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Record W2599569622

Time-Optimal Trajectory Generation and Way-Point Sequencing for 5-Axis Laser Drilling

2016· dissertation· en· W2599569622 on OpenAlexfundaboutno aff
Ammar Alzaydi

Bibliographic record

VenueUWSpace (University of Waterloo) · 2016
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooPratt and Whitney Canada
KeywordsTrajectoryDrillingPoint (geometry)Computer scienceLaser drillingGeologyMechanical engineeringEngineeringMathematicsPhysicsGeometry
DOInot available

Abstract

fetched live from OpenAlex

Laser drilling provides a highly productive method for producing arrays of holes on planar and freeform shaped components. Industrial applications include fuel injection nozzles, printed circuit boards (PCB’s), inkjet printer heads, pinholes and slits for scientific instrumentation, high-resolution circuitry, sensors, fiber-optic interconnects, medical devices, and gas turbine combustion chamber panels. This thesis deals with time-optimal trajectory planning for two mainstream laser drilling methods: on-the-fly drilling and percussion drilling, which are used in the aerospace industry. The research has been conducted in collaboration with the Canadian aero-engine producer, Pratt & Whitney Canada (P&WC). The algorithms developed have been tested in a target application involving the laser drilling of cooling hole arrays on gas turbine engine combustion chamber panels.
\nOn-the-fly drilling is an operation in which each hole receives one low powered shot at a time while the workpiece is in motion, and the beam focal point is continuously proceeding to the next hole location. The positioning sequence repeats itself until all holes are gradually opened up in small increments. Each hole location has ample time to cool down before the next shot is received. Thus, this process can yield favorable material properties in terms of preserving the desired crystal structure, and also hole quality in terms of dimensional (size) and form (shape) accuracy, due to the reduction of local thermal loading. However, there is no existing trajectory planner, in industry, or in literature, capable of generating time-optimized positioning trajectories for on-the-fly laser drilling. This thesis studies this problem and presents a new algorithm, capable of handling 5 degree-of-freedom (axis) positioning capability. The ability to generate spline-based smooth trajectories is integrated within a Traveling Salesman Problem (TSP) type sequencing algorithm. The sequencing algorithm optimizes both the order of the waypoints (i.e., hole locations) and also the timing levels in between, which affect the temporal (time-dependent) nature of the motions commanded to the laser drilling machine’s actuators. Furthermore, the duration between consecutive holes has to be an integer multiple of the laser pulsing period, considering a machine configuration in which the laser is firing at a constant frequency, and unused pulses are diverted away using a quick shutter. It is shown that the proposed algorithm is capable of generating 17-25% reduction in the beam positioning time spent during a manufacturing cycle, compared to some of the contemporary practices in industry. 17% reduction in the vibrations induced onto the laser optics is also observed, which helps prevent downtime due to the optics hardware gradually losing alignment.
\nThe second type of laser drilling operation for which optimized 5-axis trajectory planning has been developed is percussion drilling. In this process, a series of pulses are sent to each hole while the part is stationary. Once the hole is completely opened up, then positioning to the next hole proceeds. While percussion drilling is less advantageous in terms of local thermal loading and achievable part quality, it is used extensively in industry; due to its simplicity of automation compared to on-the-fly drilling. Thus, a TSP-style trajectory planning algorithm has also been developed for percussion laser drilling. The novelty, in this case, is concurrent planning of 5-axis time-optimal point-to-point movements within the sequencing algorithm, and direct minimization of the total travel time, rather than just distance (in two Cartesian axes); as is the method for which significant portion of TSP solvers and trajectory planners in literature have been developed. Compared to currently applied methods at P&WC, 32-36% reduction in the beam positioning time has been achieved. Also, 39-45% reduction in the peak magnitude of vibration has been realized.
\nLimited benchmarking with state-of-the-art TSP solvers from combinatorial mathematics, considering only 2-axis Euclidean distance as the objective function, indicate that the proposed sequencing algorithm for percussion drilling is sub-optimal by 9-12%. Thus, it can still use further improvement in future research. Nevertheless, the two trajectory planners that have been developed in this thesis for on-the-fly drilling and percussion drilling have experimentally demonstrated very promising improvements in terms of motion time and smoothness. As more advanced Computer Numerical Control (CNC) systems and laser control electronics with deterministic execution and rapid synchronization capability become available, such algorithms are expected to facilitate significant production gains in laser drilling processes used in different industries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.199
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2016
Admission routes2
Has abstractyes

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