Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

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  • Publication
    Quantum computer-aided job scheduling for storage and retrieval systems
    ( 2024)
    Windmann, Stefan
    In this paper, a quantum computer-aided approach to job scheduling for automated storage and retrieval systems is introduced. The approach covers application cases, where various objects need to be transported between storage positions and the order of transport operations can be freely chosen. The objective of job scheduling is to arrange the transport operations in a sequence, where the cumulative costs of the transport operations and empty runs between subsequent transport operations are minimized. The scheduling problem is formulated as an asymmetric quadratic unconstrained binary optimization (QUBO) problem, in which the transport operations are modeled as nodes and empty runs are modeled as edges, with costs assigned to each node and each edge. An Quantum Approximate Optimization Algorithm (QAOA) is used to solve the QUBO. Evaluations of the quantum computer-aided job scheduling approach have been conducted on the IBM Q System One quantum computer in Ehningen. In particular, the running time for the solution of the QUBO has been investigated, as well as the scalability of the approach with respect to the required number of qubits.
  • Publication
  • Publication
    High-power thulium-doped fiber MOPA emitting at 2036 nm
    ( 2024)
    Romano, Clément
    ;
    Panitzek, Dieter
    ;
    Lorenz, Dominik
    ;
    Forster, Patrick
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    An all-fiber laser system is presented with a simple MOPA configuration composed of a seed laser followed by a one-stage high-power amplifier. The seed delivers 10 W of output power at 2036 nm. The high-power amplifier operates with a high slope efficiency of 59 %. An output power of 937 W is demonstrated with a close to diffraction limited beam quality. No nonlinear effects were observed.
  • Publication
    Temperature investigation of low SWaP thulium-doped fiber lasers
    ( 2024)
    Panitzek, Dieter
    ;
    Romano, Clément
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    We investigate the temperature dependence of an in-band core-pumped thulium-doped fiber laser with a low SWaP (size, weight, and power) architecture. The temperature investigation is carried out both experimentally and numerically by a simulation model. We demonstrate experimentally that the investigated setup is resistant for temperatures till 353 K. In addition, we explain the observed behavior by considering the temperature depended spectroscopic parameters of thulium-doped silica fibers. Finally, a numerical investigation is carried out for higher temperatures up to 573 K and higher output powers up to 12 W as well as for different wavelengths and show that the considered fiber lasers works still efficient at these temperature ranges. We show the reliability of the considered thulium-doped fiber laser architecture for applications in harsh environment.
  • Publication
    Investigation of the polymer material perforation time: comparison between two fiber laser wavelengths
    ( 2024)
    Romano, Clément
    ;
    Ritt, Gunnar
    ;
    Henrichsen, Michael
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    This study investigated the perforation time of polyamide 6.6 using fiber lasers at two different wavelengths: 1070 and 1943 nm. The novelty of this research lies in the comparison of perforation times at equivalent laser irradiances on the polymer sample with two different colors of polyamide 6.6: natural and black. The results revealed that, at comparable irradiance levels and beam diameters, the 1943 nm laser source perforated the polyamide 6.6 sample faster than the 1070 nm laser source. The difference in perforation time was found to be significantly higher for natural-colored polyamide 6.6 compared to black-colored polyamide 6.6. These findings suggest that, for material processing of polyamide 6.6, especially in terms of perforation, the use of 2 μm laser sources should be privileged over 1 μm laser sources.
  • Publication
  • Publication
    A survey of the state of the art in sensor-based sorting technology and research
    ( 2024)
    Maier, Georg
    ;
    Gruna, Robin
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    Sensor-based sorting describes a family of systems that enable the removal of individual objects from a material stream. The technology is widely used in various industries such as agriculture, food, mining, and recycling. Examples of sorting tasks include the removal of fungus-infested grains, the enrichment of copper content in copper mining or the sorting of plastic waste according to the type of plastic. Sorting decisions are made based on information acquired by one or more sensors. A particular strength of the technology is the flexibility in sorting decisions, which is achieved by using various sensors and programming the data analysis. However, a comprehensive understanding of the process is necessary for the development of new sorting systems that can address previously unresolved tasks. This survey is aimed at innovative researchers and practitioners who are unfamiliar with sensor-based sorting or have only encountered certain aspects of the overall process. The references provided serve as starting points for further exploration of specific topics.
  • Publication
    Fault detection in automated production systems based on a long short-term memory autoencoder
    ( 2024)
    Windmann, Stefan
    ;
    Westerhold, Tim
    In this paper, a hybrid model of regularized Long Short-Term Memory (LSTM) and autoencoder for fault detection in automated production systems is proposed. The presented LSTM autoencoder is used as a stochastic process model, which captures the normal behavior of a production system and allows to predict the probability distribution of sensor data. Discrepancies between the observed sensor data and the predicted probability density distribution are detected as potential faults. The approach combines the advantages of LSTMs and autoencoders: The correlations between individual sensor signals are exploited by an autoencoder, while the temporal dependencies are captured by LSTM neurons. A key challenge in training such a process model from historical data is to control the information passed through the latent space of the autoencoder. Different regularization methods are investigated for this purpose. Fault detection with the proposed LSTM autoencoder has been evaluated on the use case of an industrial penicillin production, achieving significantly improved results in comparison to the baseline LSTM.
  • Publication
    Reinforcement Learning for Two-Stage Permutation Flow Shop Scheduling - A Real-World Application in Household Appliance Production
    ( 2024)
    Müller, Arthur
    ;
    Grumbach, Felix
    ;
    Kattenstroth, Fiona
    Solving production scheduling problems is a difficult and indispensable task for manufacturers with a push-oriented planning approach. In this study, we tackle a novel production scheduling problem from a household appliance production at the company Miele & Cie. KG, namely a two-stage permutation flow shop scheduling problem (PFSSP) with a finite buffer and sequence-dependent setup efforts. The objective is to minimize idle times and setup efforts in lexicographic order. In extensive and realistic data, the identification of exact solutions is not possible due to the combinatorial complexity. Therefore, we developed a reinforcement learning (RL) approach based on the Proximal Policy Optimization (PPO) algorithm that integrates domain knowledge through reward shaping, action masking, and curriculum learning to solve this PFSSP. Benchmarking of our approach with a state-of-the-art genetic algorithm (GA) showed significant superiority. Our work thus provides a successful example of the applicability of RL in real-world production planning, demonstrating not only its practical utility but also showing the technical and methodological integration of the agent with a discrete event simulation (DES). We also conducted experiments to investigate the impact of individual algorithmic elements and a hyperparameter of the reward function on the overall solution.
  • Publication
    Focal plane analysis of optical power-related metrics for atmospheric turbulence-affected laser beams
    ( 2024)
    Toselli, Italo
    The analysis of budget link and free space optical system performances requires the calculation of several metrics of the atmospheric turbulence-affected collected light. In this work, assuming the collected light is focused into an optical fiber or over a sensor positioned in the focal plane, we use the ABCD ray-matrix representation to calculate the impact of atmospheric turbulence on the power in the fiber or power over the sensor. Calculation of such metrics requires the knowledge of the transmitted average power that enters the receiver aperture (power in the bucket) and the long-term beam spread in the focal plane, from which the Strehl ratio can be obtained.