entities, a superordinate production network incorporating a Data Base Management System was implemented. For all solution approaches, open-source programming language were used to the highest possible extent due to the high interoperability and connectivity to other software solutions, avoiding interface problems and the resulting proprietary solutions. As a result of this work, a standardized framework was developed, applicable for the digitalization of SMEs in the metal forming industry. This framework was developed with a special focus on open-source programming languages, cost-effectiveness, standardization and resilience to support SMEs in this industry with the implementation of Industry 4.0, to increase the sustainability of products and processes, and to ensure economic competitiveness in the future.
KW - Industry 4.0
KW - Digitalization
KW - Digital Transformation
KW - SME
KW - Metal Forming
KW - Industrie 4.0
KW - Digitalisierung
KW - Digitale Transformation
KW - KMU
KW - Umformtechnik
U2 - 10.34901/mul.pub.2023.184
DO - 10.34901/mul.pub.2023.184
M3 - Doctoral Thesis
ER -