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Resistance based iterative learning control of additive manufacturing with wire
University West, Department of Engineering Science, Division of Automation and Computer Engineering. (PTW)ORCID iD: 0000-0002-2824-0271
University West, Department of Engineering Science, Division of Electrical and Automation Engineering. (PTW)
University West, Department of Technology, Mathematics and Computer Science, Division for Electrical Engineering and Land Surveying. (PTW)ORCID iD: 0000-0001-5608-8636
University West, Department of Engineering Science, Division of Manufacturing Processes. Chalmers. (PTW)
2015 (English)In: Mechatronics (Oxford), ISSN 0957-4158, E-ISSN 1873-4006, Vol. 31, 116-123 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents successful feed forward control of additive manufacturing of fully dense metallic components. The study is a refinement of former control solutions of the process, providing more robust and industrially acceptable measurement techniques. The system uses a solid state laser that melts metal wire, which in turn is deposited and solidified to build the desired solid feature on a substrate. The process is inherently subjected to disturbances that might hinder consecutive layers to be deposited appropriately. The control action is a modified wire feed rate depending on the surface of the deposited former layer, in this case measured as a resistance. The resistance of the wire stick-out and the weld pool has shown to give an accurate measure of the process stability, and a solution is proposed on how to measure it. By controlling the wire feed rate based on the resistance measure, the next layer surface can be made more even. A second order iterative learning control algorithm is used for determining the wire feed rate, and the solution is implemented and validated in an industrial setting for building a single bead wall in titanium alloy. A comparison is made between a controlled and an uncontrolled situation when a relevant disturbance is introduced throughout all layers. The controller proves to successfully mitigate these disturbances and maintain stable deposition while the uncontrolled deposition fails.

Place, publisher, year, edition, pages
2015. Vol. 31, 116-123 p.
Keyword [en]
Additive manufacturing, Metal deposition, Automatic control, Resistance, Process measurement, Iterative learning control
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
URN: urn:nbn:se:hv:diva-7429DOI: 10.1016/j.mechatronics.2015.03.008ISI: 000367772000013OAI: oai:DiVA.org:hv-7429DiVA: diva2:793068
Note

Available online 10 April 2015. Ingår i avhandling

Available from: 2015-03-06 Created: 2015-03-06 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Non-intrusive instrumentation and estimation: Applications for control of an additive manufacturing process
Open this publication in new window or tab >>Non-intrusive instrumentation and estimation: Applications for control of an additive manufacturing process
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

For integration of additive manufacturing into industrial production, there is a need for capable yet robust automation solutions. Such solutions are to ensure consistent process outputs, both with regard to deposit geometry and material properties. In this thesis, instrumentation and control solutions have been investigated for the laser metal wire deposition additive manufacturing process. This particular process is promising with regard to e.g. high deposition rates and negligible material waste. However, due to its inherent dynamics, it requires automatic control in order to prove competitive. A large number of process parameters affect the resulting quality of the deposit. Successful control of these parameters is crucial for turning laser metal wire deposition into an industrially tractable process. This requires relevant and reliable process information such as the temperature of the deposit and the positioning of the tool relative to the workpiece. Due to the particular requirements of instrumenting the process, only non-intrusive measurement methods are viable. In this thesis, such measurement solutions are presented that advance automatic control of the laser metal wire deposition. In response to the need for accurate temperature measurements for the process, a new temperature measurement method has been developed. By adopting the novel concept of temporal, rather than spectral, constraints for solving the multispectral pyrometry problem, it opens up for temperature measurements which compensates for e.g. an oxidising deposit. For maintaining a good deposition process in laser metal wire deposition, control of tool position and wire feed rate is required. Based on measurements of resistance through the weld pool, a simple yet well performing control system is presented in this thesis. The control system obtains geometrical input information from resistance measurements made in-situ, and feeds this information to an iterative learning controller. This results in a robust, cheap and practical control solution for laser metal wire deposition, which is suitable for industrial use and that can easily be retrofitted to existing equipment.

Place, publisher, year, edition, pages
Göteborg: Chalmers University of Technology,, 2015. 98 p.
Series
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, ISSN 0346-718X ; 3829
Keyword
Additive Manufacturing, Automation, Emissivity, Emissivity Compensated Spectral Pyrometry, Laser Metal Wire Deposition, Metal Deposition, Pyrometry, Resistance Feedback Control, Thermometry
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-7428 (URN)9789175971483 (ISBN)
Opponent
Supervisors
Available from: 2015-03-06 Created: 2015-03-06 Last updated: 2016-02-08Bibliographically approved

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Hagqvist, PetterChristiansson, Anna-Karin

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Manufacturing, Surface and Joining Technology

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