A digital twin defined autonomous milling process towards the online optimal control of milling deformation for thin-walled parts

Abstract

Thin-walled parts are widely used in the aerospace industry, where the milling deformation of the parts caused by their thin-walled draping and extremely large size ratio characteristics as well as high material removal rate has been the most common quality issue that greatly influences the assembly performance and operation safety of aerospace equipment.Hence, effective management of milling deformation of a thin-walled part will significantly improve its quality, which, however, is still made difficult by the lack of a real-time deformation perception, optimization, and control method. To bridge the gap, this paper proposes a novel online optimal control method of milling deformation for thin-walled parts by incorporating digital twins into the milling process of thin-walled parts. To this end, a reference framework of the milling process digital twin (MPDT) for thin-walled parts are designed, where the autonomous operation logic of MPDT for online optimal control of milling deformation is further clarified. On that basis, three key enabling technologies of MPDT are introduced from the perspective of multidimensional high-fidelity MPDT modeling, knowledge-driven lowlatency milling deformation simulation, and online optimal control of milling deformation, which provide an insight into the industrial implementation of MPDT. In addition, a MPDT prototype system is implemented, where its application and evaluation results demonstrate the feasibility and effectiveness of the proposed approach.

Generative AI and digital twin integrated intelligent process planning：A conceptual framework

“…Digital twin, is de ned as an integrated multi-physics, multi-scale, probabilistic simulation of an as-built product, system, or process which can mirror the life of its corresponding twin using available physical models, history knowledge, and real-time data [73], is nowadays regarded as the key for the convergence of physical systems and cyber systems [74]. The vigorous development of digital twin technology has provided a novel solution for both intelligent machining and Zero Defect Manufacturing (ZDM), demonstrating its potential in product quality management [75,76].…”

“…The vigorous development of digital twin technology has provided a novel solution for both intelligent machining and Zero Defect Manufacturing (ZDM), demonstrating its potential in product quality management [75,76]. Building upon this foundation and drawing from the accomplishments of our research group in digital twin [74,77,78], this paper proposes the integration of GIAM with digital twin technology to evaluate and verify the process knowledge and plans generated by ProcessGPT, thereby enhancing the reliability and explainability of GIPP.…”

Multi-axis CNC finishing and surface roughness prediction of TC11 titanium alloy open integral micro impeller

“…The implementation of digital twin technology, or the interactive mapping of digital models built in virtual space and physical entities, has gradually become possible thanks to the development of new generation information technologies like the Internet of things, Big Data, Cloud Computing, and Artificial Intelligence. 35 This allows for an accurate description of the operation trajectory of a physical entity's entire life cycle. 36 Digital twins are seen as an efficient way to achieve the interactive integration of the industrial information world and the physical world, particularly in the field of intelligent manufacturing.…”

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

“…Figure 1 represents the total number of published articles in these databases regarding these periods. Reference Aerospace [10,11] Marine [13] Automotive and Autonomous Vehicular Systems [12] Healthcare [15,16,17] Agriculture [18] Electronics [14] Manufacturing Processes [19,20,21,22,23] Predictive Maintenance [24] The advent of Industry 4.0 and the digital revolution have opened up new avenues for technological advancements in various fields. One such innovation is the concept of digital twins, which holds great potential to redefine the landscape of materials engineering.…”

“…This research aims to investigate the capabilities of digital twins in predicting material behavior and optimizing manufacturing processes, ultimately contributing to the evolution of advanced materials manufacturing. Materials engineering plays a pivotal role in various industries, ranging from aerospace [10,11], automotive and autonomous vehicular systems [12], marine [13], and from electronics [14] to healthcare [15,16,17] and agriculture [18], also can be implemented to many manufacturing processes such as cutting [19,20], milling [21] and other processes [22,23] and predictive maintenance systems [24] as depicted in Table 1. The demand for advanced materials with superior performance has led to the exploration of novel techniques to enhance material behavior and optimize manufacturing processes.…”