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Balancing the customization and standardization:exploration and layout surrounding the regulation of the growing field of 3D-printed medical devices in China

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Bio-Design and Manufacturing 2022年第3期5卷 580-606页

作者： Zhongboyu Jin Chaofan He Jianzhong Fu Qianqian Han Yong He State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Materials Processing and Mold Zhengzhou UniversityZhengzhou 450002China Cancer Center Zhejiang UniversityHangzhou 310058China National Institutes for Food and Drug Control Beijing 102629China

Medical devices are instruments and other tools that act on the human body to aid clinical diagnosis and disease treatment,playing an indispensable role in modern ***,the increasing demand for personalized medical devices poses a significant challenge to traditional manufacturing *** emerging manufacturing technology of three-dimensional(3D)printing as an alternative has shown exciting applications in the medical field and is an ideal method for manufacturing such personalized medical devices with complex ***,the application of this new technology has also brought new risks to medical devices,making 3D-printed devices face severe challenges due to insufficient regulation and the lack of standards to provide guidance to the *** review aims to summarize the current regulatory landscape and existing research on the standardization of 3D-printed medical devices in China,and provide ideas to address these *** focus on the aspects concerned by the regulatory authorities in 3D-printed medical devices,highlighting the quality system of such devices,and discuss the guidelines that manufacturers should follow,as well as the current limitations and the feasible path of regulation and standardization work based on this *** key points of the whole process quality control,performance evaluation methods and the concept of whole life cycle management of 3D-printed medical devices are ***,the significance of regulation and standardization is pointed ***,aspects worthy of attention and future perspectives in this field are discussed.

关键词： 3D printing Medical device Regulation Standardization

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Machine Learning-Supported Solvent Design for Lignin-First Biorefineries and Lignin Upgrading

SSRN

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SSRN 2024年

作者： König-Mattern, Laura Sanchez Medina, Edgar I. Komarova, Anastasia O. Linke, Steffen Rihko-Struckmann, Liisa Luterbacher, Jeremy S. Sundmacher, Kai Max Planck Institute for Dynamics of Complex Technical Systems Process Systems Engineering Sandtorstraße 1 Magdeburg39106 Germany Otto von Guericke University Magdeburg Chair for Process Systems Engineering Universitätsplatz 2 Magdeburg39106 Germany École Polytechnique Fédérale de Lausanne Laboratory of Sustainable and Catalytic Processing Station 6 Lausanne1015 Switzerland

Solvent selection is a difficult task for lignin-first biorefineries and lignin upgrading as the solvent must satisfy multiple complex technical requirements, while remaining extremely stable to allow recycling. High lignin solubility is a common selection criterium but the ideal solvent for lignin-first biorefineries also requires non-reactivity towards acids and stabilising reagents encountered in the reaction liquor. To facilitate the search for promising solvents, we developed a computational solvent design framework. The framework consists of a graph-based genetic algorithm for molecular design and a graph neural network for lignin solubility predictions. Based on these predictions, the genetic algorithm iteratively optimises the molecular structures and is inspired by evolutionary strategies, such as selection, cross-over, and mutation. The developed framework designed numerous solvents with enormous potential for application in lignin-first biorefineries and lignin upgrading. For these solvents, experiments confirmed solubilities between 20 and 60 wt.% across different types of lignin. Notably, several solvents were stable under typical biorefinery process conditions. Furthermore, the explainability of graph neural networks enabled us to link the lignin solubility predictions with structural features of the solvents, providing a clear rationale for solvent selection. © 2024, The Authors. All rights reserved.

关键词： Solvents

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LCA-based Multi-scenario Study on Steel or Aluminum Wheel Hub for Passenger Vehicles 30

LCA-based Multi-scenario Study on Steel or Aluminum Wheel Hu...

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30th CIRP Life Cycle engineering Conference, LCE 2023

作者： Gao, Lu Wang, Zhihui Wang, Yanan Peng, Tao Liu, Weipeng Tang, Renzhong State Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310058 China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province Zhejiang University Hangzhou310058 China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310058 China School of Engineering Zhejiang University City College Hangzhou310015 China

Lightweighting is one of the enabling techniques for energy saving and carbon reduction in the automotive industry. However, the life cycle performance of lightweight components remains unclear. Wheel hub is an important component, and its trend of replacing steel with aluminum is happening. Based on life cycle assessment and using ReCiPe model, this paper reports a cradle-to-grave study on the environmental impact of steel and aluminum wheel hub in passenger vehicles. Considering multi-scenario in the Chinese market, it is found that when the service life of passenger vehicle is less than 5.6 years, steel wheel hub is more environmental-friendly, and when the service life is less than 8.6 years, steel wheel hub also has more economic advantages. Combining different lightweight methods and different types of vehicles, it is found that structural optimization reduces the environmental impact of per unit weight mostly, process optimization reduces the life cycle environmental impact of wheel hub, and using lightweight steel wheel hub in electric vehicles has more potential in environmental benefits. some suggestions are, 1) to choose wheel hub that matches your actual usage to enjoy more environmental-economic advantages;2) to prioritize structural-process integrated optimization for lightweight wheel hub;and 3) to use more lightweight components in electric vehicles. © 2023 The Authors. Published by Elsevier B.V.

关键词： Environmental impact

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Techno-economic assessment for bio coal production from brewers spent grain

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South African Journal of Chemical engineering 2022年 40卷 1-9页

作者： Mugoronji, M. Manyuchi, M.M. Sukdeo, N. Stinner, W. Department of Chemical and Process Systems Engineering School of Engineering and Technology Harare Institute of Technology Zimbabwe Department of Operations and Quality Management Faculty of Engineering and the Built Environment University of Johannesburg South Africa Germany Biomass Research Center Leipzig Germany

Tons of organic wastes are being generated from household, domestic and industrial waste. This waste if left untreated results in the emission of greenhouses gases such as methane and carbon dioxide, in overall resulting in climate change effects. On the other hand, the organic waste provides a valuable source of raw material for the production of bio coal, which is green and is renewable. In this study, brewery waste was converted to bio coal using the hydrothermal carbonization technology. Bio coal with a heating value of 26.1 MJ/kg was then produced. An economic assessment indicated that a total capital investment of USD 7.58 million is required for a plant that produces 69 tons/day. The production cost is USD 190.60 per tonne;the selling price was pegged at USD 200.00 which is less than the market value of fossil coal by USD10.00. The net present value of utilising brewery waste as a raw material in bio coal production was positive;with a payback period of 4.62 years and a 21.7% return on investment. © 2022

关键词： Bio coal Climate change mitigation Economic feasibility Solid waste management

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Explainable artificial intelligence model for accident severity modeling

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Asian Journal of Civil engineering 2025年第6期26卷 2433-2445页

作者： Khasawneh, Mohammad Ali Umar, Ibrahim Khalil Khasawneh, Ahmad Ali Civil Engineering Department Prince Mohammad Bin Fahd University P.O. Box 1664 Al Khobar 31952 Saudi Arabia Department of Civil Engineering Technology Kano State Polytechnic Kano 700282 Nigeria Management Engineering and Process Improvement Department/Integrated Systems Engineering Department Ohio State University Wexner Medical Center Ohio State University 660 Ackerman Rd Columbus 43202 OH United States

Accident severity prediction is a critical challenge in traffic safety management, emergency response, and urban mobility planning. Road accidents remain a leading cause of fatalities worldwide, yet existing accident analysis frameworks often lack predictive accuracy, interpretability, and real-time decision-making capabilities. Traditional statistical models fail to capture complex interactions between vehicle attributes, driver behavior, and environmental factors, limiting their effectiveness in accident severity assessment. This study addresses these gaps by developing an explainable artificial intelligence (XAI) framework for accident severity prediction, leveraging machine learning models (Random Forest, Extreme Gradient Boosting, Support Vector Machine, and Naïve Bayes) and SHapley Additive exPlanations (SHAP) analysis to enhance model transparency. The dataset, sourced from the Fatality Analysis Reporting System (FARS), consists of 7394 recorded crashes and incorporates key predictors such as airbag deployment, control devices, seatbelt usage, and driver demographics. Experimental results demonstrate that XGBoost outperforms other models, achieving the highest accuracy (80.8%), recall (80.8%), and F1-score (81.0%), making it the most reliable classifier for distinguishing between severe and non-severe accidents. SHAP analysis reveals that airbag deployment, seatbelt usage, and control devices significantly impact accident severity outcomes, providing valuable insights into policy-driven interventions and traffic management strategies. Despite its effectiveness, the study highlights limitations such as data imbalance, lack of real-time behavioral factors, and exclusion of non-fatal crashes, suggesting deep learning integration, real-time telematics, and hybrid AI models in future research. The proposed framework offers a data-driven approach to accident severity prediction, improving road safety policies, vehicle design enhancements, and emergency response eff

关键词： Accident severity prediction Explainable AI Feature importance Machine learning models Risk assessment Traffic safety

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Distributed Fault-Tolerant Consensus control for Linear Multi-Agent System with K-Step Hierarchical Protocol

Distributed Fault-Tolerant Consensus Control for Linear Mult...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Wang, Yuanwen Dong, Jiuxiang College of Information Science and Engineering Northeastern University Shenyang110819 China Liaoning Province Key Laboratory of Safe Operation Technique for Autonomous Unmanned Systems Northeastern University Shenyang110819 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education Northeastern University Shenyang110819 China

ISBN: (纸本)9789811966125

The distributed fault-tolerant consensus control using k-step hierarchical protocol for linear multi-agent system (MAS) is studied in this note. Unlike most existing fault-tolerant methods for compensating actuator fault, a hierarchical protocol consisting of a virtual layer and a actual layer that considers both fault compensation and introducing fault information into the trajectory planning process which means that the motion of the MAS does not exceed the fault-tolerant compensation range of the faulty agent is proposed. Trajectory planning is responsible for the virtual layer consisting of virtual agent system and a co-controller that introduces fault information. The actual layer, consisting of the actual agent system, actuator fault observer, and tracking trajectory controller, traces the virtual layer for consensus. It is shown that the integrity of the MAS is guaranteed. Finally, the validity of the developed protocols is illustrated by simulation examples. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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CCUS and Geothermal Energy Activities in Saskatchewan, Canada: Novel Technologies in Carbon Capture and Storage Related the University of Regina's Clean Energy Technologies Research Institute and the PTRC's Aquistore Deep Saline Storage Project

CCUS and Geothermal Energy Activities in Saskatchewan, Canad...

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2023 Abu Dhabi International Petroleum Exhibition and Conference, ADIP 2023

作者： Narayanasamy, R. Ibrahim, H. Kamali, M. Fabrik, M. Petroleum Technology Research Centre 220-6 Research Drive ReginaSKS4S 7J7 Canada Clean Energy Technologies Research Institute Process Systems Engineering Faculty of Engineering and Applied Science University of Regina 3737 Wascana Parkway ReginaSKS4S OA2 Canada Energy Technologies Research Institute Process Systems Engineering Faculty of Engineering and Applied Science University of Regina 3737 Wascana Parkway ReginaSKS4S OA2 Canada

ISBN: (纸本)9781959025078

The province of Saskatchewan in Canada has two of the largest CCUS projects in the world - the Weyburn CO2-EOR flood and the Aquistore Deep Saline CO2 Storage Project. Learnings from these operations have powered significant research in capture, storage, and (inadvertently) geothermal energy production. This work will examine how these commercial operations have fostered important research into solvents for less expensive capture technologies, and reservoir characterization and monitoring that has enhanced CO2 storage while simultaneously enhancing geothermal production. The 23-year history of CO2 EOR and deep saline storage in Saskatchewan has led to a material advantage for research groups in the province - both in the areas of CO2 capture research, and CO2 deep geological storage. The SaskPower Boundary Dam Capture Facility, and the Aquistore site have both facilitated R&D programs at Saskatchewan's universities and research organizations into reactive solvent capture technologies, and at PTRC in novel measurement, monitoring and verification tools. The accumulated data from those two industrial scale projects (capture and storage) have facilitated unique findings worth sharing with other planned CCS projects now in development. Over 30 different kinds of measurement, monitoring and verification technologies for storage have been examined and compared at the Aquistore Deep Saline Storage Project. The results on plume monitoring and surveillance, using both DAS and DTS (fibre optic) deployment has shown a surprising repeatability of results as compared to the site's permanent geophone array. Novel deep fluid sampling to examine brine-CO2 interactions, and ongoing extensive sometimes surprising data related to second-by-second injection at the wellhead has revealed salt precipitation and pressure data that is crucial for planned projects globally, particularly those that may experience stop-and-start injection regimes. In relation to reactive solvent development in

关键词： Carbon dioxide

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Optimal Experimental Design for the Identification of a Reaction Kinetic Model for the Hydroaminomethylation of 1-Decene in a Thermomorphic Multiphase System

SSRN

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SSRN 2023年

作者： Sundmacher, Kai Rätze, Karsten Hans Georg Kortuz, Wieland Kirschtowski, Sabine Jokiel, Michael Hamel, Christof Otto von Guericke University Magdeburg Chair for Process Systems Engineering Universitätsplatz 2 MagdeburgD-39106 Germany Otto von Guericke University Magdeburg Chair of Chemical Process Engineering Universitätsplatz 2 MagdeburgD-39106 Germany Max Planck Institute for Dynamics of Complex Technical Systems Department Process Systems Engineering Sandtorstr. 1 MagdeburgD-39106 Germany

The homogeneously rhodium-catalyzed tandem hydroaminomethylation (HAM) of 1-decene is investigated by instructive dynamic experiments in a methanol/dodecane thermomorphic multiphase system (TMS) to derive, reduce and parameterize a mechanistic kinetic model valid for a wide range of operating conditions in order to design and optimize reactor units and production processes. Using the kinetic model from Kortuz et al. (2023), model-based optimal experimental design (mbOED) is employed to yield ﬁve optimal experiment designs for the identiﬁcation of the kinetic model parameters. Experiment setup-speciﬁc limitations are considered during the problem formulation via the discretization strategy and dedicated experimental operating window constraints. Phase separation due to the accumulation of water is prevented using phase equilibrium constraints during optimization. As the underlying activity coeﬃcient model, an artiﬁcial neural network (ANN) is created based on the perturbed-chain statistical associating ﬂuid theory (PC-SAFT) equation of state (EoS). With the results from the optimally designed experiments and additional literature data, kinetic model identiﬁcation is performed. This includes the formulation of a rigorous gas phase model, the extension of the catalyst pre-equilibrium, the inﬂuence of water on the reaction equilibria, and the estimation of kinetic and inhibition parameters. The model identiﬁcation is able to substantially improve the prediction quality of the hydroaminomethylation model in edge cases over the previous model while maintaining a quantitative agreement of experimental and simulated concentration proﬁles under nominal conditions. © 2023, The Authors. All rights reserved.

关键词： Parameter estimation

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Formulation of a Master Recipe: A Capability Aligning Approach for Resource Allocation

Formulation of a Master Recipe: A Capability Aligning Approa...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Michael Winter Tobias Klausmann Shagufta Shagufta Torben Miny Sebastian Heppner Tobias Kleinert Information and Automation Systems for Process and Material Technology RWTH Aachen University Aachen Germany Research & Development — Systems Engineering Lenze SE Aerzen Germany

The contribution addresses the challenge of transforming a general recipe, which lacks knowledge about specific production resources, into a plant-specific master recipe in the process industry. The authors propose an approach using the concept of capabilities in manufacturing, enabled by an ontology and the Asset Administration Shell. The approach aligns required and offered capabilities at different description levels to allocate equipment to process elements and generate a master recipe in BatchML. The validation of the approach is accompanied by a procedure logic for a modular plant and discusses open challenges. In conclusion, the provided approach offers a methodical and less experience-dependent derivation of a master recipe for a manufacturing process.

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SonoTransformers: Ultrafast Transformable Wireless Microscale Machines

arXiv

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arXiv 2023年

作者： Zhang, Zhiyuan Shi, Zhan Ahmed, Daniel Acoustic Robotics Systems Lab Institute of Robotics and Intelligent Systems Department of Mechanical and Process Engineering ETH Zurich RüschlikonCH-8803 Switzerland

Shape transformation, a key mechanism for organismal survival and adaptation, has gained importance across fields as diverse as electronics and medicine. However, designing and controlling microscale shape-shifting materials remains a fundamental challenge in various actuation modalities. Here, we introduce "SonoTransformer," an acoustically activated micromachine that delivers ultrafast transformability using preprogrammed soft hinges. These hinges concentrate energy through intensified oscillation and provide the necessary torque for transformation. We have created new machine designs to predetermine the folding state, enabling tailoring and milliseconds transformation. Additionally, we have shown selective transformation by adjusting acoustic power, realizing high degrees of control and functional versatility. Our findings open new research avenues in acoustics, physics, and soft matter, offering new design paradigms and development opportunities in robotics, metamaterials, adaptive optics, and microtechnology. © 2023, CC BY.

关键词： Hinges

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