https://puma.ub.uni-stuttgart.de/tag/BayesianOptimizationPUMA RSS feed for /tag/BayesianOptimization2026-04-22T11:50:06+02:00https://puma.ub.uni-stuttgart.de/bibtex/235c7e2feecb203afc29ed828b23bc4ae/ifswifsw2026-04-20T16:13:32+02:00myown Welding Laser BayesianOptimization GaussianProcesses MachineLearning Ablation Optimization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/0"><span itemprop="name">A. Michalowski</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Ilin" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/1"><span itemprop="name">A. Ilin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Kroschel" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/2"><span itemprop="name">A. Kroschel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stephanie Karg" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/3"><span itemprop="name">S. Karg</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Stritt" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/4"><span itemprop="name">P. Stritt</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adina Dais" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/5"><span itemprop="name">A. Dais</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Becker" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/6"><span itemprop="name">S. Becker</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerhard Kunz" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/7"><span itemprop="name">G. Kunz</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Sonntag" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/8"><span itemprop="name">S. Sonntag</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Martin Lustfeld" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/9"><span itemprop="name">M. Lustfeld</span></a></span></span> und 5 andere Autor(en). </span><span class="additional-entrytype-information">(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Mon Apr 20 16:13:32 CEST 2026Advanced laser processing and its optimization with machine learning2023myown Welding Laser BayesianOptimization GaussianProcesses MachineLearning Ablation Optimization The flexibility of new laser sources and process-monitoring enables new possibilities in laser-based production technology, for instance the combination of different laser processes with many adjustable parameters. The fusion of domain knowledge and probabilistic models in the form of hybrid models allows an efficient optimization of these processes with machine learning. This can be a key technology to realize self-learning laser-based universal machines in the future. The article discusses some examples where algorithm-based optimization, partly supported by hybrid models, can already greatly reduce the effort required to find suitable process parameters.https://puma.ub.uni-stuttgart.de/bibtex/235c7e2feecb203afc29ed828b23bc4ae/michaelhaasmichaelhaas2026-04-20T16:13:31+02:00Ablation BayesianOptimization GaussianProcesses Laser MachineLearning Optimization Welding myown <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/0"><span itemprop="name">A. Michalowski</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Ilin" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/1"><span itemprop="name">A. Ilin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Kroschel" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/2"><span itemprop="name">A. Kroschel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stephanie Karg" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/3"><span itemprop="name">S. Karg</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Stritt" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/4"><span itemprop="name">P. Stritt</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adina Dais" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/5"><span itemprop="name">A. Dais</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Becker" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/6"><span itemprop="name">S. Becker</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerhard Kunz" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/7"><span itemprop="name">G. Kunz</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Sonntag" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/8"><span itemprop="name">S. Sonntag</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Martin Lustfeld" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/9"><span itemprop="name">M. Lustfeld</span></a></span></span> und 5 andere Autor(en). </span><span class="additional-entrytype-information">(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Mon Apr 20 16:13:31 CEST 2026Advanced laser processing and its optimization with machine learning2023Ablation BayesianOptimization GaussianProcesses Laser MachineLearning Optimization Welding myown The flexibility of new laser sources and process-monitoring enables new possibilities in laser-based production technology, for instance the combination of different laser processes with many adjustable parameters. The fusion of domain knowledge and probabilistic models in the form of hybrid models allows an efficient optimization of these processes with machine learning. This can be a key technology to realize self-learning laser-based universal machines in the future. The article discusses some examples where algorithm-based optimization, partly supported by hybrid models, can already greatly reduce the effort required to find suitable process parameters.https://puma.ub.uni-stuttgart.de/bibtex/28c14d621fac5e000d2c65e9a33485af6/michaelhaasmichaelhaas2026-04-20T16:09:36+02:00Ablation BayesianOptimization GaussianProcesses Laser MachineLearning Optimization Welding myown <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/0"><span itemprop="name">A. Michalowski</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Ilin" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/1"><span itemprop="name">A. Ilin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Kroschel" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/2"><span itemprop="name">A. Kroschel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stephanie Karg" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/3"><span itemprop="name">S. Karg</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Stritt" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/4"><span itemprop="name">P. Stritt</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adina Dais" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/5"><span itemprop="name">A. Dais</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Becker" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/6"><span itemprop="name">S. Becker</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerhard Kunz" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/7"><span itemprop="name">G. Kunz</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Sonntag" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/8"><span itemprop="name">S. Sonntag</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Martin Lustfeld" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/9"><span itemprop="name">M. Lustfeld</span></a></span></span> und 5 andere Autor(en). </span><span class="additional-entrytype-information"><em> Laser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII, </em><em><span itemprop="publisher">SPIE</span>, </em>(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Mon Apr 20 16:09:36 CEST 2026Advanced laser processing and its optimization with machine learningLaser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII2023Ablation BayesianOptimization GaussianProcesses Laser MachineLearning Optimization Welding myown The flexibility of new laser sources and process-monitoring enables new possibilities in laser-based production technology, for instance the combination of different laser processes with many adjustable parameters. The fusion of domain knowledge and probabilistic models in the form of hybrid models allows an efficient optimization of these processes with machine learning. This can be a key technology to realize self-learning laser-based universal machines in the future. The article discusses some examples where algorithm-based optimization, partly supported by hybrid models, can already greatly reduce the effort required to find suitable process parameters.https://puma.ub.uni-stuttgart.de/bibtex/28c14d621fac5e000d2c65e9a33485af6/ifswifsw2026-04-20T16:09:36+02:00myown Welding Laser BayesianOptimization GaussianProcesses MachineLearning Ablation Optimization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/0"><span itemprop="name">A. Michalowski</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Ilin" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/1"><span itemprop="name">A. Ilin</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Kroschel" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/2"><span itemprop="name">A. Kroschel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stephanie Karg" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/3"><span itemprop="name">S. Karg</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Stritt" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/4"><span itemprop="name">P. Stritt</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adina Dais" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/5"><span itemprop="name">A. Dais</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Becker" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/6"><span itemprop="name">S. Becker</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerhard Kunz" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/7"><span itemprop="name">G. Kunz</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Sonntag" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/8"><span itemprop="name">S. Sonntag</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Martin Lustfeld" itemprop="url" href="/person/14ea9784e293ac172887a2bd6105b0af2/author/9"><span itemprop="name">M. Lustfeld</span></a></span></span> und 5 andere Autor(en). </span><span class="additional-entrytype-information"><em> Laser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII, </em><em><span itemprop="publisher">SPIE</span>, </em>(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Mon Apr 20 16:09:36 CEST 2026Advanced laser processing and its optimization with machine learningLaser Applications in Microelectronic and Optoelectronic Manufacturing (LAMOM) XXVIII2023myown Welding Laser BayesianOptimization GaussianProcesses MachineLearning Ablation Optimization The flexibility of new laser sources and process-monitoring enables new possibilities in laser-based production technology, for instance the combination of different laser processes with many adjustable parameters. The fusion of domain knowledge and probabilistic models in the form of hybrid models allows an efficient optimization of these processes with machine learning. This can be a key technology to realize self-learning laser-based universal machines in the future. The article discusses some examples where algorithm-based optimization, partly supported by hybrid models, can already greatly reduce the effort required to find suitable process parameters.https://puma.ub.uni-stuttgart.de/bibtex/21842f79aca312e73b8c33b4e193fd6ca/ifswifsw2026-04-20T10:38:19+02:00myown Welding peer Laser DesignOfExperiments BayesianOptimization Ablation Cutting <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/0"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/1"><span itemprop="name">V. Onuseit</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Matthias Buser" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/2"><span itemprop="name">M. Buser</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/3"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Nico Bär" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/4"><span itemprop="name">N. Bär</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/5"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Light: Advanced Manufacturing</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">5 </span></span>(<span itemprop="issueNumber">3</span>): <span itemprop="pagination">32</span></em> </span>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Apr 20 10:38:19 CEST 2026Light: Advanced Manufacturing332Laser material processing optimization using bayesian optimization: a generic tool52024myown Welding peer Laser DesignOfExperiments BayesianOptimization Ablation Cutting https://puma.ub.uni-stuttgart.de/bibtex/21842f79aca312e73b8c33b4e193fd6ca/michaelhaasmichaelhaas2026-04-20T10:38:18+02:00Ablation BayesianOptimization Cutting DesignOfExperiments Laser Welding myown peer <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/0"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/1"><span itemprop="name">V. Onuseit</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Matthias Buser" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/2"><span itemprop="name">M. Buser</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/3"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Nico Bär" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/4"><span itemprop="name">N. Bär</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/1dd9a2ff6d0d49434e0466f2dd16ab815/author/5"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Light: Advanced Manufacturing</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">5 </span></span>(<span itemprop="issueNumber">3</span>): <span itemprop="pagination">32</span></em> </span>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Apr 20 10:38:18 CEST 2026Light: Advanced Manufacturing332Laser material processing optimization using bayesian optimization: a generic tool52024Ablation BayesianOptimization Cutting DesignOfExperiments Laser Welding myown peer https://puma.ub.uni-stuttgart.de/bibtex/212b1bf1a3f2309bd0a79a04adff1e1ce/michaelhaasmichaelhaas2026-04-10T15:59:18+02:00Aluminum BayesianOptimization Optimization Welding X-ray myown peer <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/0"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert Steinhoff" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/1"><span itemprop="name">R. Steinhoff</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John Powell" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/2"><span itemprop="name">J. Powell</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Zaiß" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/3"><span itemprop="name">F. Zaiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Wahl" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/4"><span itemprop="name">J. Wahl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Hagenlocher" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/5"><span itemprop="name">C. Hagenlocher</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/6"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Journal of Intelligent Manufacturing</span>, </em> </span>(<em><span>27.02.2026<meta content="27.02.2026" itemprop="datePublished"/></span></em>)</span>Fri Apr 10 15:59:18 CEST 2026Journal of Intelligent ManufacturingfebEfficient parameter selection in laser welding via Bayesian optimization2026Aluminum BayesianOptimization Optimization Welding X-ray myown peer 27Identifying suitable process parameters is essential for developing effective laser welding processes. Traditionally, this involves extensive experimentation and relies heavily on expert knowledge. Bayesian optimization can be used to minimize both the experimental effort and the need for expert information. This study demonstrates the merit of Bayesian optimization for laser welding and explains the methodology for implementing the optimization technique. A strategy for selecting evaluation methods and the design of a suitable cost function to meet specific quality criteria is proposed. For the experimental demonstration, butt joint laser welding of AA1050 aluminum alloy was performed with options to adapt the laser power, welding speed, focus position, and the intensity distribution of the laser beam by changing the power distribution in a multi-core fiber. The success of the optimization was validated by finding several parameter sets producing welds that met the defined quality levels. Furthermore, the properties of the underlying surrogate model of the Bayesian optimizer generated further information that helped to improve the welding process.https://puma.ub.uni-stuttgart.de/bibtex/212b1bf1a3f2309bd0a79a04adff1e1ce/ifswifsw2026-04-10T15:59:18+02:00myown Welding peer Aluminum BayesianOptimization X-ray Optimization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/0"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert Steinhoff" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/1"><span itemprop="name">R. Steinhoff</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John Powell" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/2"><span itemprop="name">J. Powell</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Zaiß" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/3"><span itemprop="name">F. Zaiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Wahl" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/4"><span itemprop="name">J. Wahl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Hagenlocher" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/5"><span itemprop="name">C. Hagenlocher</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/18306d0818308eb273c5e8b7e216c83de/author/6"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Journal of Intelligent Manufacturing</span>, </em> </span>(<em><span>27.02.2026<meta content="27.02.2026" itemprop="datePublished"/></span></em>)</span>Fri Apr 10 15:59:18 CEST 2026Journal of Intelligent ManufacturingfebEfficient parameter selection in laser welding via Bayesian optimization2026myown Welding peer Aluminum BayesianOptimization X-ray Optimization 27Identifying suitable process parameters is essential for developing effective laser welding processes. Traditionally, this involves extensive experimentation and relies heavily on expert knowledge. Bayesian optimization can be used to minimize both the experimental effort and the need for expert information. This study demonstrates the merit of Bayesian optimization for laser welding and explains the methodology for implementing the optimization technique. A strategy for selecting evaluation methods and the design of a suitable cost function to meet specific quality criteria is proposed. For the experimental demonstration, butt joint laser welding of AA1050 aluminum alloy was performed with options to adapt the laser power, welding speed, focus position, and the intensity distribution of the laser beam by changing the power distribution in a multi-core fiber. The success of the optimization was validated by finding several parameter sets producing welds that met the defined quality levels. Furthermore, the properties of the underlying surrogate model of the Bayesian optimizer generated further information that helped to improve the welding process.https://puma.ub.uni-stuttgart.de/bibtex/226d5e75a3cc49491fcd3c3f6c9735c0b/kglumannkglumann2025-12-05T10:30:29+01:00BayesianOptimization laserwelding myown <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kim Glumann" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/0"><span itemprop="name">K. Glumann</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Sawannia" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/1"><span itemprop="name">M. Sawannia</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/2"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/3"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/4"><span itemprop="name">V. Onuseit</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/5"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>Fri Dec 05 10:30:29 CET 2025Enhancing the laser weld seam quality with dynamic beam shaping and Bayesian optimization2025BayesianOptimization laserwelding myown https://puma.ub.uni-stuttgart.de/bibtex/226d5e75a3cc49491fcd3c3f6c9735c0b/ifswifsw2025-12-05T10:30:29+01:00myown BayesianOptimization laserwelding <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kim&#034; &#034;Glumann" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/0"><span itemprop="name">K. &#034;Glumann</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael&#034; &#034;Sawannia" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/1"><span itemprop="name">M. &#034;Sawannia</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael&#034; &#034;Haas" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/2"><span itemprop="name">M. &#034;Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias&#034; &#034;Menold" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/3"><span itemprop="name">T. &#034;Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher&#034; &#034;Onuseit" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/4"><span itemprop="name">V. &#034;Onuseit</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas&#034; &#034;Michalowski" itemprop="url" href="/person/1a6b7463bf7c6f0dbdea48ef16a4fb413/author/5"><span itemprop="name">A. &#034;Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>Fri Dec 05 10:30:29 CET 2025Enhancing the laser weld seam quality with dynamic beam shaping and Bayesian optimization2025myown BayesianOptimization laserwelding https://puma.ub.uni-stuttgart.de/bibtex/28b469e9d2f79906f9c36561d4cf8939b/lukasbauerlukasbauer2025-07-14T21:00:08+02:00BayesianOptimization myown <meta content="thesis" itemprop="educationalUse"/><span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lukas Bauer" itemprop="url" href="/person/17ea73edaada131b4c4c8c28cf1a56391/author/0"><span itemprop="name">L. Bauer</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jul 14 21:00:08 CEST 2025Bayesian optimization for a skeletal muscle using the simulation framework OpenDiHu2024BayesianOptimization myown https://puma.ub.uni-stuttgart.de/bibtex/2110f05b8e3374e82ad0346a08770f293/lukasschnellerlukasschneller2025-06-30T12:57:18+02:00BayesianOptimization Drilling myown peer <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Manuel Klaiber" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/0"><span itemprop="name">M. Klaiber</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mathias Hug" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/1"><span itemprop="name">M. Hug</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lukas Schneller" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/2"><span itemprop="name">L. Schneller</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ömer Can" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/3"><span itemprop="name">Ö. Can</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Jahn" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/4"><span itemprop="name">A. Jahn</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Axel Fehrenbacher" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/5"><span itemprop="name">A. Fehrenbacher</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Reimann" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/6"><span itemprop="name">P. Reimann</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/7"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"></span><em>Seite <span itemprop="pagination">1–12</span>. </em><em><span itemprop="publisher">KIT Scientific Publishing</span>, </em>(<em><span>September 2024<meta content="September 2024" itemprop="datePublished"/></span></em>)</span>Mon Jun 30 12:57:18 CEST 2025Forum Bildverarbeitung 2024 = Image Pocessing Forum 2024sep1–12Automated image-based parameter optimization for single-pulse laser drilling2024BayesianOptimization Drilling myown peer https://puma.ub.uni-stuttgart.de/bibtex/2110f05b8e3374e82ad0346a08770f293/ifswifsw2025-06-30T12:57:18+02:00Drilling myown peer BayesianOptimization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Manuel Klaiber" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/0"><span itemprop="name">M. Klaiber</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mathias Hug" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/1"><span itemprop="name">M. Hug</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lukas Schneller" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/2"><span itemprop="name">L. Schneller</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ömer Can" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/3"><span itemprop="name">Ö. Can</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Jahn" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/4"><span itemprop="name">A. Jahn</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Axel Fehrenbacher" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/5"><span itemprop="name">A. Fehrenbacher</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Reimann" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/6"><span itemprop="name">P. Reimann</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/1386e80c8dd91a5a79814728d17c38797/author/7"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"></span><em>Seite <span itemprop="pagination">1–12</span>. </em><em><span itemprop="publisher">KIT Scientific Publishing</span>, </em>(<em><span>September 2024<meta content="September 2024" itemprop="datePublished"/></span></em>)</span>Mon Jun 30 12:57:18 CEST 2025Forum Bildverarbeitung 2024 = Image Pocessing Forum 2024sep1–12Automated image-based parameter optimization for single-pulse laser drilling2024Drilling myown peer BayesianOptimization https://puma.ub.uni-stuttgart.de/bibtex/2155f6c41af538ddfb9505e482c5b03b4/michaelhaasmichaelhaas2024-09-23T09:27:54+02:00BayesianOptimization Laser Welding X-ray myown <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/0"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/1"><span itemprop="name">V. Onuseit</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John Powell" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/2"><span itemprop="name">J. Powell</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Zaiß" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/3"><span itemprop="name">F. Zaiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Wahl" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/4"><span itemprop="name">J. Wahl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/5"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Hagenlocher" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/6"><span itemprop="name">C. Hagenlocher</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/7"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Sep 23 09:27:54 CEST 2024Improving the weld seam quality in laser welding processes by means of Bayesian optimization2024BayesianOptimization Laser Welding X-ray myown The determination of appropriate process parameters is crucial for the development of laser welding processes. This usually requires extensive and time-consuming experimentation combined with expert knowledge. To reduce the number of experiments required to determine appropriate process parameters, Bayesian optimization was used in this work. Bead on plate laser welding of AA5754 samples was performed while optimizing the laser power, the welding speed, the focus position and the power distribution in the core-ring fiber laser system with the objective of achieving welds with a specific weld depth and low number of defects at high welding speeds. The welds were evaluated using X-ray imaging and height measurements. A cost function was developed to quantify the overall weld quality based on the weld properties. It is demonstrated that the Bayesian optimizer can determine appropriate process parameters for the given objective, based on a cost function, within a comparatively small number of 29 experiments.https://puma.ub.uni-stuttgart.de/bibtex/2155f6c41af538ddfb9505e482c5b03b4/ifswifsw2024-09-23T09:27:54+02:00myown Welding Laser BayesianOptimization X-ray <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/0"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/1"><span itemprop="name">V. Onuseit</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John Powell" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/2"><span itemprop="name">J. Powell</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Zaiß" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/3"><span itemprop="name">F. Zaiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Wahl" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/4"><span itemprop="name">J. Wahl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/5"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Hagenlocher" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/6"><span itemprop="name">C. Hagenlocher</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/7"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Sep 23 09:27:54 CEST 2024Improving the weld seam quality in laser welding processes by means of Bayesian optimization2024myown Welding Laser BayesianOptimization X-ray The determination of appropriate process parameters is crucial for the development of laser welding processes. This usually requires extensive and time-consuming experimentation combined with expert knowledge. To reduce the number of experiments required to determine appropriate process parameters, Bayesian optimization was used in this work. Bead on plate laser welding of AA5754 samples was performed while optimizing the laser power, the welding speed, the focus position and the power distribution in the core-ring fiber laser system with the objective of achieving welds with a specific weld depth and low number of defects at high welding speeds. The welds were evaluated using X-ray imaging and height measurements. A cost function was developed to quantify the overall weld quality based on the weld properties. It is demonstrated that the Bayesian optimizer can determine appropriate process parameters for the given objective, based on a cost function, within a comparatively small number of 29 experiments.https://puma.ub.uni-stuttgart.de/bibtex/21f3011175c22622eb1ed4f9624cd89e5/michaelhaasmichaelhaas2024-09-23T09:21:21+02:00BayesianOptimization Laser Welding X-ray myown peer <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/0"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/1"><span itemprop="name">V. Onuseit</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John Powell" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/2"><span itemprop="name">J. Powell</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Zaiß" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/3"><span itemprop="name">F. Zaiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Wahl" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/4"><span itemprop="name">J. Wahl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/5"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Hagenlocher" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/6"><span itemprop="name">C. Hagenlocher</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/7"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"></span><em> 124, </em><em>Seite <span itemprop="pagination">772–775</span>. </em><em><span itemprop="publisher">Elsevier BV</span>, </em>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Sep 23 09:21:21 CEST 2024Procedia CIRP772–775Improving the weld seam quality in laser welding processes by means of Bayesian optimization1242024BayesianOptimization Laser Welding X-ray myown peer The determination of appropriate process parameters is crucial for the development of laser welding processes. This usually requires extensive and time-consuming experimentation combined with expert knowledge. To reduce the number of experiments required to determine appropriate process parameters, Bayesian optimization was used in this work. Bead on plate laser welding of AA5754 samples was performed while optimizing the laser power, the welding speed, the focus position and the power distribution in the core-ring fiber laser system with the objective of achieving welds with a specific weld depth and low number of defects at high welding speeds. The welds were evaluated using X-ray imaging and height measurements. A cost function was developed to quantify the overall weld quality based on the weld properties. It is demonstrated that the Bayesian optimizer can determine appropriate process parameters for the given objective, based on a cost function, within a comparatively small number of 29 experiments.https://puma.ub.uni-stuttgart.de/bibtex/21f3011175c22622eb1ed4f9624cd89e5/ifswifsw2024-09-23T09:21:21+02:00myown Welding peer Laser BayesianOptimization X-ray <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Haas" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/0"><span itemprop="name">M. Haas</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volkher Onuseit" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/1"><span itemprop="name">V. Onuseit</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John Powell" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/2"><span itemprop="name">J. Powell</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Felix Zaiß" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/3"><span itemprop="name">F. Zaiß</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Wahl" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/4"><span itemprop="name">J. Wahl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Menold" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/5"><span itemprop="name">T. Menold</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christian Hagenlocher" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/6"><span itemprop="name">C. Hagenlocher</span></a></span>, </span> und <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Michalowski" itemprop="url" href="/person/122e6c5992b446d3c9991215364a70849/author/7"><span itemprop="name">A. Michalowski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"></span><em> 124, </em><em>Seite <span itemprop="pagination">772–775</span>. </em><em><span itemprop="publisher">Elsevier BV</span>, </em>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Sep 23 09:21:21 CEST 2024Procedia CIRP772–775Improving the weld seam quality in laser welding processes by means of Bayesian optimization1242024myown Welding peer Laser BayesianOptimization X-ray The determination of appropriate process parameters is crucial for the development of laser welding processes. This usually requires extensive and time-consuming experimentation combined with expert knowledge. To reduce the number of experiments required to determine appropriate process parameters, Bayesian optimization was used in this work. Bead on plate laser welding of AA5754 samples was performed while optimizing the laser power, the welding speed, the focus position and the power distribution in the core-ring fiber laser system with the objective of achieving welds with a specific weld depth and low number of defects at high welding speeds. The welds were evaluated using X-ray imaging and height measurements. A cost function was developed to quantify the overall weld quality based on the weld properties. It is demonstrated that the Bayesian optimizer can determine appropriate process parameters for the given objective, based on a cost function, within a comparatively small number of 29 experiments.