دانلود مقاله همزاد دیجیتالی و اینترنت اشیای صنعتی
خلاصه
1. معرفی
2. پیشینه و تعریف
3. فن آوری های کلیدی فعال
4. DT ها از موارد و کاربردها در تولید استفاده می کنند
5. پیامدهای اقتصادی و زیست محیطی
6. درایورهای DTs
7. چالش ها، تهدیدها و موانع DTs
8. خلاصه و نتیجه گیری
9. تحقیقات آینده
اعلامیه منافع رقابتی
در دسترس بودن داده ها
منابع
Abstract
1. Introduction
2. Background and definition
3. Key enabling technologies
4. DTs use cases and applications in manufacturing
5. The economic and environmental consequences
6. DTs drivers
7. DTs challenges, threats, and obstacles
8. Summary and conclusions
9. Future research
Declaration of competing interest
Data availability
References
چکیده
اینترنت صنعتی اشیا (IIoT) و همزاد دیجیتالی (DTs) نحوه تعامل مدل‌های دیجیتال و محصولات فیزیکی را تغییر می‌دهند. IIoT به هوش در دنیای فیزیکی متصل می شود و DT ها عملاً همتایان فیزیکی خود را نشان می دهند. در نتیجه، DTها برای آزمایش و شبیه سازی پارامترهای جدید و انواع طراحی بسیار ارزشمند خواهند بود. با این حال، با وجود پتانسیل غیرقابل انکار DT ها، آنها هنوز نمی توانند خود را از فناوری های شبیه سازی متمایز کنند، و کاربرد و پذیرش آنها محدود است. این مطالعه مفهوم را تعریف می کند، تکامل و توسعه DT ها را برجسته می کند، فناوری های فعال کننده کلیدی آن را بررسی می کند، نقش IIoT را به عنوان ستون فقرات DT ها شناسایی می کند، روند DT ها را بررسی می کند، چالش های کلیدی را برجسته می کند، و کاربردهای آن را در فرآیند تولید و صنعت 4.0 بررسی می کند.
Abstract
The Industrial Internet of Things (IIoT) and Digital Twins (DTs) are changing how digital models and physical products interact. IIoT connects to intelligence in the physical world, and DTs virtually represent their physical counterparts. As a result, DTs will be invaluable for testing and simulating new parameters and design variants. However, Despite the undeniable potential of DTs, they still cannot differentiate themselves from simulation technologies, and their application and adoption remain limited. This study defines the concept, highlights the evolution and development of DTs, reviews its key enabling technologies, identifies IIoT’s role as the backbone of DTs, examines DTs trends, highlights the key challenges, and explores its applications in the manufacturing process and Industry 4.0.
Introduction
The industrial sector has experienced a significant transformation due to several factors, the most notable being the shift in how products are sold, from the factory floor to the point of sale [1]. Over the past 15 years, there has been a growing trend among consumers to embrace e-commerce and digital channels for their purchasing needs [2], [3] Buyers’ habits changed to home ordering–a shift that industry experts forecast to be permanent. This consumer shift brought changes to supply chain disruptions — a dramatic need for increased agility and resilience in the consumer product manufacturing industries. As a result, manufacturers incorporated robust digital platforms in a post-pandemic marketplace to maintain competitiveness, optimize their manufacturing value chain, and provide end-to-end supply chain visibility [4], [5]. According to a new survey, manufacturing companies leveraging digital technologies to transform their operations have reduced costs by 5–30 percent, increased productivity by 5–40 percent, and achieved substantial agility and sustainability improvements [6].
The second factor having a correlating impact on industrial companies’ business models is COVID-19. The pandemic has led to significant disruptions affecting nearly every aspect of global industry [4]. While supply chain disruptions have uncovered operational vulnerabilities, they have also presented transformative opportunities for manufacturing companies [7]. Manufacturers quickly adapted during disruptions by implementing new advanced technologies at the core of true fourth industrial revolution innovation [6]. The swift advancement of digital technology and designed intelligence has driven the 4th industrial revolution [8]. Similarly, Industry 4.0 helped advance the usage of technologies like the Industrial Internet of Things (IIoT) and DT and enabled progress and betterment in the industries that utilize DT [9], [10], [11].
Summary and conclusions
In the post-pandemic, manufacturers use digital transformation to gain much-needed agility by improving supply-chain visibility, creating feasible production plans, deploying advanced production planning and scheduling, and providing visibility, transparency, and traceability to consumer demand. We analyzed the use of DT and showed that DT technology with IoT capabilities has emerged as a critical concept in the digital transformation of the industry. It is used in Industry 4.0 and connected digital factories. The construction of DTs can be tailored for various objectives, including the conceptualization, production, examination, modeling, and management of non-digital systems. This is done to comprehend, supervise, and potentially enhance the real system. This paper explored the possibilities, challenges, and limitations of DT implementation and its use in different manufacturing domains. Research concerning DT solutions in manufacturing deals with production planning and control, the primary data sync within a production system that ties everything together. Supply chain and logistics management is another area where use cases of DT are reviewed in the literature.
DTs have been effectively utilized across various application fields, positioning them as a crucial component in Industry 4.0. Combining DTs and IIoT can enable new business models, such as predictive or product-as-a-service maintenance. In addition, with the ability to monitor and analyze data from multiple sources in real-time, companies can offer new value-added services to their customers. Overall, implementing DTs and IIoT can unlock significant benefits for industries regarding operational efficiency, cost savings, and new business opportunities.