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Item type:Publication, Access status: with files , Effects of design decisions on sustainability in product development: a case study for machine tools(Cambridge University Press (CUP), 2026-07-02); ; This study examines how product development activities influence the environmental sustainability of complex mechatronic systems using a 2D-flatbed laser cutting system as a case study. Three levels are identified, the machine, operation and part level, at which design changes can affect environmental sustainability during machine operation. Utilizing operational machine data, nine design changes are derived indicating that ∼36% of the environmental impact in the use phase can be reduced through technical design solutions, enabling EcoDesign principles supported by data-driven approaches.Publicationtype: Conference Paper23 18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Proof of performance for remote operations services of mechatronic systems(The Design Society, 2026); ; ; Rolle, MaximilianThis study develops a data-driven Proof of Performance to quantify productivity gains enabled by Remote Operations Support in complex mechatronic systems during operation. Remote Operations Support provides centralised, data-based monitoring and remote troubleshooting of machines, allowing error cases to be addressed without immediate on-site presence and thereby reducing downtime. The Proof of Performance operationalises productivity as additional running-state time between remote error resolution and the next error or the end of the shift, complemented by resolution-time segmentation to explain performance effects. Iterative refinement of report structure and KPI logic results in a robust measurement framework that supports consistent, comparable reporting. The developed Proof of Performance provides confirmation that Remote Operations Support can substantially enhance productivity improvement by accelerating recovery from disturbances and increasing productive machine time.Publicationtype: Conference Paper2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Data-driven system modelling in the system generation engineering(Cambridge University Press (CUP), 2025-08-27); ; ; This work develops a method to integrate operational data into system models following MBSE principles. Empirical analysis reveals significant obstacles to data-driven development, including heterogeneous and non-transparent data structures, poor metadata documentation, insufficient data quality, lack of references, and limited data-driven mindset. A method based on the RFLP chain links operating data structures to logical-level elements. Data analyses are aligned with specific requirements or functional/physical elements, enabling systematic data-driven modeling. This method improves efficiency, fosters system knowledge development, and connects technical systems with operational data.Publicationtype: Journal Article37 18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Methodological support in sustainable engineering through data-driven design of mechatronic systems(Cambridge University Press (CUP), 2025-08-27); ; ; Current legislative frameworks reflect a societal consensus to prioritize sustainability, incentivizing industries to integrate environmental goals into strategic objectives. Embedding sustainability into product development requires appropriate methods and tools. Technological advancements enable the utilization and analysis of operational machine data to support the development of new generations of sustainable systems and the conduction of Life-Cycle-Assessments. This research presents a method to support data-driven product development to reduce the environmental impact of new product generations of complex mechatronic systems during operation, addressing key factors such as the technical system, organizational infrastructure, and regulations. The application of the method resulted in multiple proposed design changes able to enhance machine sustainability and operational efficiency.Publicationtype: Journal Article33 21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Sustainable sheet-metal design: employing the Product Carbon Footprint as support for engineers in developing new roduct generations(Elsevier, 2025-04); ; ; ; This study investigates a data-driven approach for integrating sustainability criteria into the design process to reduce the Product Carbon Footprint (PCF) of sheet-metal parts. In a Live-Lab research environment, the design solutions of four engineering teams were analyzed at each iteration to assess how immediate PCF feedback and detailed sustainability information impacted both the design process and the final Product Carbon Footprint of the sheet-metal parts. The findings show that understanding the influencing factors of sustainable sheet-metal design and receiving PCF feedback led to PCF reductions of over 30 %, highlighting the importance of quantifiable sustainability metrics in industrial design practices.Publicationtype: Journal Article50 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Data-driven life cycle assessment for mechatronic systems: a comparative analysis of environmental impact assessments(Cambridge University Press (CUP), 2024-05); ; ; ; The growing emphasis on sustainability integrates eco-design and life cycle analysis into product development. Despite the value of LCAs, data limitations lead to assumptions, impacting accuracy. This study compares an estimation-based LCA with a data-driven approach, focusing on a laser machine's operational phase. The significant influence of resource consumption during operation underscores the necessity of optimization. Applying a data-driven approach reveals a 24% difference compared to the estimation-based method, emphasizing the challenges in obtaining accurate data for effective LCAs.Publicationtype: Conference Paper67 77 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Enhancing efficiency and environmental performance of laser-cutting machine tools: an explainable machine learning approach(Elsevier, 2024-05); ; ; This paper investigates the integration of sustainability and environmental performance in the development of machine tools. Through a literature review and a case study involving a fully automated solid-state laser-cutting machine tool, this research explores the potential of a data-driven, explainable machine learning (XML) approach to optimize machine tool operations for sustainability. Specifically, it addresses modeling resource consumption in laser-cutting machines, identifies the most significant factors influencing these models, and examines their contributions toward sustainable machine operation practices. Employing a combination of correlation analysis and stepwise linear regression for feature selection, and utilizing random forest regression models for predictive analysis, this study reveals that operational duration significantly impacts resource consumption levels, more than the effects of machine and laser configuration settings. The utilization of Shapely Additive Explanations (SHAP) further elucidates the predictive behaviors of these models, emphasizing the critical role of part contour length in program run duration and resource consumption. The findings suggest that optimizing machine speed and production planning, as well as incorporating part contour length as a sustainability Key Performance Indicator (KPI) during the design phase, can enhance the environmental performance of laser-cutting machines. Further, the analysis of resource consumption patterns of machine tools also offers actionable strategies to improve their sustainability during operation. It underscores the importance of integrating sustainability considerations into the development and operational phases of machine tools, contributing valuable insights to the field.Publicationtype: Conference Paper21 38 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Identification and evaluation of opportunities and risks for data-driven validation of systems of objectivesContemporary scientific research underscores the importance of data-driven validation within the product development process, particularly in relation to a system of objectives. Leveraging field-gathered machine data to inform decision-making in developing intricate mechatronic systems holds considerable promise. Despite the existence of various established models in the literature for data analysis, such as the widely adopted CRISP-DM process model for data mining, there remains a need for a specialized process model explicitly designed to assist developers involved directly in the product development process. This model should not only aid in conducting data analysis but also provide insights into the associated opportunities and risks inherent in the data analysis process. While it is tempting to focus solely on the potential benefits and opportunities offered by data analysis, it is equally essential to carefully consider the accompanying risks. Therefore, the objective of this study is to develop a systematic approach for evaluating both opportunities and risks in the data-driven validation of a system of objectives.Publicationtype: Conference Paper25 31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Methodical support for identifying and selecting data and analysis tools in the data-driven development of complex mechatronic systemsCurrent research shows that analyzing usage data from reference systems holds a high potential for product development. The process model for data-driven validation of systems of objectives supports developers in performing such data analyses. However, developers still struggle in the process of identification and selection of data and analysis tools. Thus, this work aims to develop methodical support in this process. nine expert interviews are conducted from which 15 influencing factors on the process are identified. Based on this methodical support is derived. For successful process execution, three areas of expertise are identified that must be covered regarding development domain, data, and conducting analysis. Developers have differing skills and thus require distinct levels of assistance in different process stages. To guarantee support to as many developers as possible while ensuring applicability and efficiency, five personas are derived covering frequently occurring expertise patterns. Furthermore, metadata documentation is identified as a central lever to reduce complexity in handling data, which in turn decreases dependency on experts. Thus, a consumer-focused data catalog concept is developed. Activity profiles are used to guide developers through the process while providing support at different stages as needed. Finally, the evaluation of the solution by conducting workshops with 15 developers shows an improvement of 41.7 percent in task accomplishment.Publicationtype: Conference Paper26 26 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Reference Architecture for Metadata Management - A Case Study on Data Mining in the Development of Cyber-Physical SystemsIn the domain of mechatronic system development, there exists a significant potential for the collection and utilization of vast amounts of operational data. The practical implementation of this potential presents considerable opportunities, although accompanied by substantial challenges. While some companies have already gathered large volumes of data, they are yet not able to utilize its full potential for optimizing technical systems. An essential factor in enabling developers to effectively leverage operational data lies in ensuring accessibility to the data and facilitating intuitive navigation within the database structures. This article examines the prerequisites for a database structure that can be intuitively utilized by developers as end-users. Using the example of a machine tool manufacturer, an architecture for metadatabases is presented, which incorporates user involvement in the architecture development process and is implemented within the research environment of the present research work. A comparative analysis against the pre-existing metadatabase architecture reveals significant enhancements in the usability of metadata for developers.Publicationtype: Conference Paper45