Numerical Techniques for CAM Strategies for Machining of Mould and Die

Ur-Rehman, Raza; Richterich, Claus; Arntz, Kristian; Klocke, Fritz

doi:10.1007/978-1-84996-432-6_60

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Typical high-speed machining toolpaths found in die and mould manufacturing or in aerospace industry consist of series of short segmented toolpaths [29]. When interpolated in HSM mode, the NC interpolator does not undergo a full stop at the end of each CL line.…”

Section: Modelling Of Non-stop (Contouring) Interpolation Behaviourmentioning

confidence: 99%

Accurate prediction of machining feedrate and cycle times considering interpolator dynamics

Ward

Sencer

Jones

et al. 2021

Int J Adv Manuf Technol

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This paper presents an accurate machining feedrate prediction technique by modelling the trajectory generation behaviour of modern CNC machine tools. Typically, CAM systems simulate machines’ motion based on the commanded feedrate and the path geometry. Such approach does not consider the feed planning and interpolation strategy of the machine’s numerical control (NC) system. In this study, trajectory generation behaviour of the NC system is modelled and accurate cycle time prediction for complex machining toolpaths is realised. NC system’s linear interpolation dynamics and commanded axis kinematic profiles are predicted by using finite impulse response (FIR)–based low-pass filters. The corner blending behaviour during non-stop interpolation of linear segments is modelled, and for the first time, the minimum cornering feedrate that satisfies both the tolerance and machining constraints has been calculated analytically for 3-axis toolpaths of any geometry. The proposed method is applied to 4 different case studies including complex machining toolpaths. Experimental validations show actual cycle times can be estimated with > 90% accuracy, greatly outperforming CAM-based predictions. It is expected that the proposed approach will help improve the accuracy of virtual machining models and support businesses’ decision-making when costing machining processes.

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Section: Modelling Of Non-stop (Contouring) Interpolation Behaviourmentioning

confidence: 99%

Accurate prediction of machining feedrate and cycle times considering interpolator dynamics

Ward

Sencer

Jones

et al. 2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…Typical high speed machining toolpaths found in die and mould manufacturing or in aerospace industry consist of series of short segmented toolpaths [27].…”

Section: Modeling Of Non-stop Interpolation Behaviourmentioning

confidence: 99%

“…The maximum TCP contouring or corner blending error ε T CP occurs in the centre of the cornering trajectory and is calculated by evaluating the interpolated axis displacements s at t = T 1 . The interpolated axis displacements are calculated from (27) and the vectors from the corner transition to these positions are represented by l 1 and l 2 .…”

Section: Kinematic Profiles For the 2 First Order Filter Casementioning

confidence: 99%

Accurate Prediction Of Machining Feedrate And Cycle Time Prediction Considering Interpolator Dynamics

Ward,

Sencer,

Jones

et al. 2021

Preprint

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This paper presents an accurate machining feedrate prediction technique by modeling the trajectory generation behaviour of modern CNC machine tools. Typically, CAM systems simulate machines' motion based on the commanded feedrate and the path geometry. Such approach does not consider the feed planning and interpolation strategy of the machine's numerical control (NC) system. In this study, trajectory generation behaviour of the NC system is modelled and accurate cycle time prediction for complex machining toolpaths is realized. NC system's linear interpolation dynamics and commanded axis kinematic profiles are predicted by using Finite Impulse Response (FIR) based low-pass filters. The corner blending behaviour during non-stop interpolation of linear segments is modeled, and for the first time, the minimum cornering feedrate, that satisfies both the tolerance and machining constraints, has been calculated analytically for 3-axis toolpaths of any geometry. The proposed method is applied to 4 different case studies including complex machining tool-paths. Experimental validations show actual cycle times can be estimated with >90% accuracy, greatly outperforming CAM-based predictions. It is expected that the proposed approach will help improve the accuracy of vir-

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Laser Technology: Modelling

Hinduja

2012

Proceedings of the 37th International MATADOR Conference

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An attempt was made to predict the density and microhardness of a component produced by Laser Sintering of EOS DM20 Bronze material for a given set of process parameters. Neural networks were used for process-based-modelling, and results compared with a Taguchi analysis. Samples were produced using a powder-bed type ALM (Additive Layer Manufacturing)-system, with laser power, scan speed and hatch distance as the input parameters, with values equally spaced according to a factorial design of experiments. Optical Microscopy was used to measure cross-sectional porosity of samples; Micro-indentation to measure the corresponding Vickers' hardness.Two different designs of neural networks were usedCounter Propagation (CPNN) and Feed-Forward Back-Propagation (BPNN) and their prediction capabilities were compared. For BPNN network, a Genetic Algorithm (GA) was later applied to enhance the prediction accuracy by altering its topology. Using neural network toolbox in MATLAB, BPNN was trained using 12 training algorithms. The most effective MATLAB training algorithm and the effect of GA-based optimization on the prediction capability of neural networks were both identified..

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Numerical Techniques for CAM Strategies for Machining of Mould and Die

Cited by 4 publications

References 9 publications

Accurate prediction of machining feedrate and cycle times considering interpolator dynamics

Accurate prediction of machining feedrate and cycle times considering interpolator dynamics

Accurate Prediction Of Machining Feedrate And Cycle Time Prediction Considering Interpolator Dynamics

Laser Technology: Modelling

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