Elsevier

CIRP Annals

Volume 63, Issue 1, 2014, Pages 377-380
CIRP Annals

Time-optimized hole sequence planning for 5-axis on-the-fly laser drilling

https://doi.org/10.1016/j.cirp.2014.03.126Get rights and content

Abstract

On-the-fly laser drilling requires the use of acceleration continuous trajectories, which are typically planned using time parameterized spline functions. In this operation, the choice of hole drilling sequence, and positioning timings in between the holes, play a critical role in determining the achievable cycle time. This paper presents a new algorithm for sequencing 5-axis on-the-fly laser drilling hole locations and timings. The algorithm considers machine tool and process constraints, as well as the temporal nature of the final commanded spline trajectory. The achievable productivity and motion smoothness improvement are demonstrated in the production of a gas turbine combustion chamber panel.

Introduction

On-the-fly laser drilling offers several advantages over percussion drilling. In percussion drilling, a series of shots are fired to completely open each hole while the part is stationary, followed by repositioning to the next hole. During on-the-fly drilling, the part is in continuous motion while the laser fires only one shot at a time at each hole, and the smooth positioning trajectory repeats itself until all holes are opened. This results in:

  • 1.

    Better material properties and feature quality, due to reduced thermal loading.

  • 2.

    Smoother axis motion, when a spline trajectory is used [1], which reduces vibrations induced onto the laser optics.

  • 3.

    Less downtime for optics realignment, achieved through vibration reduction.

  • 4.

    Increased productivity, as improved motion smoothness can be translated into higher drilling speeds by quickening the process while keeping the vibration levels limited.

Our earlier work had focused on time-optimal trajectory generation for 5-axis on-the-fly laser drilling [2]. The machine configuration, a typical hole pattern with varying orientations, and the hole elongation phenomenon intrinsic to the process are shown in Fig. 1. The hole sequence was determined using the ‘Nearest Neighbor’ (NN) algorithm in part coordinates [3], in which the hole closest to the current one is chosen as the next waypoint, and if the distance exceeds a threshold a new sequence is initiated. In continuing investigation, it was determined that:

  • 1.

    The sequence in which the holes are ordered has a profound impact on the actuator trajectories, and hence the cycle time.

  • 2.

    The acceleration effects in the final trajectory, which are not considered in the NN approach, also need to be taken into account in sequence planning, for improved productivity.

While the hole sequencing task resembles the Traveling Salesman Problem (TSP) known from combinatorial mathematics [4] (where a minimum-cost, e.g. distance, connection needs to be found that passes through all given waypoints only once), there are aspects of on-the-fly laser drilling that make the problem different and even more challenging than TSP, as well as earlier research in hole sequencing for stationary laser drilling [5]:

  • 1.

    Since the final trajectory will be a spline that smoothly connects the sequenced waypoints, the travel durations in between the holes (which strongly influence the spline parameterization) have to be carefully selected. Hence the sequencing algorithm has to solve for both the order of the waypoints and also the timings in between.

  • 2.

    The objective is to minimize the drilling cycle time while adhering to machine tool and process constraints. Therefore, the temporal nature of the final spline trajectory needs to be considered, along with the machine kinematics and limits.

For a part with only M (=10) holes and k (=5) possible timing levels, there can be M! × kM (∼3.54 × 1013) trajectory sequences. In gas turbine combustion chamber panels, the number of holes may vary between hundreds and thousands. Therefore, the need for an efficient and effective sequencing method has been the motivation behind the heuristic algorithm presented henceforth in this paper.

Section snippets

Proposed solution

The proposed algorithm, and data structure used in candidate sequence evaluation, are illustrated in Fig. 2, Fig. 3. Inputs to the algorithm are hole locations Qk (k = 1, …, M) defined in joint (actuator) coordinates q = [x y z a c]T (Fig. 1a). For clear presentation of the algorithm, candidate evaluation is explained first in Section 2.1, followed by the sequencing steps in Section 2.2. The implementation is described in sufficient detail to enable replication. Lengthy equations, however, are

Simulation and experimental results

The proposed sequencing algorithm has been benchmarked to the nearest neighbor (NN) sequencing [3] and optimal trajectory planning [2] technique that was developed in our earlier work. A combustion chamber panel with 567 hole locations is considered (shown in Fig. 1b). The part geometry, as well as actuator and process limits, are the same as those used in the example in [2]. The sequencing algorithm was implemented as compiled Matlab code and executed on an Intel i7 (8-core) computer.

Conclusions

This paper has presented a new waypoint and timing sequencing algorithm for 5-axis on-the-fly laser drilling. The algorithm considers the temporal nature of the final spline trajectory, and is capable of improving both cycle time and motion smoothness while satisfying the specified machine tool and process kinematic constraints. This algorithm is currently being tested further in production trials at P&WC.

Acknowledgments

This research has been supported by P&WC and NSERC through the Industrial Postgraduate Scholarship (IPS2) #430276.

References (6)

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