3D surface representation and trajectory optimization with a learning-based adaptive model predictive controller in incremental forming

Wang, Chenhao; He, An; Weegink, Kristian J.; Liu, Sheng; Meehan, Paul A.

doi:10.1016/j.jmapro.2020.08.062

Cited by 9 publications

(5 citation statements)

References 22 publications

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“…Toolpath optimisation with a learning-based adaptive model predictive controller was used by Wang et al [191]. The geometric errors considered in the model were the bending effect error close to the fixed zone of the part, the pillow effect error at the bottom of the part, and the springback error in the wall zone.…”

Section: Toolpath and Toolpath Strategiesmentioning

confidence: 99%

Emerging Trends in Single Point Incremental Sheet Forming of Lightweight Metals

Trzepieciński

Oleksik

Pepelnjak

et al. 2021

Metals

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Lightweight materials, such as titanium alloys, magnesium alloys, and aluminium alloys, are characterised by unusual combinations of high strength, corrosion resistance, and low weight. However, some of the grades of these alloys exhibit poor formability at room temperature, which limits their application in sheet metal-forming processes. Lightweight materials are used extensively in the automobile and aerospace industries, leading to increasing demands for advanced forming technologies. This article presents a brief overview of state-of-the-art methods of incremental sheet forming (ISF) for lightweight materials with a special emphasis on the research published in 2015–2021. First, a review of the incremental forming method is provided. Next, the effect of the process conditions (i.e., forming tool, forming path, forming parameters) on the surface finish of drawpieces, geometric accuracy, and process formability of the sheet metals in conventional ISF and thermally-assisted ISF variants are considered. Special attention is given to a review of the effects of contact conditions between the tool and sheet metal on material deformation. The previous publications related to emerging incremental forming technologies, i.e., laser-assisted ISF, water jet ISF, electrically-assisted ISF and ultrasonic-assisted ISF, are also reviewed. The paper seeks to guide and inspire researchers by identifying the current development trends of the valuable contributions made in the field of SPIF of lightweight metallic materials.

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Section: Toolpath and Toolpath Strategiesmentioning

confidence: 99%

Emerging Trends in Single Point Incremental Sheet Forming of Lightweight Metals

Trzepieciński

Oleksik

Pepelnjak

et al. 2021

Metals

View full text Add to dashboard Cite

show abstract

“…A mastery of modeling the toolpath strategy and the contact between the tool and the sheet is also required. In fact, investigations on toolpath strategies used in incremental sheet forming still attract many researchers until the last two years such as the work of Bonnardot et al, 5 Fabian et al, 6 Wang et al, 7 Grimm et al 8 and Sattar et al 9 New innovative technics have been used in these works to generate the optimized tool path that improved the accuracy and precision of the finished product made using ISF technics. Several solutions have been proposed through these optimizations to reduce material damage and springback occurring in incremental local deformation and to enhance the geometric accuracy and productivity of ISF process.…”

Section: Introductionmentioning

confidence: 99%

The incremental sheet forming; technology, modeling and formability: A brief review

Said

2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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The constant need to improve manufacturing processes and production methods, with the aim of making these processes more flexible and precise, and subsequently solving problems of conformity, quality of manufactured parts and productivity, drives manufacturers to develop original manufacturing techniques. The incremental sheet metal forming process, one of these novel techniques, has attracted a great deal of attention in recent decades. This paper presents a review of recent work done in this area and captures ideas for future work based on studies conducted by several researchers. A review of advanced investigations considering the following terms of interest: process, tools, formability, modeling and simulation is developed. Overall, it can be said that ISF process still requires further research to exploit the fabrication of new materials such as novel nanocomposites and Functionally graded materials (FGM). Test the performance of 4- and 5-axis CNC machines to manufacture industrial parts. Finally, apply new hybrid technics at the aim to improve the geometric accuracy, formability and the productivity of ISF process.

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“…The findings were useful for the prediction of parameters, such as temperature distribution and forming force, and facilitated estimation of microstructural evolution during the process. Wang et al [23] developed an online adaptive shape predictive model for the purposes of predicting the forming geometry within each incremental step. The model was incorporated into a coupled constrained control algorithm so as to minimise geometric error and to optimise the potential step which could provide an accurate tool path to improve geometric accuracy.…”

Section: Introductionmentioning

confidence: 99%

Application of machine learning on tool path optimisation and cooling lubricant in induction heating-assisted single point incremental sheet forming of Ti-6Al-4V sheets

Chen

Hassan

et al. 2022

Int J Adv Manuf Technol

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Induction heating-assisted single point incremental sheet forming was established for Ti-6Al-4V thin sheets at closed and above beta-transus temperature (980 °C). In order to eliminate geometric inaccuracy and adherence of lubricant on the surface caused by elevated temperature, a cooling lubricant system was designed for the forming tool to decrease the thermal expansion and friction. A radial basis function (RBF)-based tool path optimisation was developed to study the measured geometric accuracy, temperature, and forming force. By adjusting cooling lubricant control and integrating the RBF framework, the first optimised tool path was used to collect the results and to validate with the finite element (FE) model and theoretical geometric profiles. The output data were further studied by RBF and generate a second optimised tool path. The measured geometric coordinates revealed that the error percentage has been reduced to less than 5%. Further, the microstructure evolution analysed by scanning electron microscopy (SEM) indicated noticeable oxidation and alpha-layer for temperature around 1040 °C and the phenomenon was removed at temperature closed to 950 °C. The surface roughness and energy-dispersive X-ray analysis (EDX) revealed the optimised tool path distributed significant improvement in surface quality. The cooling lubricant system indicated optimal performance with RBF optimised tool path to support constant temperature and reduce friction and lubricant adherence on the surface.

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3D surface representation and trajectory optimization with a learning-based adaptive model predictive controller in incremental forming

Cited by 9 publications

References 22 publications

Emerging Trends in Single Point Incremental Sheet Forming of Lightweight Metals

Emerging Trends in Single Point Incremental Sheet Forming of Lightweight Metals

The incremental sheet forming; technology, modeling and formability: A brief review

Application of machine learning on tool path optimisation and cooling lubricant in induction heating-assisted single point incremental sheet forming of Ti-6Al-4V sheets

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