[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3131672.3131686acmconferencesArticle/Chapter ViewAbstractPublication PagessensysConference Proceedingsconference-collections
research-article
Public Access

LuBan: Low-Cost and In-Situ Droplet Micro-Sensing for Inkjet 3D Printing Quality Assurance

Published: 06 November 2017 Publication History

Abstract

Inkjet 3D printing is a disruptive manufacturing technology in emerging metal- and bio-printing applications. The nozzle of the printer deposits tiny liquid droplets, which are subsequently solidified on a target location. Due to the elegant concept of micro-droplet deposition, inkjet 3D printing is capable of achieving a sub-millimeter scale manufacturing resolution. However, the droplet deposition process is dynamic and uncertain which imposes a significant challenge on quality assurance of inkjet 3D printing in terms of product reproducibility and process repeatability. To this end, we present Luban as a certification tool to examine the printing quality in the inkjet printing process. Luban is a new low-cost and in-situ droplet micro-sensing system that can precisely detect, analyze and localize a droplet. Specifically, we present a novel tiny object sensing method by exploiting the computational light beam field and its sensitive interference effect. The realization of Luban is associated with two technical thrusts. First, we study integral sensing, i.e., a new scheme towards computational light beam field sensing, to efficiently extract droplet location information. This sensing scheme offers a new in-situ droplet sensing modality, which can promote the information acquisition efficiency and reduce the sensing cost compared to prior approaches. Second, we characterize interference effect of the computational light beam field and develop an efficient integration-domain droplet location estimation algorithm. We design and implement Luban in a real inkjet 3D printing system with commercially off-the-shelf devices, which costs less than a hundred dollars. Experimental results in both simulation and real-world evaluation show that Luban can reach the certification precision of a sub-millimeter scale with a 99% detection accuracy of defect droplets; furthermore, the enabled in-situ certification throughput is as high as over 700 droplets per second. Therefore, the performance of our Luban system can meet the quality assurance requirements (e.g., cost-effective, in-situ, high-accuracy and high-throughput) in general industrial applications.

References

[1]
{n. d.}. https://en.wikipedia.org/wiki/Lu_Ban/. ({n. d.}).
[2]
{n. d.}. Planck constant. https://en.wikipedia.org/wiki/Planck_constant. ({n. d.}).
[3]
Muhammad Taufiq Bin Zainul Abidin, Mohd Khairul Ridhwan Rosli, Sarah Addyani Shamsuddin, Nina Korlina Madzhi, and Mohd Firdaus Abdullah. 2013. Initial quantitative comparison of 940nm and 950nm infrared sensor performance for measuring glucose non-invasively. In Smart Instrumentation, Measurement and Applications (ICSIMA), 2013 IEEE International Conference on. IEEE, 1--6.
[4]
PK Aby, Anumol Jose, Bibin Jose, LD Dinu, Jomon John, and G Sabarinath. 2011. Implementation and optimization of embedded face detection system. In Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), International Conference on. IEEE, 250--253.
[5]
Francesco Aieta, Patrice Genevet, Nanfang Yu, Mikhail A Kats, Zeno Gaburro, and Federico Capasso. 2012. Out-of-plane reflection and refraction of light by anisotropic optical antenna metasurfaces with phase discontinuities. Nano letters 12, 3 (2012), 1702--1706.
[6]
Jerry Ajay, Chen Song, Aditya Singh Rathore, Chi Zhou, and Wenyao Xu. 2017. 3DGates: An Instruction-Level Energy Analysis and Optimization of 3D Printers. In Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems. ACM, 419--433.
[7]
Nathan Binkert, Bradford Beckmann, Gabriel Black, Steven K Reinhardt, Ali Saidi, Arkaprava Basu, Joel Hestness, Derek R Hower, Tushar Krishna, Somayeh Sardashti, et al. 2011. The gem5 simulator. ACM SIGARCH Computer Architecture News 39, 2 (2011), 1--7.
[8]
Gaetano Borriello, Alan Liu, Tony Offer, Christopher Palistrant, and Richard Sharp. 2005. Walrus: wireless acoustic location with room-level resolution using ultrasound. In Proceedings of the 3rd international conference on Mobile systems, applications, and services. ACM, 191--203.
[9]
Susmita Bose, Sahar Vahabzadeh, and Amit Bandyopadhyay. 2013. Bone tissue engineering using 3D printing. Materials Today 16, 12 (2013), 496--504.
[10]
Paul Calvert. 2001. Inkjet printing for materials and devices. Chemistry of materials 13, 10 (2001), 3299--3305.
[11]
Brian Derby. 2010. Inkjet printing of functional and structural materials: fluid property requirements, feature stability, and resolution. Annual Review of Materials Research 40 (2010), 395--414.
[12]
Ralph B Dinwiddie, Lonnie J Love, and John C Rowe. 2013. Real-time process monitoring and temperature mapping of a 3D polymer printing process. In SPIE Defense, Security, and Sensing. International Society for Optics and Photonics, 87050L--87050L.
[13]
Nabil Eid, Yuko Ito, Kentaro Maemura, and Yoshinori Otsuki. 2013. Elevated autophagic sequestration of mitochondria and lipid droplets in steatotic hepatocytes of chronic ethanol-treated rats: an immunohistochemical and electron microscopic study. Journal of molecular histology 44, 3 (2013), 311--326.
[14]
Matthias Faes, Wim Abbeloos, Frederik Vogeler, Hans Valkenaers, Kurt Coppens, Eleonora Ferraris, et al. 2014. Process monitoring of extrusion based 3D printing via laser scanning. In PMI 2014 Conference Proceedings, Vol. 6. 363--367.
[15]
Luigi Maria Galantucci, Fulvio Lavecchia, and Gianluca Percoco. 2009. Experimental study aiming to enhance the surface finish of fused deposition modeled parts. CIRP Annals-Manufacturing Technology 58, 1 (2009), 189--192.
[16]
Paul Green, Jan Kautz, Wojciech Matusik, and Frédo Durand. 2006. View-dependent precomputed light transport using nonlinear gaussian function approximations. In Proceedings of the 2006 symposium on Interactive 3D graphics and games. ACM, 7--14.
[17]
Bethany C Gross, Jayda L Erkal, Sarah Y Lockwood, Chengpeng Chen, and Dana M Spence. 2014. Evaluation of 3D printing and its potential impact on biotechnology and the chemical sciences. Analytical chemistry 86, 7 (2014), 3240--3253.
[18]
Chen Hongyang, Deng Ping, Xu Yongjun, and Li Xiaowei. 2005. A robust location algorithm with biased extended Kalman filtering of TDOA data for wireless sensor networks. In Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005., Vol. 2. IEEE, 883--886.
[19]
Seung Hwan Ko, Jaewon Chung, Nico Hotz, Koo Hyun Nam, and Costas P Grigoropoulos. 2010. Metal nanoparticle direct inkjet printing for low-temperature 3D micro metal structure fabrication. Journal of Micromechanics and Microengineering 20, 12 (2010), 125010.
[20]
David B Kolesky, Ryan L Truby, A Gladman, Travis A Busbee, Kimberly A Homan, and Jennifer A Lewis. 2014. 3D bioprinting of vascularized, heterogeneous cell-laden tissue constructs. Advanced materials 26, 19 (2014), 3124--3130.
[21]
Yves Lacouture and Denis Cousineau. 2008. How to use MATLAB to fit the ex-Gaussian and other probability functions to a distribution of response times. Tutorials in Quantitative Methods for Psychology 4, 1 (2008), 35--45.
[22]
Hsien-Hsueh Lee, Kan-Sen Chou, and Kuo-Cheng Huang. 2005. Inkjet printing of nanosized silver colloids. Nanotechnology 16, 10 (2005), 2436.
[23]
Tianxing Li, Qiang Liu, and Xia Zhou. 2016. Practical Human Sensing in the Light. In Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services. ACM.
[24]
Yiyan Li, Hongzhong Li, and R Jacob Baker. 2015. A low-cost and high-resolution droplet position detector for an intelligent electrowetting on dielectric device. Journal of laboratory automation 20, 6 (2015), 663--669.
[25]
Martin Löffler-Mang and Jürg Joss. 2000. An optical disdrometer for measuring size and velocity of hydrometeors. Journal of Atmospheric and Oceanic Technology 17, 2 (2000), 130--139.
[26]
Georgios Mastorakis and Dimitrios Makris. 2014. Fall detection system using KinectéĹěæłŽ infrared sensor. Journal of Real-Time Image Processing 9, 4 (2014), 635--646.
[27]
Teresa L McLaurin. 2006. The Challenge of Testing the ARM CORTEX-A8/sup TM/Microprocessor Core. In Test Conference, 2006. ITC'06. IEEE International. IEEE, 1--10.
[28]
Eduardo Napadensky. 2010. Inkjet 3D printing. The Chemistry of Inkjet Inks. New Jersey-London-Singapore: World Scientific (2010), 255--67.
[29]
Lionel M Ni, Yunhao Liu, Yiu Cho Lau, and Abhishek P Patil. 2004. LANDMARC: indoor location sensing using active RFID. Wireless networks 10, 6 (2004), 701--710.
[30]
Xize Niu, Mengying Zhang, Suili Peng, Weijia Wen, and Ping Sheng. 2007. Realtime detection, control, and sorting of microfluidic droplets. Biomicrofluidics 1, 4 (2007), 044101.
[31]
Kyung-Wook Paik, Jin-Gul Hyun, Sangyong Lee, and Kyung-Woon Jang. 2006. Epoxy/BaTiO3 (SrTiO3) composite films and pastes for high dielectric constant and low tolerance embedded capacitors in organic substrates. In 2006 1st Electronic Systemintegration Technology Conference, Vol. 2. IEEE, 794--801.
[32]
Jeong Park, Moowhan Shin, and Chin C Lee. 2004. Measurement of temperature profiles on visible light-emitting diodes by use of a nematic liquid crystal and an infrared laser. Optics letters 29, 22 (2004), 2656--2658.
[33]
Kris Pataky, Thomas Braschler, Andrea Negro, Philippe Renaud, Matthias P Lutolf, and Juergen Brugger. 2012. Microdrop Printing of Hydrogel Bioinks into 3D Tissue-Like Geometries. Advanced Materials 24, 3 (2012), 391--396.
[34]
B Subba Rao, B Shalini, B Krishna Teja, and B Kalpana. 2013. Infrared diode laser retinal treatment for chronic headache. Journal of Evolution of Medical and Dental Sciences 2, 50 (2013), 9722--9726.
[35]
Francisco J Rodríguez-Fortuño, Giuseppe Marino, Pavel Ginzburg, Daniel OéŰşÃČęonnor, Alejandro Martínez, Gregory A Wurtz, and Anatoly V Zayats. 2013. Near-field interference for the unidirectional excitation of electromagnetic guided modes. Science 340, 6130 (2013), 328--330.
[36]
Rachel E Saunders, Julie E Gough, and Brian Derby. 2008. Delivery of human fibroblast cells by piezoelectric drop-on-demand inkjet printing. Biomaterials 29, 2 (2008), 193--203.
[37]
Felix Scholkmann, Jens Boss, and Martin Wolf. 2012. An efficient algorithm for automatic peak detection in noisy periodic and quasi-periodic signals. Algorithms 5, 4 (2012), 588--603.
[38]
Daniela Nascimento Silva, Marilia Gerhardt De Oliveira, Eduardo Meurer, Maria Inês Meurer, Jorge Vicente Lopes da Silva, and Ailton Santa-Bárbara. 2008. Dimensional error in selective laser sintering and 3D-printing of models for craniomaxillary anatomy reconstruction. Journal of cranio-maxillofacial surgery 36, 8 (2008), 443--449.
[39]
Justyna Skowyra, Katarzyna Pietrzak, and Mohamed A Alhnan. 2015. Fabrication of extended-release patient-tailored prednisolone tablets via fused deposition modelling (FDM) 3D printing. European Journal of Pharmaceutical Sciences 68 (2015), 11--17.
[40]
Chen Song, Feng Lin, Zhongjie Ba, Kui Ren, Chi Zhou, and Wenyao Xu. 2016. My smartphone knows what you print: Exploring smartphone-based side-channel attacks against 3d printers. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. ACM, 895--907.
[41]
Lijun Song and Jyoti Mazumder. 2011. Feedback control of melt pool temperature during laser cladding process. IEEE Transactions on Control Systems Technology 19, 6 (2011), 1349--1356.
[42]
Imam Tazi, Kuwat Triyana, and Dwi Siswanta. 2016. A novel Arduino Mega 2560 microcontroller-based electronic tongue for dairy product classification. In ADVANCES OF SCIENCE AND TECHNOLOGY FOR SOCIETY: Proceedings of the 1st International Conference on Science and Technology 2015 (ICST-2015), Vol. 1755. AIP Publishing, 170003.
[43]
Łukasz Tymecki and Robert Koncki. 2009. Simplified paired-emitter--detector-diodes-based photometry with improved sensitivity. Analytica chimica acta 639, 1 (2009), 73--77.
[44]
Łukasz Tymecki, Marta Pokrzywnicka, and Robert Koncki. 2008. Paired emitter detector diode (PEDD)-based photometry--an alternative approach. Analyst 133, 11 (2008), 1501--1504.
[45]
Sabine Van Huffel and Philippe Lemmerling. 2013. Total least squares and errors-in-variables modeling: Analysis, algorithms and applications. Springer Science & Business Media.
[46]
Elke M Vinck, Barbara J Cagnie, Maria J Cornelissen, Heidi A Declercq, and Dirk C Cambier. 2003. Increased fibroblast proliferation induced by light emitting diode and low power laser irradiation. Lasers in medical science 18, 2 (2003), 95--99.
[47]
Jie Wang, Alvaro Goyanes, Simon Gaisford, and Abdul W Basit. 2016. Stereolithographic (SLA) 3D printing of oral modified-release dosage forms. International journal of pharmaceutics 503, 1 (2016), 207--212.
[48]
Lucas P Watkins and Haw Yang. 2005. Detection of intensity change points in time-resolved single-molecule measurements. The Journal of Physical Chemistry B 109, 1 (2005), 617--628.

Cited By

View all
  • (2024)High-Fidelity Sensing Modality for Anomaly Detection in Inkjet PrintingJournal of Manufacturing Science and Engineering10.1115/1.4066543147:2Online publication date: 14-Oct-2024
  • (2022)In-situ monitoring of sub-surface and internal defects in additive manufacturing: A reviewMaterials & Design10.1016/j.matdes.2022.111063222(111063)Online publication date: Oct-2022
  • (2021)Reviews on Machine Learning Approaches for Process Optimization in Noncontact Direct Ink WritingACS Applied Materials & Interfaces10.1021/acsami.1c0454413:45(53323-53345)Online publication date: 27-May-2021
  • Show More Cited By

Index Terms

  1. LuBan: Low-Cost and In-Situ Droplet Micro-Sensing for Inkjet 3D Printing Quality Assurance

      Recommendations

      Comments

      Please enable JavaScript to view thecomments powered by Disqus.

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      SenSys '17: Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems
      November 2017
      490 pages
      ISBN:9781450354592
      DOI:10.1145/3131672
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 06 November 2017

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. 3D Printing
      2. Experimentation
      3. Light Beam Sensors

      Qualifiers

      • Research-article
      • Research
      • Refereed limited

      Funding Sources

      Conference

      Acceptance Rates

      Overall Acceptance Rate 174 of 867 submissions, 20%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)239
      • Downloads (Last 6 weeks)22
      Reflects downloads up to 15 Jan 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)High-Fidelity Sensing Modality for Anomaly Detection in Inkjet PrintingJournal of Manufacturing Science and Engineering10.1115/1.4066543147:2Online publication date: 14-Oct-2024
      • (2022)In-situ monitoring of sub-surface and internal defects in additive manufacturing: A reviewMaterials & Design10.1016/j.matdes.2022.111063222(111063)Online publication date: Oct-2022
      • (2021)Reviews on Machine Learning Approaches for Process Optimization in Noncontact Direct Ink WritingACS Applied Materials & Interfaces10.1021/acsami.1c0454413:45(53323-53345)Online publication date: 27-May-2021
      • (2019)SpecEyeProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3326076(103-116)Online publication date: 12-Jun-2019
      • (2019)Online droplet monitoring in inkjet 3D printing using catadioptric stereo systemIISE Transactions10.1080/24725854.2018.153213351:2(153-167)Online publication date: 22-Feb-2019
      • (2019)3D Printed Electronics of Non-contact Ink Writing Techniques: Status and PromiseInternational Journal of Precision Engineering and Manufacturing-Green Technology10.1007/s40684-019-00139-9Online publication date: 17-Jul-2019
      • (2018)PAvesselProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32649322:3(1-24)Online publication date: 18-Sep-2018
      • (2018)My Smartphone Recognizes Genuine QR Codes!Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32142862:2(1-20)Online publication date: 5-Jul-2018

      View Options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Login options

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media