2018 IEEE Conference on Control Technology and Applications (CCTA) · 2018 · 14 citations · 13 references
EngineeringManufacturing EngineeringAdditive ManufacturingMechanical Behavior Of MaterialsProcess Control3D PrintingDesign For Additive ManufacturingControl FeedbackMechanical Properties Of Printed PartsOptimal Control Of Stochastic SystemsPrintabilityStiffnessStochastic Optimal Control
3D printing is rapidly becoming a commodity. However, the quality of the printed parts is not always even nor predictable. Feedback control is demonstrated during the printing of a plastic object using additive manufacturing as a means to improve macroscopic mechanical properties of the object. The printed object is a leaf spring made of several parts of different infill density values, which are the control variables in this problem. In order to achieve a desired objective stiffness, measurements are taken after each part is completed and the infill density is adjusted accordingly in a closed-loop framework. With feedback control, the absolute error of the measured part stiffness is reduced from 11.63% to 1.34% relative to the specified stiffness. This experiment is therefore a proof of concept to show the relevance of using feedback control in additive manufacturing. By considering the printing process and the measurements as stochastic processes, we show how stochastic optimal control and Kalman filtering can be used to improve the quality of objects manufactured with rudimentary printers.
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Jayanthi Parthasarathy, Binil Starly, Shivakumar Raman · Journal of Manufacturing Processes · 2011 · 383 citations