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Incremental sheet forming (ISF) is an emerging flexible manufacturing technique. However, it is currently facing the challenge of popularization in industry since the poor geometric precision of the finished parts cannot meet the engineering standard. Aiming at enhancing product geometric precision, online path planning algorithms had been proposed by researchers. However, the existing algorithms had been applied successfully in manufacturing products with very simple geometries only and had limited capabilities of being generalized to complex products, which prevented the widespread application of ISF. To solve this long-lasting problem, more powerful and generic path planning algorithm needs to be proposed for the ISF process. In this study, an adaptive MPC-based path planning algorithm was developed for the ISF process, aiming at enhancing the geometric accuracies of products with more complex geometric features. The algorithm was formulated based on the state-space modelling of the process, the learning-based parameter identification approach, and quadratic programming optimization. The performance and the generality of the present adaptive MPC algorithm were experimentally validated in manufacturing parts with several complex geometric features that were typical in industrial parts using closed-loop ISF processes. In the first test, the present adaptive MPC algorithm showed a significant performance improvement of 56% in the reduction of maximum error on the base compared to the non-adaptive MPC. In the other two tests, the present algorithm also received satisfactory performances. Compared to the non-adaptive algorithm, the test results indicated that the present adaptive algorithm had a better performance and a higher generality. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) is an advanced control algorithm that has been successfully implemented in the on-line path optimization of computer-numerical-control (CNC) machines for performing single-pass incremental sheet forming (ISF) processes, aiming at precision enhancements of products. Multi-pass ISF technique is usually employed to manufacture parts with extremely large wall angles which cannot be achieved without failure using the single-pass ISF. However, existing studies show that the geometric precision of the products of multi-pass ISF is usually very poor, which has significantly hampered the widespread application of this technique in industry. In the present study, two control algorithms based on the MPC framework were proposed, targeting at achieving a more precise geometry of multi-pass ISF products. MPC-1 was an extension of the control algorithm for the single-pass ISF process reported in our previous work, and MPC-2 was developed for the first time. The developed MPCs were comparatively validated by a group of physical benchmark test. Compared to MPC-1, MPC-2 reduced the maximum geometric error in the wall, conjunction, and base zones on the same part by 26%, 51%, and 73%, respectively. The test results show that MPC-2 had a better performance in multi-pass ISF processes. [ABSTRACT FROM AUTHOR]

Two-point incremental forming (TPIF) shows higher forming limits than single-point incremental forming (SPIF) especially for producing complex industrial functional components. However, unexpected failure still occurs occasionally under certain forming conditions in TPIF. In this paper, the applicability of six damage models for failure prediction in TPIF is evaluated. The procedure of damage parameter calibration and finite element modelling are presented. The predicted failure depth and location with these damage models are evaluated under different loading conditions. Furthermore, the stress and strain and damage evolution in TPIF are provided and discussed in detail. It is concluded that the failure location and depth can be predicted more accurately by the Ayada model than others in this work. It is noted that once double-sided contact occurs in TPIF, it reduces the variation of triaxiality through the thickness, altering the accumulation of damage. [ABSTRACT FROM AUTHOR]

The geometrical error of the formed part is one of the most significant limitations that restricts the widespread application of incremental sheet forming (ISF) in aerospace industry. The geometry of ISF parts is dependent upon the tool path, so its correction can improve the part precision. Previous research has utilized model predictive control approach to achieve this, but the method was restricted to simple convex shapes. In this study, the tool path and the formed shape were parameterized and the analytical models of geometry responses relative to tool perturbations were proposed. Then, a model predictive control algorithm was developed, aiming at reducing the geometrical errors of the parts with complex non-convex shapes in the ISF process. Experimental validation of the developed control algorithm was carried out by forming a complex shape by single-point incremental forming. The results show that the developed control algorithm greatly reduced the geometrical error in the closed-loop process. [ABSTRACT FROM AUTHOR]

Residual stresses in metallic components greatly affect the geometrical accuracy of advanced high-strength steels (AHSS) products used for automotive industry. Chain-die forming is a promising method to fabricate AHSS products which can minimize the residual stress induced. This paper aims to understand the residual stress in chain-die-formed dual-phase (DP) steels through analytical and numerical modelling together with experimental validation. Analytical and numerical models were firstly employed to predict the stress development and associated residual stresses induced by chain-die forming in consideration of an as-received residual stress field and a comprehensive material-hardening model. The residual stresses in different regions of formed parts were practically measured using the neutron diffraction method to verify the developed models. Same as the mesh size of the examining points of finite element analysis (FEA) models, the averaged over the same sampling size is measured to guarantee the accuracy. It seems to be consistent with the simulation and experimental results in consideration of both factors. However, compared with as-received residual stress, the kinematic factor has a more dominating impact on the final residual stress. The results presented should contribute to the prediction of geometric errors and minimize product defects caused by the residual stresses in chain-die forming or equivalent sheet metal-forming industry. [ABSTRACT FROM AUTHOR]

Incremental sheet forming (ISF) is a highly flexible sheet forming process, but it suffers from poor geometric accuracy. This paper presents a feedback control strategy using model predictive control (MPC) to obtain improved geometric accuracy in ISF. Based on the incremental deformation mechanism of ISF, a novel model for shape state prediction has been proposed. The step depth of the toolpath was optimised based on shape state feedback during the forming process. Two different cases were studied for experimental validation of the developed control strategy. Comparisons between formed parts in both controlled and uncontrolled ISF processes were implemented in terms of cross-sectional profiles, formed depth at the bottom area and global deviation distribution. Results show that the geometric accuracy in ISF with feedback control has been greatly improved at the bottom area of the formed parts compared with a standard ISF approach without control. Improved geometric accuracy has been achieved on the wall of the parts as well. [ABSTRACT FROM AUTHOR]

Incremental sheet forming (ISF) has been attractive during the last decades because of its greater flexibility, increased formability and reduced forming forces. However, traditional finite element simulation used for force prediction is significantly time consuming. This study aims to provide an efficient analytical model for tangential force prediction. In the present work, forces during the cone-forming process with different wall angles and step-down sizes are recorded experimentally. Different force trends are identified and discussed with reference to different deformation mechanisms. An efficient model is proposed based on the energy method to study the deformation zone in a cone-forming process. The effects of deformation modes from shear, bending and stretching are taken into account separately by two sub-models. The final predicted tangential forces are compared with the experimental results which show an average error of 6 and 11 % in respect to the variation of step-down size and wall angle in the explored limits, respectively. The proposed model would greatly improve the prediction efficiency of forming force and benefit both the design and forming process. [ABSTRACT FROM AUTHOR]

Highlights: [•] Two open-loop analytical models for multi-pass deformation design have been developed and tested given the predicted thickness strain of the final part as a main parameter using the assumption of shear deformation. [•] A comprehensive methodology for closed-loop multi-stage deformation pass design incorporating two developed models is proposed. [•] FEA and experimental tests have been performed to validate the comprehensive closed-loop design methodology with two analytical models. [•] The proposed closed-loop pass design methodology with M2 is proved to be an effective approach to designing multi-stage deformation passes in order to quantitatively control the material flow. [ABSTRACT FROM AUTHOR]