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Multi-objective Optimization-Driven Design: Generative Design Approach for Manufacturing of a Train Bogie 1

引用

33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Daareyni, Amirmohammad Queguineur, Antoine Mokhtarian, Hossein Asadi, Reza Ituarte, Inigo Flores Tampere Univ Fac Engn & Nat Sci Korkeakoulunkatu 6 Tampere 33014 Finland Ecole Cent Nantes GeM UMsR CNRS 6183 1 Rue Noe F-44321 Nantes France

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

In recent years, advances in additive manufacturing (AM) technologies, particularly in Direct Energy Deposition (DED) as Wire Arc Additive Manufacturing (WAAM) and Laser Wire Directed Energy Deposition (LW-DED), have enabled engineers to produce large complex structures. Consequently, these developments drive a paradigm shift in how we conceptualize and manufacture complex components, pushing the limits of what is possible in engineering and design. As a result, there is a growing need for optimized structures considering the material constraints and advantages. This study uses a multi-objective optimization-driven engineering design approach to optimize the shape and materials of a train bogie as a case study. From the material perspective, different materials were selected to benefit from the high-strength steel (HSL) and low-carbon steel (LCS) and achieve weight reduction while considering other structural constraints. We generated multiple prospective designs using the generative design feature from Autodesk Fusion 360. Subsequently, safety factors are collected from these models using AbaqusCAE and the fatigue data with fe-safe. Moreover, a multi-objective optimization approach is applied to find the best possible design based on the resulting safety factor, weight, fatigue life, and maximum displacement of the proposed part. Finally, the collected results are compared, and a set of optimum designs is presented based on different criteria detailed in the study.

关键词： engineering design Generative design Multi-objective optimization Additive Manufacturing

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Advancing Digital Twin-Based Virtual Part Inspection in Additive Manufacturing: Systematic Literature Review of Virtual Inspection Methods in FFF 1

引用

33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Krueckemeier, Slim Schleich, Benjamin Tech Univ Darmstadt Product Life Cycle Management D-64287 Darmstadt Germany

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

This paper presents a systematic literature review that analyzes virtual inspection methods (VIMs) in the context of additive manufacturing (AM), with a specific focus on fused filament fabrication (FFF) technology. Virtual part inspection, enabled by digital twin-based approaches, offers a promising way to improve quality assurance in AM processes. A structured methodology following the PRISMA 2020 statement was used to identify and analyze 39 relevant publications. The investigation aims to systematically address research questions related to quality characteristics, input parameters, and types of virtual inspection methods proposed in the literature. The results indicate that VIMs predominantly employ artificial intelligence methods compared to analytical and numerical methods. ISO 17296-3 outlines 16 quality characteristics for AM. However, the literature only addresses eight, with dimensional accuracy being the most frequently targeted aspect. VIMs utilize various input parameters, such as camera images, temperature data, and printing parameters, to deduce the quality characteristics of additively manufactured parts. The discussion focuses on the implications of these findings for improving quality assurance practices and identifies future research directions for VIMs. The overarching goal is to enhance the overall quality assurance process in AM.

关键词： Digital Twin Additive Manufacturing Fused Filament Fabrication

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A Review of Value Stream Mapping (VSM) for Viable Business Process Management Among Agro-Allied Companies During the 4IR 32nd

A Review of Value Stream Mapping (VSM) for Viable Business P...

引用

32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Ajayi, Makinde Oluwafemi Laseinde, Opeyeolu Timothy Univ Johannesburg Fac Engn & Built Environm Johannesburg South Africa Univ Johannesburg Mech & Ind Engn Tech Dept Johannesburg South Africa

ISBN: (纸本)9783031382406;9783031382413

The ever-contending competitive forces in the industrial sector and the peculiarities associated with agro-allied manufacturing not limited to short shelf life, seasonality, and heterogeneity of raw materials have perpetually compelled management experts to deal with issues relating to the product, information, time, and material resource wastage. These factors play a significant role in consumer value maximization and have a lasting impact on the overall operational efficiency of any business. To cater to this concurrent industrial abnormality, Business organizations must be deliberate in adopting viable Business Process Management (BPM) strategies. Previous research provides sufficient data to prove that Value Stream Mapping (VSM) is a veritable lean manufacturing technique to adopt and settle challenges of operational deficiencies attributable to non-value-added activities in the value stream as practiced in other sectors such as engineering, healthcare, supply chain logistics, etc., with a limited focus on the agro-allied companies. The research, therefore, presents a review that further investigates the potentials of business process management among agro-allied firms and the exigency of the fourth industrial revolution (4IR) using value stream mapping. The study findings suggest that the agro-allied industry is still lagging behind its potential. Awareness of the use of VSM to ensure an efficient manufacturing process is extremely low among stakeholders. The study recommends further study on the importance of VSM to ensure agro-allied waste is controlled significantly.

关键词： Business Process Management Agro-allied Companies 4IR Value Stream Mapping Industry 4.0

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Safe Control Allocation of Articulated Heavy Vehicles Using Machine Learning 16th

Safe Control Allocation of Articulated Heavy Vehicles Using ...

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16th International Symposium on Advanced Vehicle Control

作者： van Dam, Sander Wisell, Lukas Shingade, Kartik Kieu, Mikael Erdinc, Umur Kati, Maliheh Sadeghi Gelso, Esteban Parthasarathy, Dhasarathy Volvo Grp Trucks Technol Gothenburg Sweden Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9783031703942;9783031703928;9783031703911

As articulated heavy vehicles are over-actuated, achieving a safe control allocation is crucial to ensure stability. This study introduces a machine learning model developed to identify unsafe behaviours and modes, such as jack-knifing and trailer swing, enabling the control scheme to prioritize stability. High-fidelity simulations, focusing on high-risk scenarios, generate data for training the machine learning model. This model is integrated into the control scheme to predict safe braking allocations and prevent unsafe vehicle modes during real-time driving scenarios. Initial tests showed promising results regarding prediction accuracy and a safety margin that can be implemented to further ensure that safe vehicle motion is achieved.

关键词： Control allocation articulated heavy vehicles machine learning yaw instability

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How Industry 4.0 and Lean Management Are Interrelated with Green Paradigm 32nd

How Industry 4.0 and Lean Management Are Interrelated with G...

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32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Bilancia, Alessia Costa, Federica Staudacher, Alberto Portioli Politecn Milan Dept Management Econ & Ind Engn Via Lambruschini 4-B I-20156 Milan Italy

ISBN: (纸本)9783031381645;9783031381652

Recently, sustainability has been tackled several times due to the impending climate change the earth is facing. Numerous techniques have been applied to reverse the direction companies were going into. In this paper, it is explained the importance that Lean Manufacturing tools and Industry 4.0 technologies can have on the sustainable side of a company. The aim of this work is to fill the scientific gap related to studies deepening the combination of these different paradigms, Industry 4.0-Lean-Green, which have been scarcely investigated together. Thus, a Systematic Literature Review has been performed to detect which were the key variables of these three fields and then, it was studied what their interaction was. This study is giving the opportunity to understand the main variables of Industry 4.0 and Lean manufacturing on which companies have to act in order to have an impact on green variables and their overall sustainability.

关键词： Green Industry 4.0 Lean Manufacturing

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Simulation-Based Approaches to Enhance Operational Decision-Support in Healthcare 5.0: A Systematic Literature Review 32nd

Simulation-Based Approaches to Enhance Operational Decision-...

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32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Chidozie, Bernardine Chigozie Ramos, Ana Luisa Ferreira, Jose Vasconcelos Univ Aveiro GOVCOPP DEGEIT Aveiro Portugal

ISBN: (纸本)9783031381645;9783031381652

The objective of this study is to systematically evaluate peer-reviewed literature and analyze the current research on the thematic area "Simulation-Based Approaches to Enhance Operational Decision-Support in Healthcare 5.0" using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. This systematic review was conducted in compliance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement and implemented with the aid of the StArt software. Appropriate keywords were used in a search of the Science Direct, SCOPUS, and Web of Science databases. A total of 357 papers were retrieved from the databases and evaluated automatically. Eventually, 79 papers were analyzed according to their title, keywords and abstract. After the full-text analysis, 33 papers successfully met the inclusion criteria in the study. The review showed that healthcare providers and decision-makers can be guided by applying the Key Performance Indicators (KPIs) obtained from the simulation-based platforms to ensure quality and resilient health system.

关键词： Decision-Support Healthcare 5.0 Simulation

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Black Ice Detection Based on Tire Friction Coefficient Estimation of Vehicle Longitudinal Model 16th

Black Ice Detection Based on Tire Friction Coefficient Estim...

引用

16th International Symposium on Advanced Vehicle Control

作者： Lee, Seung-Yong Lee, Ho-Jong Kim, Gi-Woo Inha Univ Incheon 22212 South Korea HanKook Tire & Technol Co R&D Ctr Daejeon South Korea

ISBN: (纸本)9783031703942;9783031703928;9783031703911

Black ice is a deadly hazard on the road because it is visually transparent and difficult to identify by driver's naked eye while driving. Because tire friction on a black icy road surface is obviously smaller than normal road, the braking distance significantly increases and leads to severe traffic accidents. Road hazard detection such as black ice has been actively attempted so far, usually focusing on methodology using intelligent vision systems (e. g., cameras). However, current image-based methods are prone to reduced low accuracy due to their susceptibility to vibrations transmitted from road surfaces to vehicles. In addition, incorporating cameras and light detection and ranging sensors increases the complexity and computational burden, especially when extending their functionality to include road surface classification. Therefore, we investigate the potential of new road surface classification based on vehicle longitudinal velocity and tire effective radius estimation from vehicle longitudinal model. This study explores a sensor-fusion type indirect road surface classification algorithm based on Kalman filtering.

关键词： Black Ice Detection Extended Kalman Filter Vehicle Longitudinal Velocity Tire Effective Radius Wheel Slip Ratio

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Modelling and Simulation of Solar Desalination Based on Multiple Effect Distillation Process in Saudi Arabia 14th

Modelling and Simulation of Solar Desalination Based on Mult...

引用

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

作者： AlRabiah, A. N. Orfi, J. King Saud Univ Coll Engn Sustainable Energy Technol Ctr POB 800 Riyadh 11421 Saudi Arabia King Saud Univ Coll Engn Mech Engn Dept POB 800 Riyadh 11421 Saudi Arabia

ISBN: (纸本)9783031672408;9783031672415

In recent years, Saudi Arabia has witnessed an increase in water and energy demand due to the high growth in its population and its industrial activities. This growing demand for fresh water and the overdependence on fossil fuels to produce desalinated water have led and motivated further development of water desalination and purification utilizing renewable energy technologies. Solar, geothermal and wind energy are gaining interests and becoming attractive options to drive potable water production systems. Integrating solar energy with desalination offers a promising prospect for covering the fundamental needs of power and water;this is beneficial for remote regions especially, where there is no connection to the public electric grid and water scarcity is severe. This work presents a model and simulations on coupled mature technologies of solar energy collection and potable water production. A mathematical model is developed for both multiple effect distillation (MED) and concentrated solar power (CSP) given the capacity required and the resources for a selected location. The model, which is systematically validated, is based on conservation of mass and energy and appropriate specifications of CSP and MED components. Besides, an economic model is also presented and used to estimate the overall desalinated water cost. The study is also performed for three coastal cities across Saudi Arabia which are Dhahran, Abha and Tabuk. The results show that the cost of produced water for a system that has a capacity of 10000 m(3)/day is 2.101 $/m(3), 2.039 $/m(3) and 1.927 $/m(3) for Dhahran, Abha and Tabuk respectively.

关键词： Drinking Water Sustainable Desalination MED Solar Energy Parabolic Trough Collectors Water Cost

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E-Manufacturing Model Using Crowdsourcing Technologies for Production Efficiency in Railway Transport Manufacturing Companies in South Africa 33rd

E-Manufacturing Model Using Crowdsourcing Technologies for P...

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Bakam, Genevieve Mpofu, Khumbulani Mbohwa, Charles Tshwane Univ Technol Pretoria South Africa

ISBN: (纸本)9783031744815;9783031744822

Advanced manufacturing practices require smarter technologies such as crowdsourcing to enhance continuous production improvement. It happens that crowdfunding is more popular in South Africa compared to crowdsourcing especially in the manufacturing field due to the lack of technical expertise in engineering fields. Also, previous literature focused on smart factories and smart road transportation systems using industrial 4.0 initiatives without shedding light on the application of crowdsourcing and crowdsensing in railway manufacturing industries. This paper proposed a model for the e-manufacturing of trains using crowdsourcing technologies for production efficiency in railway transport manufacturing companies in South Africa. A systematic analysis based on synthetised literature and empirical evidencewas employed to compile factors enabling crowdsourcing initiatives and to design a transformative crowdsourcing manufacturing (TCM) model. Findings showed that a well-defined manufacturing process, network collaborators, crowdsourcing platforms, crowdsourcing forms, systems communication and participation are core factors enabling crowdsourcing execution regarding well-designed trains and railway innovations in railway transportation systems. Despite the lack of public data sharing, cyberattacks, a less digitalized country and an uneducated crowd in South Africa, the proposed TCM model revealed that crowdsourcing is a problem-solving and decision-making tool that promotes productivity, efficient trains, effective booking and payment systems leading to passenger satisfaction, inclusive growth and sustainability. However, the South African government should define a conducive regulatory system and compatible network communication infrastructures that enable the deployment of crowdsourcing ingenuities to revitalise the railway transport system.

关键词： E-manufacturing Crowdsourcing production efficiency transport system and South Africa

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Semantic Knowledge Representation in Asset Administration Shells: Empowering Manufacturing Utilization 33rd

Semantic Knowledge Representation in Asset Administration Sh...

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Elshafei, Basem Martinez-Arellano, Giovanna Chaplin, Jack C. Sanderson, David Ratchev, Svetan Univ Nottingham Inst Adv Mfg Nottingham NG7 2RD England

ISBN: (纸本)9783031744815;9783031744822

Within the context of Industry 4.0 and the Reference Architecture Model Industrie 4.0, the Asset Administration Shell (AAS) framework has emerged as a critical component for implementing Digital Twins that facilitate a seamless data exchange within a manufacturing ecosystem. The concept enables asset communication across various application domains, organizing the design and interaction amongst manufacturing components while capturing key information relating to assets such as operational parameters, intrinsic properties, and technical functionalities. Each category of information is stored within the AAS in a structure called a sub-model, while specific properties are stored as sub-model elements. Moreover, the literature presents a gap in post-processing the information contained within the sub-models to generate data-driven decisions and the bidirectional data exchange with the AAS. Additionally, the developing concept behind AAS requires demonstration with manufacturing cases of what can be done with the information in the submodels of the AAS. This research explores the practical implementation of AAS in a manufacturing context and the tools used in their development. An approach is developed to map a semantic ontology representation from the AAS structure. The semantic structure of the information enables querying and reasoning about the data, which contributes to better understanding among diverse manufacturing components, enabling enhanced monitoring and decision-making. The use case utilizes parameter data from the AAS to estimate a key performance Indicator, Overall Equipment Effectiveness (OEE), and stores the value back in the AAS. Utilizing this approach contributes to optimizing manufacturing efficiency and productivity within manufacturing production.

关键词： Asset Administration Shell Semantic Ontology Digital Twin Key Performance Indicator

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