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Charging and Discharging of Hydrogen Sorption Storage Tank 14th

Charging and Discharging of Hydrogen Sorption Storage Tank

引用

14th International Conference on Computational Heat and Mass Transfer (ICCHMT)

作者： Klepp, G. Filippi, M. Langer, G. Th Ostwestfalen Lippe Campusallee 12 D-32657 Lemgo Germany

ISBN: (纸本)9783031672408;9783031672415

The application of hydrogen in order to store energy and as a vehicle fuel requires efficient and effective storage technologies. An alternative solution to cryogenic and high pressure tanks is the use of porous material and physisorption (carbons, metal organic frameworks) or chemisorption (hydrides) in the tank. Due to the heat of sorption the temperature and its distribution in the tank might vary significantly during charging and discharging, affecting the storage capacity. The flow of the hydrogen in the tank is described by the equation of mass conservation, the Navier-Stokes equations and the equation of energy conservation as implemented in a CFD code. In the conservation equation additional terms are implemented in order to account for the amount of hydrogen involved in the sorption and the corresponding heat of sorption. These result from the mass and energy balance for the hydrogen in a finite volume whereat the equilibrium is described by an appropriate sorption isotherm. The use of data driven models is often computationally more advantageous then physical models. Based on the physical adsorption model a data driven model is derived using different machine learning techniques. This model is implemented as source terms in the governing equations, leading to a computationally more advantageous formulation. Thus the distribution of temperature and concentration during charging and discharging of the tanks is computed and limiting phenomena are identified.

关键词： Hydrogen Storage Tanks Adsorption CFD Machine Learning

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Tuning Time Delays to Improve the Performance of a Steering Controller 16th

Tuning Time Delays to Improve the Performance of a Steering ...

引用

16th International Symposium on Advanced Vehicle Control

作者： Li, Jialin Takacs, Denes Lu, Jianwei Voros, Illes Stepan, Gabor Hefei Univ Technol Sch Automot & Transportat Engn Hefei Anhui Peoples R China Budapest Univ Technol & Econ Fac Mech Engn Dept Appl Mech Budapest Hungary HUN REN BME Dynam Machines Res Grp Budapest Hungary

ISBN: (纸本)9783031703942;9783031703928;9783031703911

Time delays and lags in control loops can cause instability and pose significant challenges to engineers. This study investigates a steering controller using the dynamic bicycle model, where the steering system dynamics are approximated by a steering lag. A higher-level controller calculates the desired steering angle based on the vehicle's lateral position and yaw angle by considering various time delays related to these states. Stability charts are plotted for delay combinations, and the most stable gain setups for the feedback controller are determined. The results indicate that an appropriate increase in one of the time delays expands the stable domain of control gains for the vehicle system, and it enhances the performance of the vehicle controller.

关键词： time delay steering control stability analysis feedback control

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Decision Trees and Multi-objective Optimization to Calibrate Process Parameters 1

引用

33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Chen, Chiao-Yu Hong, I-Hsuan Li, Yue-Hong Natl Taiwan Univ 1Sect 4Roosevelt Rd Taipei 10617 Taiwan

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

The paper introduces an innovative approach to address the challenge of determining process parameter settings to achieve desired goals. We propose a mathematical programming approach that integrates a multi-objective formulation with decision tree models. These decision tree models predict different targets, and the mathematical model combines their outputs with other process requirements. A case study demonstrates the effectiveness of our model and compares its performance to a method based on a multi-objective decision tree. The results reveal that our method, employing multiple single-objective decision trees, outperforms the conventional approach utilizing a single multi-objective decision tree. The suggested outcomes provide the most suitable parameter ranges based on their target preferences.

关键词： Decision tree Process parameter Multi-objective decision tree

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The Impact of KAIZEN on the Operational Performance of Multinational Manufacturing Companies Through the Degree of Maturity. A Mixed Study in Mexico 8th

The Impact of KAIZEN on the Operational Performance of Multi...

引用

8th International Scientific-Technical Conference (MANUFACTURING)

作者： Suarez-Barraza, Manuel F. Chavez-Pineda, Jesus A. Altamirano, Dailin A. Ramirez Huerta-Carvajal, Maria Isabel Univ Amer Puebla Mexico Autonomous Univ Chihuahua Chihuahua Mexico Natl Polytech Inst Mexico City Mexico

ISBN: (纸本)9783031564468;9783031564444

Kaizen or change for the better continues to be a term that needs much to be explored in the industrial environment and in the academic arena. Understanding its implementation, especially in multinational manufacturing companies (EMMs), is vital to avoid errors and confusion. On the other hand, the EMMs that apply it must explore the degree of maturity or sustainability of the implementation of Kaizen techniques to achieve positive results in their operational performance. Therefore, the general objective of this study is: to analyze the impact of Kaizen techniques through the degree of maturity on operational performance in multinational manufacturing companies (EMM). A mixed methodology (qualitative and quantitative) to analyze the implementation of the Kaizen EMM, the quantitative result, speaking, indicates the most implemented techniques, and how those EMMs that have a greater degree of maturity and implementation present better results in their operational performance.

关键词： Kaizen degree of maturity operational performance Kaizen techniques degree of conformation multinational manufacturing companies (EMM)

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Dynamic Adaptability in Human-Robot Collaboration for Industrial Assembly: A Behaviour Tree Based Task Execution 33rd

Dynamic Adaptability in Human-Robot Collaboration for Indust...

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Akkaladevi, Sharath Chandra Propst, Matthias Deshpande, Kapil Hofmann, Michael Pichler, Andreas Sapoutzoglou, Panagiotis Zacharia, Athena Kalogeras, Dimitrios Pateraki, Maria PROFACTOR GmbH Robot & Automat Syst Stadtgut D1 A-4400 Steyr Gleink Austria Alpen Adria Univ Klagenfurt Inst Networked & Embedded Syst Klagenfurt Austria Natl Tech Univ Athens Inst Commun & Comp Syst ICCS Athens 15773 Greece Natl Tech Univ Athens Sch Rural Surveying & Geoinformat Engn Athens 15780 Greece

ISBN: (纸本)9783031744815;9783031744822

This work deals with the intricacies of human-robot collaboration (HRC) within industrial settings, with a focus on achieving seamless interaction through a skill-based robot task execution engine. The proposed framework intricately orchestrates the dynamic interplay between the perception and acting/reacting layers in the context of human-robot collaboration, with a specific emphasis on the role of Behavior Trees (BTs) in both task execution and deviation handling. The Behavior Tree-based Task Execution (BTE) is seamlessly integrated into the acting/reacting layer, collaborating synergistically with the perception layer, which includes robot proprioception and object localization modules. This integration facilitates the efficient detection and handling of deviations, particularly those arising from failures during robotic manipulation (grasping), ensuring real-time responsiveness to environmental changes in collaborative assembly tasks. Real-world experiments conducted on a car door assembly line serve as practical demonstrations of the proposed framework's adaptability to address deviations in dynamic environments.

关键词： Human-Robot Collaboration Skill-Based Task Execution Object Detection

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Application of Ontology Reasoning in Machining Process Planning - Case Study 32nd

Application of Ontology Reasoning in Machining Process Plann...

引用

32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Adjei, Peter Asare, Felix Sormaz, Dusan Abir, Riad Al Hasan Fuloria, Mandvi Koonce, David Seeharit, Saruda Ohio Univ Athens OH 45701 USA

ISBN: (纸本)9783031382406;9783031382413

Data interoperability is a critical issue in machining and process planning because it allows data to be exchanged and reused across different systems and organizations. Ontologies, particularly those developed within the context of the Basic Formal Ontology (BFO), play an important role in promoting data interoperability by providing a shared vocabulary as well as a formal representation of the concepts and relationships within a specific domain. This study explores the integration of ontologies in Computer-Aided Process Planning (CAPP) to enhance manufacturing efficiency, accuracy, and flexibility. IMPlanner, a manufacturing process planning system, is utilized to generate process models and process hierarchies, to leverage the benefits of ontologies for information representation and sharing. By modeling the results within an ontology, we efficiently infer newinformation, providing a deeper understanding of the manufacturing process. The approach presented has the potential to significantly improve manufacturing planning and execution, allowing manufacturers to optimize their operations in Industry 4.0. By harnessing the power of ontologies and reasoning tools, we demonstrate that it elevates the accuracy, efficiency, and adaptability of manufacturing processes.

关键词： Data interoperability Machining processes Process planning Ontologies BFO IOF

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Reticular Structures Embedded in Phase Change Material: Effects of Orientation on Thermal Performance 14th

Reticular Structures Embedded in Phase Change Material: Effe...

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14th International Conference on Computational Heat and Mass Transfer (ICCHMT)

作者： Nonino, Carlo Diani, Andrea Univ Udine DPIA Udine Italy Univ Padua DII Padua Italy

ISBN: (纸本)9783031666087;9783031666094

Phase change materials (PCMs) are plagued by very low thermal conductivity. Metal foams and conductive fillers are often used to increase the overall thermal conductivity of composite PCM structures. Additive Manufacturing (AM) technology like Selective Laser Melting (SLM) can also be employed. This paper presents a numerical investigation on the influence of cell orientation on the thermal performance of PCM-impregnated metal reticular structures produced through Additive Manufacturing (AM). The study includes four cubic cell reticular structures with varying cell sizes (5 mm and 10 mm) and porosities (87% and 93%). Additionally, four distinct cell orientations are examined. Rubitherm's RT42 paraffin wax is used as the Phase Change Material (PCM), and AlSi10Mg aluminum alloy constitutes the material for the reticular structures. Numerical simulations were carried out using a simplified purely conductive model implemented in the commercial Ansys Fluent software. The results indicate that, for a specific cell size and porosity, cell orientation significantly influences the thermal energy storage rate. Furthermore, a cell orientation has been identified that, in addition to providing good thermal performance, allows easier fabrication by SLM.

关键词： Thermal energy storage Phase change material Reticular structures Additive manufacturing

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Prediction Model of Product Quality in Production Company: Based on PCA and Logistic Regression 32nd

Prediction Model of Product Quality in Production Company: B...

引用

32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Antosz, Katarzyna Rzeszow Univ Technol Fac Mech Engn & Aeronaut Al Powstancow Warszawy 8 PL-35959 Rzeszow Poland

ISBN: (纸本)9783031381645;9783031381652

The paper presents the possibility of implementation the Principle Component Analysis (PCA) and logistic regression to develop the decision tool supporting quality of oil inserts for candles production process. The research methodology was divided into three stages: collecting data from the production process, using the PCA method to reduce the dimensionality of the production process parameters, and using logistic regression to develop a predictive model for assessing the quality of products. The results of the research showed that it was enough to have five main components to keep about 84% of the information on variability. In the third stage the logistic regression to develop the predictive model of product quality in production company was used. The developed model explain the impact of the production parameters on product quality. In addition, this decision tool will help the managers in the company identification the improvement actions.

关键词： Principle component analysis PCA Logistic regression Product quality control

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Knowledge Graph-Driven Manufacturing Resources Recommendation Method for Ship Pipe Manufacturing Workshop 7th

Knowledge Graph-Driven Manufacturing Resources Recommendatio...

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7th International Workshop on Autonomous Remanufacturing (IWAR)

作者： Zhang, Zijun Tian, Sisi Peng, Ling Li, Ruifang Xu, Wenjun Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Wuhan Univ Technol Hubei Key Lab Broadband Wireless Commun & Sensor Wuhan 430070 Peoples R China China Ship Dev & Design Ctr Wuhan 430064 Peoples R China

ISBN: (纸本)9783031526480;9783031526497

In the context of the digitized and intellectualized transformation of ship pipe manufacturing enterprises, how to transform the massive multi-source heterogeneous data into knowledge and realize the reuse of manufacturing knowledge and experience in the ship pipe manufacturing workshop are the key to optimizing the allocation of workshop manufacturing resources. In order to solve the aforementioned issues, a knowledge graph-driven manufacturing resource recommendation method for ship pipe manufacturing workshops is proposed. Firstly, the correlation between multi-sources heterogeneous manufacturing data (device resources, manufacturing process of pipe, manufacturing orders) is analyzed and integrated. Then, a knowledge graph of manufacturing resources for the ship pipe manufacturing workshop is constructed. On this basis, a manufacturing resource recommendation method based on the Knowledge Graph Convolution Networks is proposed to recommend the device for orders in the ship pipe manufacturing workshop. Finally, a case study is implemented to verify the feasibility and effectiveness of the proposed method.

关键词： Knowledge graph Ship pipe manufacturing workshop Resource recommendation Knowledge graph convolution networks

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Toward ML-Based Application for Vehicles Operation Cost Management 1

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8th International Scientific-Technical Conference (MANUFACTURING)

作者： Rojek, Izabela Mikolajewski, Dariusz Przybylinski, Slawomir Dostatni, Ewa Sapietova, Alzbeta Kazimierz Wielki Univ Bydgoszcz Poland Poznan Univ Tech Poznan Poland Univ Zilina Zilina Slovakia

ISBN: (数字)9783031564673

ISBN: (纸本)9783031564697;9783031564673

This paper presents the design and implementation of a web-based application for managing vehicle operating costs. The application is intended to help vehicle users control and optimize the money spent on the maintenance of both a single vehicle and a group of vehicles (fleet) for the company. Moreover this application aims to collect data that will then serve as sample files that will then be used in a machine learning application. At the beginning of the work, the methodology and requirements to be met by the web application were discussed. In the following parts of the work, the implementation of the web application and tests of the application are presented. At the end of the work, proposals for further development of the application and conclusions of the work are presented. In the era of electric vehicles, such applications will play an increasingly important role, including as journey calculators (charging plans, etc., taking into account journey times, distance covered, stopping times, minimizing energy consumption, etc.), hence the role of machine learning (ML) will grow, as, for example, as a route is covered, the software will recalculate data and alternative options in real time, which can be reflected in ERP logistics and enterprise fleet management systems for sustainability.

关键词： Artificial Intelligence Machine Learning Industry 4.0 Fleet Management Cost Optimization Sustainable Exploitation

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