Structured surfaces at the micro- and nanoscale enable precise control of cell–material interactions in tissue engineering and regenerative medicine (TERM). This keynote examines scalable manufacturing methods for 2D substrates, 3D scaffolds, and implants, analyzing relationships between topography, biological performance, and process efficiency. Key technologies include nanoimprint lithography, micro injection molding, high-resolution additive manufacturing, and ultrafast laser texturing. Strategies for combining biological efficacy with cost-effective production are presented, along with multifunctional designs for osseointegration and antibacterial activity. Future perspectives address biomimetic and patient-specific structures, process–function modeling, and smart materials to support advanced TERM applications and clinical translation.
Many critical manufacturing processes in sheet metal forming are characterized by shear-dominated mechanisms. By clearly defining how shear-dominated processes can be classified based on stress triaxiality and the Lode parameter, this paper provides an overview of their characteristics and challenges in sheet metal forming. Based on the distinction into in-plane and out-of-plane shear-dominated processes and an introduction to the mechanical fundamentals of shearing mechanics, the topics of testing and measurement methods, simulation, and tooling are discussed. Finally, concepts and principles are illustrated with specific application examples. The paper concludes with open topics and upcoming challenges.
Industrial maintenance plays a critical role in enabling complex assets such as production equipment and more widely factories to be available for use in a sustainable manner. With the emergence of digital technologies such as digital twins, IoT, virtual and augmented reality, and machine learning, significant opportunities are observed to transform the way in which maintenance is delivered. It is anticipated that maintenance will become more affordable, proactive, predictive, outcome driven and sustainable in the future. This paper presents the state of the art and industrial perspectives on digitally enhanced maintenance covering current approaches and challenges. Furthermore, a comprehensive framework is presented to structure future research directions by considering the concept of a maintenance ecosystem. Finally, a strategic vision is set out to convey the future of maintenance.
4H-SiC wafers require damage-free, ultra-smooth surfaces for power devices manufacturing, whereas conventional chemical mechanical polishing (CMP) often suffers from limited throughput and high cost. Slurry-less electrochemical mechanical polishing (ECMP) enables efficient smoothing with low cost, but surface scratches still limit surface integrity and yield. This study systematically observed and classified surface morphologies formed on 4H-SiC under different ECMP conditions, including conventional groove-type scratches and ECMP-specific ridge-type traces, and elucidated the mechanisms underlying each type. Based on these insights, practical process-optimization strategies were proposed to suppress trace formation and improve slurry-less ECMP stability and applicability.
Hardness is a critical surface integrity metric governing the performance of machined components. Due to experimental constraints, hardness characterization typically relies on sparse measurements, limiting spatial resolution and generalization across machining conditions. This work addresses this limitation by introducing a physics-informed graph transformer for hardness prediction in milling, using process parameters and in-situ power signals. To mitigate data scarcity, power signals are synthesized, and a graph representation is constructed to embed machining physics and measurement relationships. Data analysis demonstrates robust and generalizable prediction under limited reference data, establishing a soft sensing framework for scalable characterization of hardness from milling operations.
