Erdem Ozturk

The engineering team at PDSVISION UK simulates a mechanism within a transmission system. A rigid body dynamics simulation was performed to evaluate the performance of this mechanism to help understand its behaviour for different engine speeds and input torques. #Ansys Motion, the multi-body / rigid-body dynamics (MBD/RBD) package offered by Ansys, was used to perform a study to investigate the complex behaviour of the mechanism in order to understand the system’s performance. Multi-body dynamics is a powerful simulation tool, it simplifies the transient dynamic behaviour of a complex system, allowing users to identify potential design issues before a product is even built and tested. The use of rigid bodies means that massively complex moving systems which would be difficult to simulate using traditional FE methods can be modelled in their entirety instead of having to simplify the system in order to keep simulation solve times down. This analysis allowed the customer to have increased confidence in their designs and diagnose issues, allowing for improved transmission performance. Learn more & discover how our #simulationsolutions can help transform your analysis >

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✈ News: New strategy and roadmap sets 2028 deadline for additive manufacturing advancements A new ATI additive manufacturing (AM) strategy and roadmap published today sets out the actions needed by 2028 for UK aerospace to capitalise on the AM market which is expected to reach £10bn by 2033. The vision for 2030 is an order of magnitude growth in the number of flying AM parts in civil aerospace, designed and delivered by a fully capable end to end UK supply chain. To realise this, it is crucial to synchronise technology development with the product decisions that key industry stakeholders are expected to take in the 2028 timeframe in preparation for next generation commercial aircraft. Alex Hickson, Head of Technology – Structures, Manufacturing & Materials, ATI and co-author of the roadmap said: “Advancing capabilities and getting additive manufactured parts onto aircraft is a key enabler on the journey to Destination Zero. This roadmap provides the strategic direction and key milestones which are key to delivering UK competitiveness in this area and securing the economic benefits on offer.” The roadmap targets four key challenge areas: ⛓ supply chain resilience ✅ more efficient qualification 📉 reducing part cost 📈 increasing application opportunities The ATI AM Strategy and Roadmap was developed together with MTC - Manufacturing Technology Centre following consultation with OEMs together more than 50 partners from across the aerospace supply chain. Featured case studies from Airbus, Eaton, GKN Aerospace and Rolls-Royce explore the benefits of AM across parts production, thermal management and MRO. The ATI AM Strategy and Roadmap is now available to download on the ATI website. Read more: https://lnkd.in/eNeMHVrW Cross-cutting enabling technologies and additive manufacturing will feature in an expert panel session at ATI Conference 2024 on 8th & 9th October at the ICC Wales, Newport. The agenda is out now at www.ati.org.uk/conference where tickets can also be purchased. 📸 Photo credit: Parker Meggitt #DestinationZero #AdditiveManufacturing #AM #Roadmap #AdvancedManufacturing #Aerospace

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The page is from the wonderful recent open access paper In situ observation and reduction of hot-cracks in laser additive manufacturing Yunhui Chen, Duyao Zhang, Patrick O’Toole, Dong Qiu, Marc Seibold, Klaus. Schricker, Jean-Pierre Bergmann, Alexander Rack & Mark Easton (NATURE) Communications Materials volume 5, Article number: 84 (2024) https://lnkd.in/ecJd_kW5 This recent (May 2024) paper, using sophisticate and expensive experimental tools like synchrotron radiation facilities, needed to couple process history - time - with materials parameters. In my much simpler case if one would like - maybe just for a preliminar evaluation of solidification cracking of a specific metallic material - it could be wise to use the approach by prof. Sindo Kou, which recently he proved to be comparable to RDG Rappaz Drezet Gremaud. In such a "static preview" the 9 formulas reported here are (preliminarly) substitued by one (numerical derivative) One point in favour of this approach is that the data(bases) that one uses in "my" case are of thermodynamic origin, they could be commercial, such in this case, or open. In both cases hypotheses may be tested; for instance, plotting the numerical derivative of the Scheil curve, relating Temperature T ( first column of the Excel files, here in K degrees) to the solid fraction fs ( which is usually reported from 0 - all liquid - to 1 - all solid) third column of the Excel files . The Sindo Kou approach may be viewed in the the Excel files; the square root of solid fraction fs is at column AZ, while the (-) derivative of the temperature with the square root of the solid fraction fs is at column BA For my students Excel files relevant to the two Al metallic alloys here AA6061 and AlSi10Mg, with calculations using Computherm Pandat 2018 and PanAl2014 thermodynamic database are respectively at my "private" teaching site for this 2024 (Computational) Metallurgy Course The files are Respectively AA6061 https://lnkd.in/dY9VHjeC and AlSi10Mg https://lnkd.in/dQBxwGGA Do not download them directly from Linkedin, but (assuming the site is secure!) copy and past the link, just if you would like... Yet probably your browser will qualify even those Excel files as "insecure", never mind, in the remote case someone would be interested, one can still require them by email at metallurgia24 at gmail dot com Sorry, I do not have secretaries or assistants for making this specific task... more troubleless

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📢 Modelling Process Monitoring Data in Laser Powder Bed Fusion: A Pragmatic Route to Additive Manufacturing Quality Assurance' Quality assurance in laser powder bed fusion and metal additive manufacturing is a significant challenge due to large and cumbersome datasets. This paper proposes a pragmatic approach to model process monitoring data using a straightforward algorithm. By fitting the algorithm to experimental data, key process parameters are better understood, with predictability improving at higher energy levels, achieving an R² of up to 0.8. Key takeaways: - Two behavioural regimes identified: low sensitivity at energy densities below 0.2 J/mm and more predictable outcomes above this threshold. - The approach lays the groundwork for a generalized predictive tool to address quality assurance challenges. - Future improvements will focus on refining methodologies to handle noise, geometry, and systematic behaviours. This study opens up new pathways for intelligent build planning and individual build validation by pre-emptively assessing challenging features and strategies. It’s an exciting development in the pursuit of enhanced reliability and accuracy in additive manufacturing! #LaserPowderBedFusion #AdditiveManufacturing #QualityAssurance #ProcessMonitoring #ManufacturingInnovation Luke Carter

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Please take a look at our July newsletter for recent updates from Frewer Engineering

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Powerful insights from Stephen McCartney at Advanced Engineering UK on the value of AI use in the Composites sector. Exciting examples of: 🔬 Microscopy analysis 🎯 NDT defect detection 🎚️ Live composite moulding process control 🧠 Knowledge management Steve's parting comment: "AI's best applications now are to augment, not replace, people. Don't trust AI in isolation!" Reach out to Steve if you have interest in the area and would like to explore working with High Value Manufacturing Catapult in developing/using our "AI in Engineering test bed".

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New Paper: Analyzing the Interplay of Sintering Conditions on Microstructure and Hardness in Indirect Additive Manufacturing of 17‑4PH Stainless Steel Indirect #AM methods have recently attracted attention from researchers thanks to their great potential for cheap, straightforward, and small-scale production of metallic components. Atomic diffusion additive manufacturing (#ADAM), a variant of indirect AM methods, has recently been developed based on fused deposition modelling and metal injection moulding. However, there is still limited knowledge of the process conditions and material properties fabricated through this process, where #sintering plays a crucial role in the final consolidation of parts. Therefore, this research systematically investigates this aspect for the first time. https://lnkd.in/dGsJRfmD This research has been implemented at the Integrated Additive Manufacturing Center at Politecnico di Torino in collaboration with Markforged Inc. Special thanks to Markforged Inc., Erika Lannunziata, Mohammad Hossein Mosallanejad, Manuela Galati, and Gabriele Piscopo for their contribution. #additivemanufacturing #Sintering #consolidation #research #collaboration

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💦Exciting Collaboration within High Value Manufacturing Catapults 🇬🇧 MTC - Manufacturing Technology Centre and AMRC Cymru, part of The University of Sheffield, have teamed up to design a reconfigurable factory system for scalable production of both #fuelcells and #electrolysers. Key Benefits: • Cost Savings: By utilizing common resources and components. • Risk Reduction: Flexible production systems to adapt to varying demands. • Future-Proofing: Digital manufacturing solutions for optimized reconfigurability and efficiency. Key Outcomes: • Detailed assessment of commonalities in assembly technologies. • Three conceptual designs for automated cell stacking using robotics. • Virtual evaluations of bi-product manufacturing systems. • Optimized production designs and capacity comparisons. • Implementation of an operational digital twin for adaptive scheduling. Cameron Blackwell, Hydrogen Technical Lead at MTC, says, “This strategic collaboration showcases how the High Value Manufacturing Catapult supports UK manufacturing businesses to maximise the benefits of the hydrogen economy.” 📈 The hydrogen economy is evolving, and this collaboration ensures we’re ready to meet future demands. 🌱 #Hydrogen #ManufacturingInnovation #SustainableEnergy #FuelCells #Electrolysers #DigitalManufacturing #ReconfigurableFactories #MTC #AMRC #UKManufacturing

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XPS Metrology Survey - part 2 Here is a set of C (1s) XPS spectra from naturally formed native metal oxides. These are clipped down so that the bottom can conduct if possible. I did not scrape the bottom side.

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Our article "Effect of SiC interlayer on microstructure and joint strength of Cu-Al welds obtained using a new friction processing method" is published in "CIRP Journal of Manufacturing Science and Technology" and is now online. This article carefully investigates how, SiC particles expose nascent surfaces of Al-Cu, promote interdiffusion, and enhance wetting when there will be local melting of the interface at a reduced temperature than the actual Al-Cu eutectic. SiC particles are seen to increase the fracture energy remarkably, at nearly similar electrical resistance. Additionally and surprisingly, SiC interlayer is seen to result in a lower percentage rise in joint electrical contact resistance with temperature particularly at higher current level. SiC can be an effective and cheap solution to enhance the joint strength without compromising the joint resistance. The article can be accessed from the following link with 50 days' free access. https://lnkd.in/gaGBshGk

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New Paper: Critical condition for initiation of dynamic recrystallisation in electron beam powder bed fused Ti-6Al-4 V Alloy Despite the unique capabilities of Additive Manufacturing processes for producing Ti components with complex geometries, the desired properties are only achievable if a holistic scheme is devised, considering the synergistic role of post-processing steps. This work aimed to enhance the applicability of metal AM products by improving the process chain in the manufacturing industry. This new hybrid approach, developed at the Integrated Additive Manufacturing Center at Politecnico di Torino, can broaden the use of Additive Manufacturing and Ti alloys in high-tech applications. The paper is fully open access and can be downloaded through the following link: https://lnkd.in/dj5uf3gP Mohammad Taghian Todeshki, Mohammad Hossein Mosallanejad, Hossein Mani, Ata A., Luca Iuliano Dipartimento di Ingegneria Gestionale e della Produzione - DIGEP Politecnico di Torino #additivemanufacturing #hybridmanufacturing #electronbeampowderbedfusion #electronbeammelting #EBM #Thermomechanical #Titanium #Tialloys #research #collaboration

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https://lnkd.in/dPXky5Ku Just published ( June 28th) open paper by the very active group of prof. Geoff Brooks "Supersonic coherent jets are widely in practice in steelmaking processes including electric arc furnaces (EAF). Injecting oxygen through such coherent jets plays a vital role in enhancing the liquid gas mixing and reaction rates leading to boosting energy efficiency. Several experiments and numerical simulations have been carried out to understand the physical phenomenon of the coherent jets and to predict the behavior of the jets. However, the research on pollutant formation in the coherent jets for steelmaking is limited. As the industry transitions toward reducing emissions, prediction of pollutant formation is crucial. This numerical study analyzes both methane shrouding coherent jets and hydrogen shrouding coherent jets and predicts the NOx (oxides of nitrogen) formation."

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Ever wondered how virtual commissioning works? In this clip, Stefano Catalano breaks down how we used DELMIA to control the Sigma-Tau robot in the Innovate UK-funded e-Tau project. It’s a game-changer for offline programming and laser welding! Want to dive deeper into how this could work for you? Check out the full 12-minute video here: https://lnkd.in/eA-g_R7Y and drop me a message if you’d like to set up a meeting to chat more. #VirtualCommissioning #DigitalManufacture #LaserWelding #Robotics #OfflineProgramming #DigitalTwin #3DEXPERIENCE #Delmia"

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Some interesting and positive finds in this report on the Additive Manufacturing UK website about the true impact of UK manufacturing that was launched at the MACH 2024 event. Nice to see that manufacturing accounts for £518billion of UK GDP and supports 7.3million jobs reveal new findings. Read more, https://bit.ly/3YlTAjC. #ukmfg #supportukmanufacturing #ukmanufacturing #additivemanufacturing #engineering

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How to shorten supply chains in manufacturing

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Our very own Keanu Copp has been mentioned at number one for Rob Dando's Manufacturing Top 10 for this week, which partners with Support UK Manufacturing to promote and support the incredible manufacturing industry. 👏 Keanu wrote about a report that The Additive Manufacturing UK website shared, its a great read and can be seen here: https://lnkd.in/eS73Ep87 #additivemanufacturing #engineering #engineeringrecruitment #workinengineering #workinmanufacturing #manufacturingrecruitment

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Can we use 𝗽𝗵𝘆𝘀𝗶𝗰𝘀-𝗶𝗻𝗳𝗼𝗿𝗺𝗲𝗱 𝗻𝗲𝘂𝗿𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸𝘀 to predict weld visibility in molded parts when limited experimental data are available? 🔍 Traditional methods for predicting weld line visibility in injection-molded parts usually require 𝗻𝘂𝗺𝗲𝗿𝗼𝘂𝘀 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝗹 𝘁𝗿𝗶𝗮𝗹𝘀, which can be costly and time-consuming. But what if there was a smarter approach? 🧠 Enter physics-informed neural networks (PINNs), which integrate physical laws directly into the learning process. By using physical principles, such as 𝗽𝗮𝗿𝘁𝗶𝗮𝗹 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝗹 𝗲𝗾𝘂𝗮𝘁𝗶𝗼𝗻𝘀, PINNs help to overcome the lack of extensive experimental data. This allows for the generation of highly 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲 𝘀𝘆𝗻𝘁𝗵𝗲𝘁𝗶𝗰 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀 for training machine learning models, drastically reducing the need for experimental points by up to 78%! 🔄 This novel approach doesn't just predict the temperature gradient within the molded part but associates these values with the visibility of weld lines using a simulation result known as the 𝗙𝗿𝗼𝘇𝗲𝗻 𝗟𝗮𝘆𝗲𝗿 𝗥𝗮𝘁𝗶𝗼. The result? A robust model that 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝘀 𝘄𝗲𝗹𝗹 𝗲𝘃𝗲𝗻 𝘄𝗶𝘁𝗵 𝗹𝗶𝗺𝗶𝘁𝗲𝗱 𝗱𝗮𝘁𝗮, ensuring high-quality production without the traditional costs and efforts associated with extensive data collection. 🚀 Looking forward, the potential applications of PINNs in predicting 𝗼𝘁𝗵𝗲𝗿 𝘁𝘆𝗽𝗲𝘀 𝗼𝗳 𝘀𝘂𝗿𝗳𝗮𝗰𝗲 𝗱𝗲𝗳𝗲𝗰𝘁𝘀, including sink marks and burn marks, are vast. This could provide a powerful tool for defect detection in molded parts across industries. 📖 Interested in diving deeper into this innovative method? Check out our latest research published in the prestigious 𝗝𝗼𝘂𝗿𝗻𝗮𝗹 𝗼𝗳 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 to explore how you can apply these insights to your manufacturing processes! https://lnkd.in/dZ9eYGNX Moldex3D ITALIA Moldex3D (CoreTech System Co., Ltd.) Dipartimento di Ingegneria Industriale - DII UNIPD Datapizza Giacomo Ciarlini #Manufacturing #MachineLearning #InjectionMolding #PlasticsEngineering

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Calphad Science and the Art of Steelmaking in Continuous Casting and Additive Manufacturing of Steel I Considerations using an elementary Thermodynamic // Computational Metallurgy Calphad approach Recent motivation: a visit of three distinguished colleagues from Cambridge to Udine in a long weekend Less recent motivation: a special issue of MDPI journal metals Entitled Calphad Tools for the Metallurgy of Solidification Historic motivation: myself being the first academic using metal powder bed 3d printing in Italy Prehistoric motivation: myself being for a small timespan process metallurgist of ABS Acciai after my PhD in engineering metallurgy Thermodynamics and phase diagrams are just the "Beginning of Wisdom" From being to becoming: the Scheil equation (and possible elementary variants of it) all (potentially) implemented in Calphad softwares Kinetics not only one step beyond, but we would not consider it here In metal solidification, there are many critical issues here I consider only those aspects which may be derived from a "simple" solidification curve a) cracking susceptibility coefficient (CSC) b) semi-solid sensitivity (SSS) c) growth restriction factor (Q) How should be use the information provided by a link between T and fs? Choices are T=T(fs) or fs=fs(T) Once we decide for T=T(fs) we can use information a) just from the curve b) from the (numerical) integral of the curve T=T(fs) c) from the (numerical) derivative of the curve T=T(fs) From the Art of Steelmaking we should try at least to consider process variables, for Continuous Casting (CC) and Additive Manufacturing (AM) It appears that in the younger technology AM process variables are many, but not as many as in CC Designing "disruptive" new steels would involve also processing; considering them at an early step of the "new product design" would spare time, indeed. Moreover with "exotic" composition would need physical properties which are currently not available - often at all. Focusing on CSC for both processes Clyne (Davis) model is the winner in term of longevity ( 50 years) Kou model is interesting being derived directly from a solidification curve, and has been used originally with Computherm Pandat Easton model is less widespread, but all these models have now been implemented in last (2024A) version of Thermo-Calc In specific modeling softwares, Rappaz-Drezet-Gremaud Hot Tearing Criterion is highly considered by some solidification software The first model is looking at the T=T(fs) function, the second model to its derivative (with the square root of fs) Easton and Rappaz criterion consider the integral of T=T(fs) Some recent papers - up to May 2024 - considers specific criteria for AM, which are close to CC to be continued later and, possibly, improved by visuals by the best of my students, this week, interacting with myself and other colleagues involved M. Balart  H.D.K.H. Bhadeshia B. Clyne F. Maurigh S. Miani S. Ooi B. Sundman

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Additive manufacturing has the potential to revolutionise industries with reduced waste, lower energy consumption and complex design capabilities. Despite cost and speed limitations, it's impacting aerospace, medical and energy sectors. Neil Ballinger explains why additive manufacturing isn't universally adopted yet 👉 https://bit.ly/3Y85qOd #AdditiveManufacturing #InnovationInIndustry #ManufacturingTech #AMImpact #EUAutomation

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