Skip to main content
SpringerLink
Log in

Product Fingerprints for the Evaluation of Tool/Polymer Replication Quality in Injection Molding at the Micro/Nano Scale

  • Original Article
  • Published:
Nanomanufacturing and Metrology Aims and scope Submit manuscript

Abstract

Replication processes for the manufacturing of micro/nano-structured components are characterized by a certain degree of precision and accuracy. The transcription loss, or replication fidelity, defines the geometrical and dimensional correspondence of micro/nano-structure from metal tool inserts into plastic patterned products. The employment of a vast spectrum of micro/nano-structured geometries calls for methodologies that can be used for the estimation of replication fidelity. This study presents a number of product fingerprints, which propose multiple ways to characterize micro/nano structures in replication technologies. Replication fidelity yielded values above 80% and up to 96% depending on the considered product fingerprints and their definition. Thereafter, a correlation of the product fingerprint with the process parameters was found to optimize the replication process. Measurement uncertainty accompanies the analysis of the product fingerprints, enabling a standardized, robust, and quantitative methodology for process learning, modeling, and optimization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Roeder M, Guenther T, Zimmermann A (2019) Review on fabrication technologies for optical mold inserts. Micromachines 10:1–25

    Article  Google Scholar 

  2. Maghsoudi K, Jafari R, Momen G, Farzaneh M (2017) Micro-nanostructured polymer surfaces using injection molding: a review. Mater Today Commun 13:126–143

    Article  Google Scholar 

  3. Packianather M, Griffiths C, Kadir W (2015) Micro injection moulding process parameter tuning. In: Procedia CIRP, pp 400–405

  4. Baruffi F, Gülçür M, Calaon M et al (2019) Correlating nano-scale surface replication accuracy and cavity temperature in micro-injection moulding using in-line process control and high-speed thermal imaging. J Manuf Process 47:367–381

    Article  Google Scholar 

  5. Calaon M, Hansen HN, Tosello G et al (2013) Microfluidic chip designs process optimization and dimensional quality control. Microsyst Technol 21:561–570

    Article  Google Scholar 

  6. Vera J, Brulez A-C, Contraires E et al (2018) Factors influencing microinjection molding replication quality. J Micromech Microeng 28:015004

    Article  Google Scholar 

  7. Rytka C, Kristiansen PM, Neyer A (2015) Iso- and variothermal injection compression moulding of polymer micro- and nanostructures for optical and medical applications. J Micromech Microeng 25:065008

    Article  Google Scholar 

  8. Nagato K (2014) Injection compression molding of replica molds for nanoimprint lithography. Polymers 6(3):604–612

    Article  Google Scholar 

  9. Sorgato M, Babenko M, Lucchetta G, Whiteside B (2017) Investigation of the influence of vacuum venting on mould surface temperature in micro injection moulding. Int J Adv Manuf Technol 88:547–555

    Article  Google Scholar 

  10. Tosello G (2019) Product/process fingerprint in micro manufacturing. Micromachines 10(5):340

    Article  Google Scholar 

  11. Brinksmeier E, Reese S, Klink A, Langenhorst L, Lübben T, Meinke M, Meyer D, Riemer O, Sölter J (2018) Underlying mechanisms for developing process signatures in manufacturing. Nanomanuf Metrol 1(4):193–208

    Article  Google Scholar 

  12. Sealy MP, Liu ZY, Guo YB, Liu ZQ (2016) Energy based process signature for surface integrity in hard milling. J Mater Process Technol 238:284–289

    Article  Google Scholar 

  13. Parenti P, Masato D, Sorgato M, Lucchetta AM (2017) Surface footprint in molds micromilling and effect on part demoldability in micro injection molding. J Manuf Process 29:160–174

    Article  Google Scholar 

  14. Frerichs F, Meyer H, Strunk R, Kolkwitz B, Epp J (2018) Development of a process signature for manufacturing processes with thermal loads. Metall Mater Trans A Phys Metall Mater Sci 49(8):3419–3429

    Article  Google Scholar 

  15. Eckert S (2019) Multi-cycle process signature of laser-induced thermochemical polishing. J Manuf Mater Process 3(4):90

    Google Scholar 

  16. Fang T, Jafari MA, Bakhadyrov I, Safari A, Danforth S, Langrana N (1998) On-line defect detection in layered manufacturing using process signature. Proc IEEE Int Conf Syst Man Cybern 5:4373–4378

    Google Scholar 

  17. Tosello G, Marinello F, Hansen HN (2012) Characterisation and analysis of microchannels and submicrometre surface roughness of injection moulded microfluidic systems using optical metrology. Plast Rubber Compos Macromol Eng 41(1):29–39

    Article  Google Scholar 

  18. Calaon M, Tosello G, Garnaes J, Hansen HN (2017) Injection and injection-compression moulding replication capability for the production of polymer lab-on-a-chip with nano structures. J Micromech Microeng 27:105001

    Article  Google Scholar 

  19. Christiansen AB, Clausen JS, Mortensen NA, Kristensen A (2014) Injection moulding antireflective nanostructures. Microelectron Eng 121:47–50

    Article  Google Scholar 

  20. Regi F, Doest M, Loaldi D, Li D, Frisvad JR, Tosello G, Zhang Y (2019) Functionality characterization of injection moulded micro-structured surfaces. Precis Eng 60:594–601

    Article  Google Scholar 

  21. Søgaard E, Andersen N K, Taboryski R, Smistrup K (2012) Injection molded superhydrophobic surfaces based on microlithography and black silicon processing. In: Technical proceedings of the 2012 NSTI nanotechnology conference and expo, pp 722–725

  22. Loaldi D, Quagliotti D, Calaon M, Parenti P, Annoni M, Tosello G (2018) Manufacturing signatures of injection molding and injection compression molding for micro-structured polymer Fresnel lens production. Micromachines 9(12):653

    Article  Google Scholar 

  23. Giannekas N, Zhang Y, Tosello G (2018) Investigation on product and process fingerprints for integrated quality assurance in injection molding of microstructure biochips. J Manuf Mater Process 2:79

    Google Scholar 

  24. Zhang Y, Basso A, Christensen SE, Pedersen DB, Staal L, Valler P, Hansen HN (2020) Characterization of near-zero pressure powder injection moulding with sacrificial mould by using fingerprint geometries. Cirp Ann 69(1):185–188

    Article  Google Scholar 

  25. Dundar Arisoy F, Czolkos I, Johansson A, Nielsen T, Watkins JJ (2020) Low-cost, durable master molds for thermal-NIL, UV-NIL, and injection molding. Nanotechnology 31(1):15302

    Article  Google Scholar 

  26. Baruffi F, Calaon M, Tosello G (2018) Micro-injection moulding in-line quality assurance based on product and process fingerprints. Micromachines 2018(9):293

    Article  Google Scholar 

  27. Giannekas N, Kristiansen PM, Zhang Y, Tosello G (2018) Investigation of product and process fingerprints for fast quality assurance in injection molding of micro-structured components. Micromachines 9(12):661

    Article  Google Scholar 

  28. Loaldi D (2020) Integration of micro and nano structures on injection moulded devices. Ph.D. Thesis, Department of Mechanical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark.

  29. Autodesk Moldflow® Insight (2017) Material database, Autodesk Inc, San Rafael, CA, USA

  30. JCGM 100 (2008) Evaluation of measurement data—guide to the expression of uncertainty in measurement (GUM).

  31. ISO 15530-3 (2011) Geometrical product specification (GPS)-coordinate measuring machine (CMM): techniques for determining the uncertainty of measurement. (ISO 15530-3:2011). International Organization for Standardization, Geneva

  32. ISO 251078-70 (2014) Geometrical product specification (GPS)-Surface texture: Areal—Part 70: Material measures. (ISO 25178-70:2014). International Organization for Standardization, Geneva

  33. Yang Y, Pan Y, Ping G (2017) Structural coloration of metallic surfaces with micro/nano-structures induced by elliptical vibration texturing. Appl Surf Sci 402:400–409

    Article  Google Scholar 

  34. Montgomery DC (2012) Design and analysis of experiments, 8th edition, Wiley, ISBN: 978-1-118-09793-9

Download references

Acknowledgements

This research work was undertaken in the context of the research projects PROSURF and MADE DIGITAL. The PROSURF project (“Surface Specifications and Process Chains for Functional Surfaces”, http://www.prosurf-project.eu/) is funded by the HORIZON 2020 program (Project ID: 767589) of the European Commission. MADE DIGITAL (Project ID: 6151-00006B), Manufacturing Academy of Denmark (http://en.made.dk/), Work Package WP3 “Digital manufacturing processes”, is funded by Innovation Fund Denmark (https://innovationsfonden.dk/en).

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Technical University of Denmark (DTU), 2800, Kongens Lyngby, Denmark

    Dario Loaldi, Francesco Regi, Dongya Li, Nikolaos Giannekas, Matteo Calaon, Yang Zhang & Guido Tosello

Authors
  1. Dario Loaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francesco Regi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dongya Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nikolaos Giannekas
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matteo Calaon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Guido Tosello
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guido Tosello.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there are no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Loaldi, D., Regi, F., Li, D. et al. Product Fingerprints for the Evaluation of Tool/Polymer Replication Quality in Injection Molding at the Micro/Nano Scale. Nanomanuf Metrol 4, 278–288 (2021). https://doi.org/10.1007/s41871-021-00105-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41871-021-00105-7

Keywords

Search

Navigation