Abstract
On-the-fly laser machining is defined as a process that aims to generate pockets/patches on target components that are rotated or moved at a constant velocity. Since it is a nonintegrated process (i.e., linear/rotary stage system moving the part is independent of that of the laser), it can be deployed to/into large industrial installations to perform in situ machining, i.e., without the need of disassembly. This allows a high degree of flexibility in its applications (e.g., balancing) and can result in significant cost savings for the user (e.g., no dis(assembly) cost). This paper introduces the concept of on-the-fly laser machining encompassing models for generating user-defined ablated features as well as error budgeting to understand the sources of errors on this highly dynamic process. Additionally, the paper presents laser pulse placement strategies aimed at increasing the surface finish of the targeted component by reducing the area surface roughness that are possible for on-the-fly laser machining. The overall concept was validated by balancing a rotor system through ablation of different pocket shapes by the use of a Yb:YAG pulsed fiber laser. In this respect, first, two different laser pulse placement strategies (square and hexagonal) were introduced in this research and have been validated on Inconel 718 target material; thus, it was concluded that hexagonal pulse placement reduces surface roughness by up to 17% compared to the traditional square laser pulse placement. The concept of on-the-fly laser machining has been validated by ablating two different features (4 × 60 mm and 12 × 4 mm) on a rotative target part at constant speed (100 rpm and 86 rpm) with the scope of being balanced. The mass removal of the ablated features to enable online balancing has been achieved within < 4 mg of the predicted value. Additionally, the error modeling revealed that most of the uncertainties in the dimensions of the feature/pocket originate from the stability of the rotor speed, which led to the conclusion that for the same mass of material to be removed it is advisable to ablate features (pockets) with longer circumferential dimensions, i.e., stretched and shallower pockets rather than compact and deep.
Highlights
In the last decade the application of advanced materials, such as ceramic composites and superalloys has increased the demand for affordable and capable material removal techniques to machine difficult-to-cut materials [1]
This paper presents a mathematical model that predicts the material removal, process time and the errors of on-the-fly laser machining, of a specified geometrical area targeting as application the balancing of a rotating part at constant velocity
Considering that the width (Dx) is commanded by the laser galvanometer sequentially between ablated tracks, this section presents a way to determine the expected errors in the length (Dy) of the ablated pocket along the cord of the rotor; with the ablation depth known from artificial neural network (ANN), Dx considered of negligible variation, the variance of the on-the-fly ablated volume can be obtained enabling the assessment of the precision of the in-situ laser balancing method
Summary
In the last decade the application of advanced materials, such as ceramic composites and superalloys has increased the demand for affordable and capable (micro) material removal techniques to machine difficult-to-cut materials [1]. 3. MODELLING THE ERRORS FOR ON-THE-FLY LASER MACHINING TARGETING AN APPLICATION FOR IN-SITU BALANCING The model determines the optimum pulse frequency (f), laser power (P) and number of ablated layers (nz) for a defined geometric feature using multi-objective optimisation techniques in order to minimise the process time (t) and the deviation from the desired mass removal (m). Considering that the width (Dx) is commanded by the laser galvanometer sequentially between ablated tracks, this section presents a way to determine the expected errors in the length (Dy) of the ablated pocket along the cord of the rotor; with the ablation depth known from ANN (see section 3.4), Dx considered of negligible variation, the variance of the on-the-fly ablated volume can be obtained enabling the assessment of the precision of the in-situ laser balancing method This allows the development of a general error prediction model, which is not tied to one specific experimental set-up. The associated errors of the feature are evaluated (see Equation (18)) to enable corrective actions to the on-the-fly laser machining process
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