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      • Faculty of Engineering
      • Department of Mechanical Engineering
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      Development of an iterative learning controller for polymer based micro-stereolithography prototyping systems

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      Author(s)
      Türeyen, Erkan Buğra
      Karpat, Yiğit
      Çakmakcı, Melih
      Date
      2016
      Source Title
      Proceedings of the 2016 American Control Conference, ACC 2016
      Print ISSN
      0743-1619
      Publisher
      IEEE
      Pages
      852 - 857
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      Additive manufacturing has become increasingly popular for a wide range of applications in recent years. Micro-stereolithography (μSLA) is a popular method for obtaining polymer-based parts. Systems using the μSLA approach usually consist of a vertical positioning system, a light source and a container where the component is built gradually as the polymer is cured at the locations where the ultraviolet light is projected. It has been noted that the motion of the positioning system and the intensity of the light source is an important factor to achieve high level dimensional precision. In this paper a three dimensional error based learning scheme is presented to improve the time varying process parameters of the system so that the dimensional accuracy of the product is improved. A mathematical model of the curing process is used for developing the error based learning algorithm. The current process parameters as a function of time and the dimensional error obtained at each layer of the production are used for increasing the quality and precision of the same part in the next iteration. Our initial simulation results show significant improvements can be obtained in a few iterations if the correct learning parameters are used based on the target parts dimensional properties.
      Keywords
      Mathematical model
      Resins
      Curing
      Shape
      Polymers
      Liquids
      Permalink
      http://hdl.handle.net/11693/37488
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/ACC.2016.7525020
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      • Department of Industrial Engineering 702
      • Department of Mechanical Engineering 288
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