{'fraction_non_alphanumeric': 0.02058590657165479, 'fraction_numerical': 0.003167062549485352, 'mean_word_length': 5.652631578947369, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A model-based approach to enhance performance in high-end laser-positioning systems

In this paper the challenge of improving throughput in additive manufacturing and other laser-based manufacturing processes is addressed. It is the main obstacle, for industries using these processes, to market position themselves with regards to conventional material processing technologies. A key component affecting throughput, besides the material alteration process itself, is the laser scanner controlling the laser spot position.In this paper, a new model-based methodology to improve the performance of such laser scanners is proposed. This methodology consists of two main steps: (1) identification of a high-fidelity model of the laser scanner quantifying its dynamics (2) design of a model-based feedforward controller improving performance beyond conventional control. This methodology is implemented and validated using an industrial setup equipped with an open controller for additive manufacturing machines, an industrial laser scanner and a camera based monitoring system that allows an accurate evaluation of the scanner positioning. The validation on the setup showed improvement in performance up to 49% compared to conventional control of the laser scanner.