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PublicationData-driven indirect punch wear monitoring in sheet-metal stamping processes( 2024)The wear state of the punch in sheet-metal stamping processes cannot be directly observed, necessitating the use of indirect methods to infer its condition. Past research approaches utilized a plethora of machine learning models to infer the punch wear state from suitable process signals, but have been limited by the lack of industrial-grade process setups and sample sizes as well as their insufficient interpretability. This work seeks to address these limitations by proposing the sheared surface of the scrap web as a proxy for the punch wear and modeling its quality from acoustic emission signals. The experimental work was carried out in an industrial-grade fine blanking process setting. Evaluation of the model performances suggests that the utilized regression models are capable of modeling the relationship between acoustic emission signal features and sheared surface quality of the scrap webs. Subsequent model inference suggests adhesive wear on the punch as a root cause for the sheared surface impairment of the scrap webs. This work represents the most extensive modeling effort on indirect punch wear monitoring in sheet-metal stamping both from a model prediction and model inference perspective known to the authors.
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PublicationQuantifizierung der Auswirkungen auf die Nachhaltigkeit( 2023-05-05)Die Nachhaltigkeit der globalen Wirtschaft ist zu einem kritischen Aspekt für Politik und Wirtschaftsinvestitionen geworden, wobei die UN-Agenda 2030 für nachhaltige Entwicklung spezifische Ziele und Indikatoren für nachhaltige Entwicklung festlegt. Während die (CO)_2 -Reduktion aktuell ein primärer Fokus ist, müssen auch andere Ziele wie Wassermanagement oder soziale Ziele berücksichtigt werden. Die Wechselwirkung zwischen Nachhaltigkeitszielen und Indikatoren zu verstehen, ist jedoch komplex. Die Komplexität der Auswirkungen von Technologien auf die Nachhaltigkeitsziele kann anhand eines aktuellen Beispiels in der Automobil-Stahl-Lieferkette veranschaulicht werden. In dieser Branche sind der Energieverbrauch und die Kohlenstoffemissionen hoch, und daher sind innovative Technologien erforderlich, um den Übergang zu einer auf Nachhaltigkeit ausgerichteten Lieferkette zu unterstützen. Gleichzeitig durchläuft die Branche enorme Veränderungen, die traditionelle Geschäftsmodelle aufgrund des Übergangs zur Produktion nachhaltiger Produkte oder der Umsetzung nachhaltiger Betriebsabläufe beeinflussen. Die Betrachtung eines Beispiels für die Erfassung, Nutzung und gemeinsame Nutzung von Materialdaten zur Verbesserung der Zusammenarbeit entlang der Lieferkette und zur Reduzierung von Ausschuss zeigt die derzeitige Komplexität bei der Bewertung der Einführung solcher Ansätze im größeren Maßstab. Aufgrund der Schwierigkeiten, den tatsächlichen Einfluss einer Maßnahme oder Technologie zu quantifizieren, müssen Entscheidungen über den Übergang zu nachhaltigen wirtschaften auf Intuition anstatt auf konkret quantifizierte Auswirkungen basieren. Innovationsentscheidungen müssen die persönliche Verantwortung für die Nachhaltigkeit von der Produktionsunternehmen berücksichtigen.
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PublicationQuantification of Sustainability Impact( 2023-05-05)The global economy's sustainability has become a critical aspect for politics and economic investments, with the UN 2030 Agenda for Sustainable Development outlining specific targets and indicators for sustainable development. While (CO)_2 reduction is a primary focus, other goals such as water management or social goals must be considered. However, understanding the interaction between sustainability targets and indicators is complex. The complexity of sustainability impact of technology or measure can be illustrated by recent example in the automotive steel supply chain. Here, the current impact on energy consumption and carbon emissions are high, and therefore, innovative technologies are needed to support the transition into a sustainability focused supply chain. Simultaneously, the industry is undergoing tremendous changes that impact traditional business models due to the shift to either production of sustainable products, or implementation of sustainable operations. The consideration of an example in material data acquisition, utilization and sharing to enhance collaboration throughout supply chain and reduce waste shows the current of complexity of assessing the introduction of such approaches on a broader scale. Yet, due to the difficulties to quantify the actual impact of a measure or technology, decisions on transitioning to sustainable operations must be based on intuition rather than a concretely quantified sustainability impact, as assessing these impacts is currently beyond available capacity. Innovation decisions must consider personal responsibility for the sustainability of production and the economy.
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PublicationThe digital twin in battery cell production( 2023-01-11)
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PublicationDer Digitale Zwilling in der Batteriezellfertigung( 2023-01-10)
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PublicationStudy on learning efficient stroke representations in clocked sheet metal processing: theoretical and practical evaluation( 2023)Clocked manufacturing processes such as sheet metal forming and cutting processes pose a challenge for process monitoring approaches due to inaccessibility of tool components and high production rates which make direct measurement of the physical process conditions unfeasible. Auxiliary data such as force signals are acquired and assessed, often still relying on control and run charts or even visual control in order to monitor the process. The data of these signals are high-dimensional and contain a large amount of redundant information. Therefore, the processing of such signals focuses on compressing information into as few variables as possible that still represent the important information for the manufacturing process. Due to repeatability in clocked sheet metal processing, the data generated consist of a series of time series of the same operation with varying physical conditions due to wear and variations in lubrication or material properties. In this paper two major research objectives are identified: (i) the theoretical evaluation of representation learning methods in context of clocked sheet metal processing, and the connection with (ii) the practical evaluation of the learned representations with a given use case to track the wear progression in series of strokes. The contribution of this paper is the comparison of varying time series representation learning techniques and their performance evaluation in a theoretical and practical scenario.
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PublicationMonitoring of fluctuating material properties for optimizing sheet-metal forming processes: a systematic literature review( 2023)Material properties can vary both along a sheet-metal coil and from coil to coil despite tight tolerances influencing the process stability of sheet-metal processes and the part quality, which leads to rejects and machine downtime [1]. This significantly affect the economic efficiency of the process. Monitoring fluctuations in material characteristics at regular intervals along sheet-metal coils is enabled directly by non-destructive testing (NDT) before the process offering conclusions on the material properties. Another material monitoring technique arises from monitoring process conditions of the upstream processes, e.g., cold rolling, leading indirectly to insights on material properties. In this work, a systematic literature review (SLR) [2] is conducted to investigate recent approaches for material monitoring and for the utilization of resulting material data for optimizing different sheet-metal forming processes. Existing approaches for different sheet-metal forming processes are critically appraised. Based on the SLR research gaps are revealed and research opportunities, e.g., arising from a potential transfer of existing solutions between different forming processes and recent advances in data-driven methods, are identified.
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PublicationDigitalized manufacturing process sequences - foundations and analysis of the economic and ecological potential( 2022)As a consequence of the increasing digitalization of production, the availability of data from individual manufacturing processes and components is rising continuously. Digitalization affects various levels of production, such as the design of manufacturing processes, technology planning, quality monitoring, or logistics control. The contribution of this paper is to present the foundations for digitalized manufacturing process sequences and to develop data-based models and methods for the design of economically and ecologically optimized process sequences. For this purpose, a procedure for cross-process life cycle assessment was developed and carried out in order to evaluate the various ecological effects resulting from manufacturing and, in particular, different process designs. This ecological evaluation was combined with the evaluation of economic efficiency in order to provide an integrated evaluation as the basis for the design of manufacturing process sequences. In addition, the effects of the individual manufacturing process designs or process parameters on component quality were analyzed and an approach was derived for determining cross-process dependencies. The basis for these developments is a process sequence for the manufacture of pinion shafts used in electric car gearboxes. This digitalized process sequence consists of the processes soft cutting, gear hobbing, case-hardening, cylindrical grinding, and gear grinding, and over 100 components were manufactured with various process designs. This enabled an extensive amount of process and quality data to be collected throughout the process sequence. The application of the developed methods to the aforementioned process sequence underlines the high potential for the optimization of the target parameters quality, economy and ecology through cross-process analyses of digitalized manufacturing process sequences. Finally, an outlook on further developments regarding the digitalization of manufacturing process sequences is given.
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PublicationHow Distributed Ledger Technologies affect business models of manufacturing companies( 2021)Industry 4.0 is characterized by the transformation and networking of production systems as a result of utilizing digital technologies and processing huge amounts of data. The features of Distributed Ledger Technologies have the potential to revolutionize production by creating trust and transparency in stored data, eliminating dependence on single entities and performing automated transactions in real time. Due to the disruptive change coming with an implementation, manufacturers remain skeptical about the technology. To raise awareness of the potential of Distributed Ledger Technology, this paper describes valid use cases and examines the interactions with business models in real world manufacturing scenarios.
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PublicationMonetarisierung von Fertigungsdaten( 2020)Eine Monetarisierung von Fertigungsdaten ermöglicht Unternehmen der fertigenden Industrie eine Steigerung ihrer Produktivität und Nachhaltigkeit. Neben dieser Optimierung bestehender Geschäftsmodelle können Unternehmen durch eine Monetarisierung von Fertigungsdaten gleichzeitig neue Einkommensströme erschlossen werden durch neue digitale und progressive Geschäftsmodelle. Durch Fortschritte im Bereich der Künstlichen Intelligenz und der Datenverarbeitung können Erkenntnisse aus Fertigungsdaten gezielt gewonnen und im Rahmen von Daten-Allianzen ausgetauscht werden. In diesem Beitrag werden verschiedene Stufen der Datenverwertung von der Wissensgenerierung bis hin zur Monetarisierung dieser Daten konzipiert, technische Grundlagen dargestellt sowie resultierende Potenziale, Hindernisse und deren Lösungen diskutiert und anhand praxisorientierter Anwendungsfälle verdeutlicht. Abschließend werden Handlungsempfehlungen für Unternehmen der fertigenden Industrie abgeleitet und eine potenzielle Monetarisierungsstrategie für Fertigungsdaten ausgelegt.
