Journal of Plasticity Engineering

Foreword of Special Column for “AI-empowered Plastic Processing”

Review of intelligent technologies for “material-process-equipment” in metal plastic forming

Metal plastic forming technology plays a crucial role in modern manufacturing, yet traditional methods face challenges such as low accuracy, poor efficiency and weak adaptability in areas like material constitutive description, process defect prediction, quality optimization and equipment control. In recent years, the rise of artificial intelligence(AI) technologies has provided innovative solutions to these issues, driving the field toward intelligent transformation. The application progress of AI in metal plastic forming was systematically summarized, with detailed discussions from three perspectives: materials, process and equipment. In terms of material constitutive modeling, the limitations of traditional phenomenological models have been overcome by data-driven approaches. Artificial neural networks(ANN) have improved prediction accuracy under single loading paths, while recurrent neural networks(RNN) simulate the historical dependencies of complex loading paths. Machine learning(ML) surrogate models accelerate the prediction of dynamic microstructural evolution. Physics-informed neural networks(PINN) and multiscale surrogate models ensure thermodynamic consistency, enabling efficient multiscale coupled simulations. In forming processes, AI leverages deep learning(DL) to predict macro defects such as wrinkling and spring back, as well as micro damage, with physics-driven coupling enhancing robustness. Intelligent optimization strategies, such as reinforcement learning, achieving closed-loop control of thickness, sheet shape and process parameters, thereby improving product quality and efficiency. In intelligent equipment control, deep learning-based fault diagnosis methods perform excellent under variable operating conditions and small sample sizes, with transfer learning boosting generalization. Frameworks for remaining useful life prediction and intelligent control of hydraulic servo systems and vibration suppression support predictive maintenance and autonomous decision-making. Overall, AI has significantly reduced the development costs of metal forming technologies, markedly improved prediction accuracy, and demonstrated feasibility in industrial scenarios. Despite challenges in interpretability and generalization, future advancements through mechanism-data fusion, few-shot learning and digital twins will effectively empower the high-quality development of metal plastic forming.

Research on application of data-driven artificial intelligence technology in forming process

With the transformation of manufacturing industry towards intelligence, the forming process, as a core link in the field of plastic engineering, is facing challenges such as difficult process optimization, low quality prediction accuracy and bottlenecks in production efficiency improvement. Artificial intelligence(AI) technology has provided a new path for solving complex problems in the forming process by virtue of its powerful data processing and modeling capabilities. Focusing on “forming process data + AI”, the application logic and practical achievements of AI technology in the manufacturing field were systematically sorted out. Firstly, the roles of the three major schools of AI in the manufacturing industry were analyzed from the perspective of cybernetics, with emphasis on the application of the behaviorist school(cybernetics) in the parameter regulation of the manufacturing process. Secondly, how the digital twin system provides structured and high-timeliness data support for AI was discussed, and the complex system integration driven by digital twin technology was constructed. Thirdly, the specific applications of machine learning algorithms(such as K-means clustering and neural network) in forming process optimization and quality prediction were analyzed in depth. Finally, aiming at the limitations of general large language models(LLM) in the manufacturing industry, a construction scheme of a vertical model for the forging field based on knowledge graph(KG) and retrieval-augmented generation(RAG) was proposed, which can provide a theoretical reference and practical path for the intelligent upgrading of the forming process.

HRDIC investigation on meso-and micro-scale nonuniform deformation of Cu-Ag alloy

Using high-resolution digital image correlation(HRDIC) technology combined with semi in-situ uniaxial tensile experiment, the meso-and micro-scale nonuniform deformation behaviors of Cu-4 Ag and Cu-20 Ag alloys were systematically investigated. The results indicate that at the micro-scale, the slip bands in the Cu-4 Ag alloy primarily converge within Cu matrix, forming periodically spaced highstrain bands. Ag particles hinder the propagation of slip bands and create strain concentration at the Cu-Ag interface. For the Cu-20 Ag alloy, with its higher volume fraction of Ag phase, slip bands concentrate to form nonuniform local high-strain zones, exhibiting three modes: impeded, unilateral penetration and complete penetration, along with synergistic deformation phenomena. At the meso-scale, the deformation uniformity of Cu-4 Ag alloy is primarily governed by the deformation of Cu matrix, whereas the Cu-20 Ag alloy, due to its higher Ag content, exhibits more pronounced deformation nonuniformity influenced by heterogeneous interfaces. Strain statistics reveal that as deformation amount increases, the mean strain of the softer Cu phase consistently exceeds that of the Ag phase, thus bearing higher strain values. The continuously rising variance reflects an increasing degree of strain dispersion, indicating progressively greater deformation inhomogeneity. As a heterogeneous dual-phase material, the as-cast Cu-Ag alloy develops strain gradients at the interface due to the differing properties of the Cu and Ag phases. This leads to the accumulation of geometrically necessary dislocations and the generation of back stress at the interface, inducing heterogeneous-induced strengthening to enhance material strength. Simultaneously, this strengthening mechanism delays necking by coordinating strain distribution across heterogeneous interfaces, thereby synergistically optimizing the strength and ductility of alloy.

Study on key parameters affecting push-spin integrated bending forming of aluminum alloy thin-walled tubes with a 0. 8D bending radius

To enhance the bending forming limit of 5A02 aluminum alloy thin-walled tubes with small bending radius, the influence of key parameters in push-spin integrated bending forming for Φ30 mm×1. 0 mm tube blanks with a bending radius of 0. 8D was investigated.Combining Abaqus finite element simulation with process experiments, the influence of tube blank feed rate V₁, spin wheel speed V₂,back pressure P and its loading path on forming quality were systematically investigated. The results indicate that reducing the tube blank feed rate V₁ can effectively suppress inner wrinkling, when V₁ decreases from 15 mm·s^-1 to 3 mm·s^-1, the inner wall thickening rate decreases by 5. 1%. Spin wheel speed V₂ plays a crucial role in improving forming quality, compared to a fixed spinneret configuration,increasing V₂ to 1. 5V₁ reduces inner wall thickening rate by 8. 0% and extends the stick-out length by 107. 8%, however, further increases of V₂ shows diminishing returns. The back pressure P requires precise control, the value below 70 MPa may cause non-adherence to the die and wrinkling, while values above 70 MPa exacerbate wall thickness non-uniformity and inhibit material elongation; based on this,an optimal process window is determined: under the back pressure P of 70 MPa, combined with the D loading path(where P undergoes linear change and reaches the maximum value at 3/4 of the tube blank stroke), high-quality bent tubes without defects can be produced.

Effect of interference amount on mechanical performance of CFRP bolted joints: Analysis and numerical simulation

Focusing on interference amount as the core process parameter, its dual influence on both the static and fatigue performance of CFRP single-lap bolted joints was systematically explored. Through conducting quasi-static tension and tension-tension fatigue tests across four interference levels, the regulatory effects of interference amount on the yield load, failure mode and fatigue life of the joint structures were quantitatively analyzed. Test results indicate that the static strength increases monotonically with the increase of interference amount,while the fatigue life exhibits nonlinear response laws of increasing first and then decreasing, and reaches peak value with interference amount of 0. 6%. Furthermore, a three-dimensional progressive damage finite element model incorporating the interference assembly effect was developed. This model couples 3D Hashin failure criterion with residual stiffness/strength degradation models and constant life equation. The simulation results align well with test data, the fatigue life across all working conditions is accurately predicted, with the maximum error below 3. 6%, and the key failure morphologies such as matrix damage around the hole are successfully replicated.

THE NEW RESEARCHE PROGRESS OF SHEET METAL STAMPING SPRINGBACK

The history and progress of springback researche in bending and 3 D shallow drawing are all\|sidedly presented in this paper with three aspects of theoretic analyzing,numerical simulating and springback controlling.The references quoted by this paper cover with the most of main methods and important achievements in springback researche.

Introduction of sheet metal hot-forming

Blank hot forming is a new technology which is realized by heating the advanced high strength steel to Austenitic phase,quick stamping,and quenching in die during press holding to meet the required cooling speed.By this new forming technology,the phase of the parts can be changed to martensite,and the strength of the parts can be about 1500MPa.In this paper,Key equipments,key technology,advantage and disadvantage of blank hot forming are introduced,and the application status and trends is proposed.

The application and development of advanced shot peen forming technologies

Some advanced shot peen forming(SPF) technologies such as the pre-stress SPF technology,the numerical SPF technology and several new type of SPF technologies including the double-sided simultaneous SPF,the Laser SPF,the ultrasonic SPF and the water-jet cavitation shotless peening technology,have been reviewed in this paper.The principle and the current developing situation of these advanced technologies have been analyzed,which will have the important signification on the research and developement of SPF technology.

Progress of crystal plasticity theory and simulations

The development history,constitutive models,and homogenization schemes of crystal plasticity theory with large deformation were reviewed. Several theoretical achievements and typical applications of crystal plasticity were outlined. The theories basis,advantages and disadvantages of both phenomenological and physically based crystal plasticity models were compared and analyzed in terms of flow models,work hardening models,and the evolution of state variables. The characteristics and applications of both mean-field and full-field crystal plasticity models were illustrated. The typical applications of crystal plasticity simulations were introduced from the aspects of anisotropy,texture evolution,non-uniform plastic deformation,formability,size effect,damage and fracture behavior,hot deformation and microstructure evolution,and virtual testing etc. And future development trends in this field were pointed out.

Present situation and prospects of stamping process planning for automobile pane ls

Stamping process planning of automobile panel are th e foundation of the die's design and manufacturing, and the key point for panel's forming satisfactorily. The present process studies on automobile panel forming such as forming ability analysis, process planning, process particular designs a nd the actuality computer aided process planning are discussed, and the trends i n press process planning for automobile panels are also analyzed in this paper.

Review on application and fabrication of shark skin bionic structure

The riblet structure of shark skin is proved to significantly effect drag reduction.The bionic riblet structure is widely applied in industry,such as aviation,naval vessels,automotives,pipe transportation and wind power generation.The fabrication of the bionic riblet structures focuses on two styles:simplified riblet structure and shark placoid scales directly replication.As to the former style,the typical technologies of micro-riblet rolling,diamond profile grinding,femtosecond laser ablation are reviewed.And the technologies of micro-thermal pressing,solidification,micro-casting,mirco/nano-rolling and soft lithography are also reviewed for the latter style.Finally,the suggestions on the riblet structure fabricating are presented.