Malzeme Mühendisliğinde Gelişmiş Malzeme Davranışı Tahmini ve Üretim Süreci Optimizasyonu için Dijital İkizler ve Uygulamaları

Year 2023, Volume: 6 Issue: 2, 172 - 190, 31.12.2023

Erkan Tur

https://doi.org/10.55117/bufbd.1303782

Abstract

Endüstri 4.0'ın gelişi ve dijital devrim, malzeme mühendisliğini yeniden tanımlama potansiyeline sahip dijital ikizler gibi yenilikçi teknolojileri ortaya çıkardı. Fiziksel varlıkların sanal temsilleri olan dijital ikizler, malzeme davranışını modelleyebilir ve tahmin edebilir, malzemelerin gelişmiş tasarımını, test edilmesini ve üretilmesini sağlar. Bununla birlikte, malzeme mühendisliğinde tahmine dayalı analiz ve süreç optimizasyonu için dijital ikizlerin kapsamlı kullanımı büyük ölçüde keşfedilmemiş durumda bulunmaktadır. Bu araştırma, dijital ikizlerin malzeme davranışını tahmin etme ve üretim süreçlerini optimize etme konusundaki yeteneklerini araştırarak, bu ilgi çekici kesişimi derinlemesine incelemeyi ve böylece gelişmiş malzeme üretiminin gelişimine katkıda bulunmayı amaçlamaktadır. Çalışmamız, dijital ikiz kavramının ve bunların malzeme mühendisliğindeki özel uygulamalarının ayrıntılı bir araştırması ile başlayacak ve sanal bir ortamda karmaşık malzeme davranışlarını ve süreçlerini simüle etme yeteneklerini vurgulayacaktır. Daha sonra, mekanik özellikler, arıza modları ve faz dönüşümleri gibi çeşitli malzeme davranışlarını tahmin etmek için dijital ikizlerden yararlanmaya odaklanacağız ve dijital ikizlerin sonuçları doğru bir şekilde tahmin etmek için tarihsel veriler, gerçek zamanlı izleme ve gelişmiş algoritmaların bir kombinasyonunu nasıl kullanabileceğini göstereceğiz. Ayrıca, dijital ikizlerin döküm, işleme ve eklemeli imalat dahil olmak üzere malzeme üretim süreçlerini optimize etmedeki rolüne değinerek dijital ikizlerin bu süreçleri nasıl modelleyebileceğini, olası sorunları nasıl tanımlayabileceğini ve en uygun parametreleri nasıl önerebileceğini göstereceğiz. Avantajları ve zorlukları da dahil olmak üzere malzeme mühendisliğinde dijital ikizlerin uygulanmasına ilişkin pratik bilgiler sağlamak için ayrıntılı vaka çalışmaları sunacağız. Araştırmamızın son bölümü, veri kalitesi, model doğrulama ve hesaplama talepleri gibi dijital ikizlerin uygulanmasındaki mevcut zorlukları ele alacak, potansiyel çözümler önerecek ve gelecekteki yönleri özetleyecektir. Bu araştırma, malzeme mühendisliğinde dijital ikizlerin dönüştürücü potansiyelinin altını çizmeyi ve böylece daha verimli, sürdürülebilir ve akıllı malzeme tasarımı ve üretim süreçlerinin önünü açmayı amaçlamaktadır.

Keywords

Dijital İkiz, Endüstri 4.0, Proses Optimizasyonu, İleri Malzemeler, Malzeme Davranış Tahmini

Harnessing the Power of Digital Twins for Enhanced Material Behavior Prediction and Manufacturing Process Optimization in Materials Engineering

Abstract

The advent of Industry 4.0 and the digital revolution have brought forth innovative technologies such as digital twins, which have the potential to redefine the landscape of materials engineering. Digital twins, virtual representations of physical entities, can model and predict material behavior, enabling enhanced design, testing, and manufacturing of materials. However, the comprehensive utilization of digital twins for predictive analysis and process optimization in materials engineering remains largely uncharted. This research intends to delve into this intriguing intersection, investigating the capabilities of digital twins in predicting material behavior and optimizing manufacturing processes, thereby contributing to the evolution of advanced materials manufacturing. Our study will commence with a detailed exploration of the concept of digital twins and their specific applications in materials engineering, emphasizing their ability to simulate intricate material behaviors and processes in a virtual environment. Subsequently, we will focus on exploiting digital twins for predicting diverse material behaviors such as mechanical properties, failure modes, and phase transformations, demonstrating how digital twins can utilize a combination of historical data, real-time monitoring, and sophisticated algorithms to predict outcomes accurately. Furthermore, we will delve into the role of digital twins in optimizing materials manufacturing processes, including casting, machining, and additive manufacturing, illustrating how digital twins can model these processes, identify potential issues, and suggest optimal parameters. We will present detailed case studies to provide practical insights into the implementation of digital twins in materials engineering, including the advantages and challenges. The final segment of our research will address the current challenges in implementing digital twins, such as data quality, model validation, and computational demands, proposing potential solutions and outlining future directions. This research aims to underline the transformative potential of digital twins in materials engineering, thereby paving the way for more efficient, sustainable, and intelligent material design and manufacturing processes.

Keywords

Digital Twins, Industry 4.0, Process Optimization, Material Behavior Prediction, Advanced Materials

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