Bosch

In the era of environmental degradation and resource scarcity, the concept of circular economy (CE) has emerged as a pivotal strategy to transform the contemporary industrial landscape. As an integral component of the 10R framework, remanufacturing is emerging as a production strategy that revitalizes end-of-life (EOL) products to a like-new condition, fostering a more sustainable production and consumption. Despite its immense environmental and economic benefits, the implementation of remanufacturing practices is confronted with a multitude of challenges, including sourcing of EOL products, managing component variability, and arbitrary failure rates that result in major process inefficiencies. This paper embarks on the definition of functional and non-functional requirements for remanufacturing production planning and control (RPPC) to establish a systematic approach to address the existing challenges and uncertainties that arise in remanufacturing systems. Based on the synthesis of a comprehensive literature study, eight functional requirements and a total of 48 associated key performance measures are derived and contextualized in a coherent conceptual framework. This establishes a consensus to mitigate the impacts caused by uncertainty in remanufacturing. The feasibility of the conceptual framework is validated in an industrial case study with an OEM remanufacturer of electric power steering products. The findings of this research paper advance the field of RPPC and offer guidance to industrial decision-makers to evaluate and optimize their remanufacturing production systems.

New electrical machines for passenger cars are gaining popularity. These electrical machines which contain copper parts need to generate a magnetic field to generate the propulsion of the machine. Laser welding is a fast and an effective joining process for the copper parts. In order to determine the lifetime of the copper parts, it is necessary to assess the fatigue behavior of the laser weld seam. Current guidelines for fatigue assessment do not include copper parts or copper weld seams, hence a fatigue concept must be derived. This proceeding examines the applicability of the notch stress concept with a reference radius of 0.05 mm for copper weld seams and provides a complex and a simplified way of modeling the weld seams. The presented concept takes the geometry of the weld seams and the fracture area surfaces into account. This leads to stress results with a low scatter range and a flat slope of the S-N curve. Furthermore, the results indicate that the notch stresses are transferable.

A high-power laser beam profiling system was set up to investigate the influence of the interaction between the laser beam and the process emissions during welding with a shaped beam profile. A positional instability of the beam on the workpiece in the order of magnitude of tens of µm and noticeable distortions of the beam shape were observed when no cross jet was used. Both perturbations were reduced when a cross jet was applied to remove the process emissions from the beam path and minimized when the cross jet was positioned closest to the workpiece.

The MiG-V was designed for high-security applications and is the first commercially available logic-locked RISC-V processor on the market. In this context, logic locking was used to protect the RISC-V processor design during the untrusted manufacturing process by using key-driven logic gates to obfuscate the original design. Although this method defends against malicious modifications, such as hardware Trojans, logic locking’s impact on the RISC-V processor’s data confidentiality during runtime has not been thoroughly examined. In this study, we evaluate the impact of logic locking on data confidentiality. By altering the logic locking key of the MiG-V while running SSL cryptographic algorithms, we identify data leakages resulting from the exploitation of the logic-locking hardware. We show that changing a single bit of the logic locking key can expose 100% of the cryptographic encryption key. This research reveals a critical security flaw in logic locking, highlighting the need for comprehensive security assessments beyond logic-locking key-recovery attacks. This article is part of the theme issue ‘Emerging technologies for future secure computing platforms’.

In this work, we present novel protocols over rings for semi-honest secure three-party computation (3PC) and malicious four-party computation (4PC) with one corruption. While most existing works focus on improving total communication complexity, challenges such as network heterogeneity and computational complexity, which impact MPC performance in practice, remain underexplored. Our protocols address these issues by tolerating multiple arbitrarily weak network links between parties without any substantial decrease in performance. Additionally, they significantly reduce computational complexity by requiring up to half the number of basic instructions per gate compared to related work. These improvements lead to up to twice the throughput of state-of-the-art protocols in homogeneous network settings and up to eight times higher throughput in real-world heterogeneous settings. These advantages come at no additional cost: Our protocols maintain the best-known total communication complexity per multiplication, requiring 3 elements for 3PC and 5 elements for 4PC.We implemented our protocols alongside several state-of-the-art protocols (Replicated 3PC, ASTRA, Fantastic Four, Tetrad) in a novel open-source C++ framework optimized for high throughput. Five out of six implemented 3PC and 4PC protocols achieve more than one billion 32-bit multiplications or over 32 billion AND gates per second using our implementation in a 25 Gbit/s LAN environment. This represents the highest throughput achieved in 3PC and 4PC so far, outperforming existing frameworks like MP-SPDZ, ABY3, MPyC, and MOTION by two to three orders of magnitude.

This paper presents a Digital Twin (DT) framework for the remote control of an Autonomous Guided Vehicle (AGV) within a Network Control System (NCS). The AGV is monitored and controlled using Integrated Sensing and Communications (ISAC). In order to meet the real-time requirements, the DT computes the control signals and dynamically allocates resources for sensing and communication. A Reinforcement Learning (RL) algorithm is derived to learn and provide suitable actions while adjusting for the uncertainty in the AGV's position. We present closed-form expressions for the achievable communication rate and the Cramer–Rao bound (CRB) to determine the required number of Orthogonal Frequency-Division Multiplexing (OFDM) subcarriers, meeting the needs of both sensing and communication. The proposed algorithm is validated through a millimeter-Wave (mmWave) simulation, demonstrating significant improvements in both control precision and communication efficiency.

Knowledge graphs (KGs) continue spreading into industrial use cases due to their advantages and superiority over classical data representations. A problem that has not yet adequately been solved for KGs is the traceability and provenance of changes, which can be required in an enterprise or by regulations. KGs typically contain the current snapshot of data valid at a certain moment in time only. Changes over time are usually not recorded and no change history exists. The lack of suitable and scalable traceability solutions hinders the wider application of KGs. This paper presents a traceability and provenance solution for KGs, which can track all changes of a KG on triple level. It comprises a provenance engine that intercepts SPARQL/Update queries; PROV-STAR, an RDF-star enabled light-weight extension of the Provenance Ontology (PROV-O) for representing changes and their provenance; and a SPARQL query transformation approach for tracking the changes on a separate provenance KG with SPARQL-star queries. The solution supports full traceability of all changes, on the lowest possible level of triples, with each change being comprehended with detailed provenance information. From the provenance KG a detailed change history can be retrieved, and any past version of the KG can be restored with a single query. The implementation and validation have shown that changes can be tracked at runtime during the normal operation of a KG. Furthermore, the solution is scalable to large KGs and frequent updates, as only the delta of each change is stored.

Initial clinical trials with drugs targeting epigenetic modulators - such as bromodomain and extraterminal protein (BET) inhibitors - demonstrate modest results in acute myeloid leukemia (AML). A major reason for this involves an increased transcriptional plasticity within AML, which allows cells to escape the therapeutic pressure. In this study, we investigated immediate epigenetic and transcriptional responses following BET inhibition and could demonstrate that BET inhibitor-mediated release of BRD4 from chromatin is accompanied by an acute compensatory feedback that attenuates down-regulation, or even increases expression, of specific transcriptional modules. This adaptation is marked at key AML maintenance genes and is mediated by p300, suggesting a rational therapeutic opportunity to improve outcomes by combining BET- and p300- inhibition. p300 activity is required during all steps of resistance adaptation, however, the specific transcriptional programs that p300 regulates to induce resistance to BET inhibition differ in part between AML subtypes. As a consequence, in some AMLs the requirement for p300 is highest during earlier stages of resistance to BET inhibition, where p300 regulates transitional transcriptional patterns that allow leukemia-homeostatic adjustments. In other AMLs, p300 shapes a linear resistance to BET inhibition and remains crucial throughout all stages of the evolution of resistance. Altogether, our study elucidates the mechanisms that underlie an "acute" state of resistance to BET inhibition, achieved through p300 activity, and how these mechanisms remodel to mediate "chronic" resistance. Importantly, our data also suggest that sequential treatment with BET- and p300-inhibition may prevent resistance development, thereby improving outcomes.

The present study is concerned with an experimental study into the effect of superimposed creep deformation, varying local fiber orientation distributions, and more complex multiaxial stress states on the fatigue of short fiber reinforced thermoplastics. The cross-interaction of these effects is a relevant feature in all fields of applications of short fiber composites since molding related variations of the local fiber orientation states cannot be avoided for injection molded structures. Long term loading will result in a combined occurrence of fatigue and creep and thus an interaction of the related effects. The study is based on a short glass fiber reinforced polyamide 66 as reference material which is a common material grade in many automotive applications. A basic characterization is performed by means of tensile and DMA experiments. Subsequently, creep and creep fatigue experiments are performed at ambient and elevated temperatures. In order to include the effects of locally varying fiber orientation situations and locally multiaxial loading situations, the coupon experiments are complemented by experiments on breadboard specimens featuring notches, holes, and structural component related external geometries. Superimposed creep deformation might accelerate fatigue failure, however, for notched specimens might also result in an increased fatigue lifetime due to creep-induced stress relief at the notch roots. The results reveal that care has to be taken when transferring the results on idealized coupon specimens to generalized, realistic problems. The results also serve as a development and validation data base for a continuum damage mechanics material model presented in an oncoming contribution.

Zusammenfassung Hintergrund/Ziel Phytotherapie wird zunehmend zur Behandlung dermatologischer Erkrankungen, insbesondere der atopischen Dermatitis (AD), eingesetzt. Ziel dieser systematischen Übersichtsarbeit war es, die Wirksamkeit topischer und systemischer pflanzlicher Interventionen bei Kindern und Jugendlichen mit AD zu bewerten. Methoden Eine systematische Literaturrecherche in Medline/PubMed, Scopus und dem Cochrane Central Register of Controlled Trials (Central) bis zum 12. April 2023 identifizierte randomisierte kontrollierte Studien (RCTs). Die Übersichtsarbeit folgte den PRISMA-Richtlinien, und die Qualität der Studien wurde mithilfe des Cochrane Risk of Bias Tools 2.0 sowie den GRADE-Kriterien bewertet. Eine Metaanalyse wurde unter Verwendung des Random-Effects-Modells durchgeführt. Ergebnisse Insgesamt wurden 25 RCTs mit 2091 Teilnehmern eingeschlossen. Verschiedene pflanzliche Präparate, wie Sonnenblumenöl, Feige, Eibisch und Kokosnussöl, zeigten in einzelnen Studien eine vielversprechende Wirksamkeit. Eine Metaanalyse von 5 RCTs zu systemischem Nachtkerzenöl zeigte jedoch keinen signifikanten Unterschied im Vergleich zu Placebo. Schlussfolgerung Die Ergebnisse deuten darauf hin, dass einige pflanzliche Präparate eine potenzielle Wirksamkeit bei AD aufweisen. Dennoch sind größere, methodisch robuste Studien notwendig, um klare Empfehlungen zur Anwendung pflanzlicher Therapien bei AD im Kindes- und Jugendalter aussprechen zu können.

This survey provides an overview of combining federated learning (FL) and control to enhance adaptability, scalability, generalization, and privacy in (nonlinear) control applications. Traditional control methods rely on controller design models, but real‐world scenarios often require online model retuning or learning. FL offers a distributed approach to model training, enabling collaborative learning across distributed devices while preserving data privacy. By keeping data localized, FL mitigates concerns regarding privacy and security while reducing network bandwidth requirements for communication. This survey summarizes the state‐of‐the‐art concepts and ideas of combining FL and control. The methodical benefits are further discussed, culminating in a detailed overview of expected applications, from dynamical system modelling over controller design, focusing on adaptive control, to knowledge transfer in multi‐agent decision‐making systems.

The prediction of forced vibrations in nonlinear systems is a common task in science and engineering, which can be tackled using various methodologies. A classical approach is based on solving differential (algebraic) equations derived from physical laws ('first principles'). Alternatively, Artificial Neural Networks (ANNs) may be applied, which rely on learning the dynamics of a system from given data. However, a fundamental limitation of ANNs is their lack of transparency, making it difficult to understand and trust the model's predictions. In this contribution, we follow a hybrid modelling approach combining a data‐based prediction using a stabilised Autoregressive Neural Network (s‐ARNN) with a priori knowledge from first principles. Moreover, aleatoric and epistemic uncertainty is quantified by a combination of mean‐variance estimation (MVE) and deep ensembles. Validating this approach for a classical Duffing oscillator suggests that the MVE ensemble is the most accurate and reliable method for prediction accuracy and uncertainty quantification. These findings underscore the significance of understanding uncertainties in deep ANNs and the potential of our method in improving the reliability of predictive nonlinear system modelling. We also demonstrate that including partially known dynamics can further increase accuracy, highlighting the importance of combining ANNs and physical laws.