Towards the development of a smart fused filament fabrication system using multi-sensor data fusion for in-process monitoring

Emerald - Tập 26 Số 7 - Trang 1249-1261 - 2020
Michele Moretti1, Federico Bianchi1, Nicola Senin1
1Department of Engineering, Universita degli Studi di Perugia, Perugia, Italy

Tóm tắt

Purpose This paper aims to illustrate the integration of multiple heterogeneous sensors into a fused filament fabrication (FFF) system and the implementation of multi-sensor data fusion technologies to support the development of a “smart” machine capable of monitoring the manufacturing process and part quality as it is being built. Design/methodology/approach Starting from off-the-shelf FFF components, the paper discusses the issues related to how the machine architecture and the FFF process itself must be redesigned to accommodate heterogeneous sensors and how data from such sensors can be integrated. The usefulness of the approach is discussed through illustration of detectable, example defects. Findings Through aggregation of heterogeneous in-process data, a smart FFF system developed upon the architectural choices discussed in this work has the potential to recognise a number of process-related issues leading to defective parts. Research limitations/implications Although the implementation is specific to a type of FFF hardware and type of processed material, the conclusions are of general validity for material extrusion processes of polymers. Practical implications Effective in-process sensing enables timely detection of process or part quality issues, thus allowing for early process termination or application of corrective actions, leading to significant savings for high value-added parts. Originality/value While most current literature on FFF process monitoring has focused on monitoring selected process variables, in this work a wider perspective is gained by aggregation of heterogeneous sensors, with particular focus on achieving co-localisation in space and time of the sensor data acquired within the same fabrication process. This allows for the detection of issues that no sensor alone could reliably detect.

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Tài liệu tham khảo

2019, In-situ monitoring of polymer flow temperature and pressure in extrusion based additive manufacturing, Additive Manufacturing, 26, 76, 10.1016/j.addma.2019.01.002

2014, Highly reproducible printable graphite strain gauges for flexible devices, Sensors and Actuators A: Physical, 206, 75, 10.1016/j.sna.2013.11.034

Britech 3D (2019), “Aluminum MK8 extruder for CR-10”, available at: https://britech3d.com/product/aluminum-mk8-extruder-for-cr-10-upgraded-for-flexible-filament-afinibot-a31/#.XbgOoOhKiUk (accessed 29 October 2019).

Broadcom (2019), “High resolution 3-channel housed encoder module kits with snap-on cover”, available at: www.broadcom.com/products/motion-control-encoders/incremental-encoders/transmissive-encoders/aedm-5xxx (accessed 29 October 2019).

2008, Vision-based online process control in manufacturing applications, IEEE Transactions on Automation Science and Engineering, 5, 140, 10.1109/TASE.2007.912058

2010, On-line temperature monitoring in selective laser sintering/melting, Physics Procedia, 5, 515, 10.1016/j.phpro.2010.08.079

2011, Online quality control of selective laser melting, 212

2012, Detection of process failures in layerwise laser melting with optical process monitoring, Physics Procedia, 39, 753, 10.1016/j.phpro.2012.10.097

2018, Embedded sensing: integrating sensors in 3-D printed structures, Journal of Sensors and Sensor Systems, 7, 169, 10.5194/jsss-7-169-2018

2013, Real-time process monitoring and temperature mapping of a 3D polymer printing process, Thermosense: Thermal Infrared Applications XXXV, 87050L, 10.1117/12.1518454

2017, Electrically conductive nanocomposites for fused deposition modelling, Synthetic Metals, 226, 7, 10.1016/j.synthmet.2017.01.009

E3D (2017), “V6 all metal hot end”, available at: https://e3d-online.com/v6-all-metal-hotend (accessed 29 October 2019).

2016, Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing, Materials & Design, 95, 431, 10.1016/j.matdes.2016.01.099

Fabbrix (2019), “Fabbrix materials”, available at: www.fabbrix.com/ (accessed 29 October 2019).

2007, Low temperature direct 3D printed bioceramics and biocomposites as drug release matrices, Journal of Controlled Release, 122, 173, 10.1016/j.jconrel.2007.06.022

2017, Closed loop control of slippage during filament transport in molten material extrusion, Additive Manufacturing, 14, 31, 10.1016/j.addma.2016.12.005

2019, Profile monitoring based quality control method for fused deposition modeling process, Journal of Intelligent Manufacturing, 30, 947, 10.1007/s10845-018-1424-9

2012, Rapid 3D printing of anatomically accurate and mechanically heterogeneous aortic valve hydrogel scaffolds, Biofabrication, 4, 10.1088/1758-5082/4/3/035005

2017, In situ real time defect detection of 3D printed parts, Additive Manufacturing, 17, 135, 10.1016/j.addma.2017.08.003

2013, Fiber bragg grating based investigation of residual strains in ABS parts fabricated by fused deposition modeling process, Materials & Design, 50, 44, 10.1016/j.matdes.2013.02.067

2016, In-situ monitoring of strain and temperature distributions during fused deposition modeling process, Materials & Design, 97, 400, 10.1016/j.matdes.2016.02.099

2012, Thermography for monitoring the selective laser melting process, 999

2019, Image analysis-based closed loop quality control for additive manufacturing with fused filament fabrication, Journal of Manufacturing Systems, 51, 75, 10.1016/j.jmsy.2019.04.002

2018, An improved fault diagnosis approach for FDM process with acoustic emission, Journal of Manufacturing Processes, 35, 570, 10.1016/j.jmapro.2018.08.038

Logitech (2013), “Logitech webcam C170”, available at: www.logitech.com/da-dk/product/webcam-c170?crid=34 (accessed 29 October 2019).

2011, Design of an optical system for the in situ process monitoring of selective laser melting (SLM), Physics Procedia, 12, 683, 10.1016/j.phpro.2011.03.085

2017, In-Line 3D Print Failure Detection Using Computer Vision

Marlin (2019), “Marlin firmware”, available at: http://marlinfw.org/ (accessed 29 October 2019).

2019, Dynamic measurements using FDM 3D-printed embedded strain sensors, Sensors, 19, 1, 10.3390/s19122661

Megatronics (2019), “Megatronics 3.0”, available at: https://reprap.org/wiki/Megatronics_3.0 (accessed 29 October 2019).

National Instruments (2020), available at: www.ni.com/en-us.html (accessed 27 May 2020).

2017, Filament temperature dynamics in fused deposition modelling and outlook for control, Procedia Manufacturing, 11, 536, 10.1016/j.promfg.2017.07.147

2015, Online Real-Time quality monitoring in additive manufacturing processes using heterogeneous sensors, Journal of Manufacturing Science and Engineering, 137, 10.1115/1.4029823

Repetier (2018), “Software repetier host”, available at: www.repetier.com/.

RepRap (2016), “Wade geared extruder”, available at: https://reprap.org/wiki/Wade%27s_Geared_Extruder (accessed 29 October 2019).

RepRap (2019), “3Drag 3D printer kit, open store electronics”, available at: https://store.open-electronics.org/3Drag 3D printer KIT (accessed 29 October 2019).

2014, Online monitoring of additive manufacturing processes using ultrasound, 11th European conference on Non-destructive Testing

2016, Adaptation of pharmaceutical excipients to FDM 3D printing for the fabrication of patient-tailored immediate release tablets, International Journal of Pharmaceutics, 513, 659, 10.1016/j.ijpharm.2016.09.050

2017, Evaluating the deposition quality of parts produced by an open-source 3D printer, Rapid Prototyping Journal, 23, 796, 10.1108/RPJ-05-2016-0078

2019, Multi-view online vision detection based on robot fused deposit modeling 3D printing technology, Rapid Prototyping Journal, 25, 343, 10.1108/RPJ-03-2018-0052

SKF, 2019, Deep goove ball bearings

2018, Nozzle condition monitoring in 3D printing, Robotics and Computer-Integrated Manufacturing, 54, 45, 10.1016/j.rcim.2018.05.010

2019, A dynamic model for current-based nozzle condition monitoring in fused deposition modelling, Progress in Additive Manufacturing, 4, 211, 10.1007/s40964-019-00089-3

Ultimaker (2019), “Ultimaker 3”, available at: https://ultimaker.com/3d-printers/ultimaker-3 (accessed 29 October 2019).

Ultimaker, B.V. (2019), “Ultimaker cura, ultimaker.com”, available at: https://ultimaker.com/software/ultimaker-cura (accessed 29 October 2019).

2015, Low-cost closed-loop control of a 3D printer gantry, Rapid Prototyping Journal, 21, 10.1108/RPJ-09-2014-0108

2016, In situ monitoring of FDM machine condition via acoustic emission, International Journal of Advanced Manufacturing Technology. The International Journal of Advanced Manufacturing Technology, 84, 1483, 10.1007/s00170-015-7809-4

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Emerald

Tập 26 Số 7

1249-1261

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