Development of Tool Paths for Multi-axis Single Stage Incremental Hole-flanging

Besong, Lemopi Isidore; Buhl, Johannes; Ünsal, Ismail; Bambach�, Markus; Polte, Mitchel; Blumberg, Julian; Uhlmann, Eckart

doi:10.1016/j.promfg.2020.04.290

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…Tool path definition is one of the crucial parts of design and fabrication of sheet metal parts formed by SPIF [10,16]. It was notice that proper definition as well as generation of tool path is significant process because it influences the geometric accuracy of formed parts [26]. Besides this it was also gathered that proper generation of tool path in incremental forming also influences resultant force acting on tool as well as on forming limit [26].…”

Section: Discussionmentioning

confidence: 99%

“…In the present work, tool path for various geometries of hole flanges were presented and proper selection of tool path is quite interrelated with the three different output parameters namely geometry accuracy, resultant forces, and forming limit [10,11,26]. Therefore, tool path for hole flanging should be selected on the basis of such tool path which yield geometric accuracy, low resultant force on forming tool and higher forming limit [10,11,26]. Another aspect of selection of optimized tool path depends upon step size of tool path and speed of tool which in turn reduces the surface roughness of hole flanges [26].…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, tool path for hole flanging should be selected on the basis of such tool path which yield geometric accuracy, low resultant force on forming tool and higher forming limit [10,11,26]. Another aspect of selection of optimized tool path depends upon step size of tool path and speed of tool which in turn reduces the surface roughness of hole flanges [26].…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Tool path planning for hole-flanging process using single point incremental forming

Mohan,

Dewang,

Sharma

2024

MATEC Web Conf.

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Hole-flanging is a process used to create flanges around holes in sheet metal parts. It traditionally relies on dies and punches, posing cost and time challenges for small quantities or prototypes. While Incremental forming does not require dedicated sets of tools and dies, and it provides more flexibility and adaptability with enhanced formability, and emerged as a better alternative to conventional press forming. However, precise and efficient tool path planning is essential to achieve high-quality hole-flanged components. Precise toolpath planning is one of the crucial and important part in designing of hole flanging process for both through numerical simulations and experiments. The objective of the present work is to generate tool paths as well as associated G-codes using MATLAB code for different geometries of incremental hole flanging process using SPIF. Six different geometries of hole flanges were considered to generate tool path using MATLAB code. The proposed methodology was successfully applied for different shapes of hole flanges. Since the proposed methodology provides unified programming technique in the current MATLAB environment, which performs dual duties, creating toolpath coordinates against time data and outputting a G-code file and it saves computational time and programming efforts. Hence, proposed methodology is found to be better for incremental hole flanging in contrast to previously existed methodology for development of toolpath for incremental forming cases. Thus, it was concluded that this proposed methodology can be effective for capturing any intricate shapes for incremental hole flanging. You should leave 8 mm of space above the abstract and 10 mm after the abstract. The heading Abstract should be typed in bold 9-point Arial. The body of the abstract should be typed in normal 9-point Times in a single paragraph, immediately following the heading. The text should be set to 1 line spacing. The abstract should be centred across the page, indented 17 mm from the left and right page margins and justified. It should not normally exceed 200 words.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Tool path planning for hole-flanging process using single point incremental forming

Mohan,

Dewang,

Sharma

2024

MATEC Web Conf.

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“…[27]. Using industrial robots as manipulators further increases flexibility and provides opportunities to form flanges in hard-to-reach areas with novel process strategies such as overbending as well as inclined or undercutted flanges [28,29]. However, due to the low stiffness of industrial robots, the process force Fp causes unwanted tool deflections u and results in low machining accuracies.…”

Section: High-precision Robot Manufacturingmentioning

confidence: 99%

Recent Advances in Precision, Sustainability and Safety of Machine Tools

Eckart

2023

Journal of Machine Engineering

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Machine tools are the main driver of economic, environmental and social sustainability in industrial production. The ongoing shift from mass production to highly individualized, small batch manufacturing requires machine tools to be more flexible to changing needs while maintaining at least the same level of productivity. However, flexibility and productivity are at odds with the necessity for resource and energy efficiency. At the same time, more sophisticated workpiece specifications are pushing the boundaries regarding precision and dynamics of machine tools. In such a high-performance context, machine safety plays a major role and is becoming increasingly challenging due to higher kinetic energies of moving components. This paper examines recent advances in machine tool precision, sustainability, and safety. Six comprehensive case studies are provided to illustrate how these improvements contribute to an increased productivity. Hardware and software solutions for pose-controlled robotic manufacturing and thermoelectrically tempered high-performance spindles will be presented. Modular machine tool frames based on building blocks and an adaptive cooling system with thermoelectric generators for linear direct drives demonstrate their major impact on resource and energy efficiency. Machine safety is addressed through an analysis of potential hazards as well as improved protective measures. Model-based predictions precisely identify critical process parameters that lead to unbalance-induced failure of slim tool extensions, while on the protection side, new statistical models are applied to assess the protective performance of safeguards much more accurately. The cutting-edge technologies for machine tools presented in this paper will help manufacturers to cope with current and future challenges in industrial production.

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Online force prediction by neural networks in single point incremental hole flanging operations

Besong,

Buhl,

Bambach

2024

J Intell Manuf

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Incremental hole flanging by industrial robots requires an accurate estimation of process forces to ensure the safe use of robots and develop tool path strategies that enable defect-free forming. Existing analytical models for force prediction in single-point incremental forming (SPIF) usually predict only the maximum process force, which is insufficient for real-time force prediction necessary for process control. This research investigates the application of neural network models for real-time prediction of the process forces in hole flanging by incremental forming. Experiments and finite element simulations (synthetic data) serve as training data to compare the performance of four time series machine learning (ML) algorithms: a nonlinear autoregressive model with exogenous inputs (NARX), a convolutional neural network (CNN), a long short-term memory (LSTM), and a hybrid CNN-LSTM neural network in predicting real-time forces. The experimental forces predicted by the NARX had a regression ($$\:{R}^{2}$$) of 0.998, while the other ML algorithms achieved $$\:{R}^{2}$$ greater than 0.75, indicating strong correlations between the predicted and measured data. All the ML algorithms trained on synthetic data achieved $$\:{R}^{2}$$ greater than 0.98. Surrogate models built by the integration of synthetic to experiment data led to a decline in the performance of the ML models compared to models composed of only experimental data. The NARX model exhibits superior performance in the investigated scenarios and can be applied to predict online process forces while minimizing experimental effort through the utilization of synthetic data.

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Development of Tool Paths for Multi-axis Single Stage Incremental Hole-flanging

Cited by 6 publications

References 12 publications

Tool path planning for hole-flanging process using single point incremental forming

Tool path planning for hole-flanging process using single point incremental forming

Recent Advances in Precision, Sustainability and Safety of Machine Tools

Online force prediction by neural networks in single point incremental hole flanging operations

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