Skip to main content
Erschienen in: Journal of Intelligent Manufacturing 1/2020

06.08.2018

An application to Stereolithography of a feature recognition algorithm for manufacturability evaluation

verfasst von: Giampaolo Campana, Mattia Mele

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 1/2020

Einloggen

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Additive manufacturing processes are experiencing extraordinary growth in present years. Concerning the production of goods by using this technology, expertise and know-how are today relevant while process simulation needs to be extensively validated before acquiring the necessary reliability, which is already achieved and established for a number of manufacturing processes. The objective of the present work is the development of a new algorithm for feature recognition, which is the first step towards an application of rules for manufacturability to digital models. The proposed approach was specifically conceived for design for additive manufacturing (DfAM). The method starts from a graph-based representation of geometric models that is the base for the definition of new and original geometrical entities. Then, an algorithm-based process has been identified and proposed for their detection. Eventually, these geometrical entities have been used for comparison with rules and constraints of DfAM in order to point out possible critical issues for manufacturability. A self-developed plugin software was implemented for the application of proposed procedure in Computer Aided Design systems. Several applications of a set of DfAM rules are provided and tested to validate the method by means of case studies. As a conclusion, such an application demonstrated the suitability of the approach for detections of features that are relevant to an early investigation into Stereolithography manufacturability. Presented approach could be helpful during early phases of product development for detecting critical manufacturing issues and thus for realising an assistant-tool that can help designers by displaying potential solutions to overcome them. Since the very first steps of product design, this integration of manufacturing knowledge allows for a reduction of a number of potential errors occurring during product fabrication and then for a decrease of required time for product development.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Anhänge
Nur mit Berechtigung zugänglich
Literatur
Zurück zum Zitat Anjum, N. A., Harding, J. A., Young, R. I. M., & Case, K. (2012). Manufacturability verification through feature-based ontological product models. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture,226(6), 1086–1098.CrossRef Anjum, N. A., Harding, J. A., Young, R. I. M., & Case, K. (2012). Manufacturability verification through feature-based ontological product models. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture,226(6), 1086–1098.CrossRef
Zurück zum Zitat Babic, B., Nesic, N., & Miljkovic, Z. (2008). A review of automated feature recognition with rule-based pattern recognition. Computers in Industry,59(4), 321–337.CrossRef Babic, B., Nesic, N., & Miljkovic, Z. (2008). A review of automated feature recognition with rule-based pattern recognition. Computers in Industry,59(4), 321–337.CrossRef
Zurück zum Zitat Brousseau, E., Dimov, S., & Setchi, R. (2008). Knowledge acquisition techniques for feature recognition in CAD models. Journal of Intelligent Manufacturing,19(1), 21–32.CrossRef Brousseau, E., Dimov, S., & Setchi, R. (2008). Knowledge acquisition techniques for feature recognition in CAD models. Journal of Intelligent Manufacturing,19(1), 21–32.CrossRef
Zurück zum Zitat Calignano, F., et al. (2017). Investigation of accuracy and dimensional limits of part produced in aluminum alloy by selective laser melting. The International Journal of Advanced Manufacturing Technology,88, 451–458.CrossRef Calignano, F., et al. (2017). Investigation of accuracy and dimensional limits of part produced in aluminum alloy by selective laser melting. The International Journal of Advanced Manufacturing Technology,88, 451–458.CrossRef
Zurück zum Zitat Chen, Y. M., Miller, R. A., & Sevenler, K. (1995). Knowledge-based manufacturability assessment: An object-oriented approach. Journal of Intelligent Manufacturing,6(5), 321–337.CrossRef Chen, Y. M., Miller, R. A., & Sevenler, K. (1995). Knowledge-based manufacturability assessment: An object-oriented approach. Journal of Intelligent Manufacturing,6(5), 321–337.CrossRef
Zurück zum Zitat Gao, S., & Shah, J. J. (1998). Automatic recognition of interacting machining features based on minimal condition subgraph. Computer-Aided Design,30(9), 727–739.CrossRef Gao, S., & Shah, J. J. (1998). Automatic recognition of interacting machining features based on minimal condition subgraph. Computer-Aided Design,30(9), 727–739.CrossRef
Zurück zum Zitat Gibson, I., et al. (2010). Design rules for additive manufacture. In 21st annual international solid freeform fabrication symposium, Austin, TX. Gibson, I., et al. (2010). Design rules for additive manufacture. In 21st annual international solid freeform fabrication symposium, Austin, TX.
Zurück zum Zitat Hague, R., Mansour, S., & Saleh, N. (2004). Material and design considerations for rapid manufacturing. International Journal of Production Research,42(22), 4691–4708.CrossRef Hague, R., Mansour, S., & Saleh, N. (2004). Material and design considerations for rapid manufacturing. International Journal of Production Research,42(22), 4691–4708.CrossRef
Zurück zum Zitat Han, J. H., Pratt, M., & Regli, W. C. (2000). Manufacturing feature recognition from solid models: A status report. IEEE Transactions on Robotics and Automation,16(6), 782–796.CrossRef Han, J. H., Pratt, M., & Regli, W. C. (2000). Manufacturing feature recognition from solid models: A status report. IEEE Transactions on Robotics and Automation,16(6), 782–796.CrossRef
Zurück zum Zitat Hanrahan, P. (1983). Ray tracing algebraic surfaces. ACM SIGGRAPH Computer Graphics,17(3), 83–90.CrossRef Hanrahan, P. (1983). Ray tracing algebraic surfaces. ACM SIGGRAPH Computer Graphics,17(3), 83–90.CrossRef
Zurück zum Zitat Jakubowski, J., & Peterka, J. (2014). Design for manufacturability in virtual environment using knowledge engineering. Management and Production Engineering Review,5(1), 3–10.CrossRef Jakubowski, J., & Peterka, J. (2014). Design for manufacturability in virtual environment using knowledge engineering. Management and Production Engineering Review,5(1), 3–10.CrossRef
Zurück zum Zitat Jiang, B. C., & Hsu, C. H. (2003). Development of a fuzzy decision model for manufacturability evaluation. Journal of Intelligent Manufacturing,14(2), 169–181.CrossRef Jiang, B. C., & Hsu, C. H. (2003). Development of a fuzzy decision model for manufacturability evaluation. Journal of Intelligent Manufacturing,14(2), 169–181.CrossRef
Zurück zum Zitat Joshi, S., & Chang, T. C. (1988). Graph-based heuristics for recognition of machined features from a 3D solid model. Computer-Aided Design,20(2), 58–66.CrossRef Joshi, S., & Chang, T. C. (1988). Graph-based heuristics for recognition of machined features from a 3D solid model. Computer-Aided Design,20(2), 58–66.CrossRef
Zurück zum Zitat Kranz, J., Herzog, D., & Emmelmann, C. (2015). Design guidelines for laser additive manufacturing of lightweight structures in TiAl6V4. Journal of Laser Applications,27(S14001), 1–16. Kranz, J., Herzog, D., & Emmelmann, C. (2015). Design guidelines for laser additive manufacturing of lightweight structures in TiAl6V4. Journal of Laser Applications,27(S14001), 1–16.
Zurück zum Zitat Liu, X. (2012). Modeling of additive manufacturing process relevant feature in layer based manufacturing process planning. Journal of Shanghai Jiaotong University (Science),17(2), 241–244.CrossRef Liu, X. (2012). Modeling of additive manufacturing process relevant feature in layer based manufacturing process planning. Journal of Shanghai Jiaotong University (Science),17(2), 241–244.CrossRef
Zurück zum Zitat Lockett, H. (2005). A knowledge based manufacturing based manufacturing advisor for CAD. PhD thesis, Cranfield University. Lockett, H. (2005). A knowledge based manufacturing based manufacturing advisor for CAD. PhD thesis, Cranfield University.
Zurück zum Zitat Lockett, H. L., & Guenov, M. D. (2005). Graph-based feature recognition for injection moulding based on a mid-surface approach. Computer-Aided Design,37(2), 251–262.CrossRef Lockett, H. L., & Guenov, M. D. (2005). Graph-based feature recognition for injection moulding based on a mid-surface approach. Computer-Aided Design,37(2), 251–262.CrossRef
Zurück zum Zitat Nannan, G., & Ming, C. L. (2013). Additive manufacturing: Technology, applications and research needs. Frontiers of Mechanical Engineering,8(3), 215–243.CrossRef Nannan, G., & Ming, C. L. (2013). Additive manufacturing: Technology, applications and research needs. Frontiers of Mechanical Engineering,8(3), 215–243.CrossRef
Zurück zum Zitat Nasr, E. S. A., & Kamrani, A. K. (2006). A new methodology for extracting manufacturing features from CAD system. Computers & Industrial Engineering,51(3), 389–415.CrossRef Nasr, E. S. A., & Kamrani, A. K. (2006). A new methodology for extracting manufacturing features from CAD system. Computers & Industrial Engineering,51(3), 389–415.CrossRef
Zurück zum Zitat Onwubolu, G. C. (1999). Manufacturing features recognition using backpropagation neural networks. Journal of Intelligent Manufacturing,10, 289–299.CrossRef Onwubolu, G. C. (1999). Manufacturing features recognition using backpropagation neural networks. Journal of Intelligent Manufacturing,10, 289–299.CrossRef
Zurück zum Zitat Öztürk, N., & Öztürk, F. (2004). Hybrid neural network and genetic algorithm based machining feature recognition. Journal of Intelligent Manufacturing,15(3), 287–298.CrossRef Öztürk, N., & Öztürk, F. (2004). Hybrid neural network and genetic algorithm based machining feature recognition. Journal of Intelligent Manufacturing,15(3), 287–298.CrossRef
Zurück zum Zitat Rahmani, K., & Arezoo, B. (2007). A hybrid hint-based and graph-based framework for recognition of interacting milling features. Computers in Industry,58, 304–312.CrossRef Rahmani, K., & Arezoo, B. (2007). A hybrid hint-based and graph-based framework for recognition of interacting milling features. Computers in Industry,58, 304–312.CrossRef
Zurück zum Zitat Ranjan, R., Samant, R., & Anand, S. (2015). Design for manufacturability in additive manufacturing using a graph based approach. In Proceedings of the ASME 2015 International Manufacturing Science and Engineering Conference MSEC2015, 8–12 June 2015, Charlotte, NC. Ranjan, R., Samant, R., & Anand, S. (2015). Design for manufacturability in additive manufacturing using a graph based approach. In Proceedings of the ASME 2015 International Manufacturing Science and Engineering Conference MSEC2015, 8–12 June 2015, Charlotte, NC.
Zurück zum Zitat Shah, J. J., Anderson, D., Kim, Y. S., & Joshi, S. (2001). A discourse on geometric feature recognition from CAD models. ASME Journal of Computing and Information Science in Engineering,1(1), 440–746. Shah, J. J., Anderson, D., Kim, Y. S., & Joshi, S. (2001). A discourse on geometric feature recognition from CAD models. ASME Journal of Computing and Information Science in Engineering,1(1), 440–746.
Zurück zum Zitat Thomas, D. (2009). The development of design rules for selective laser melting. PhD thesis. University of Wales. Thomas, D. (2009). The development of design rules for selective laser melting. PhD thesis. University of Wales.
Zurück zum Zitat Thompson, M. K., et al. (2016). Design for additive manufacturing: Trends, opportunities, considerations, and constraints. CIRP Annals-Manufacturing Technology,65(2), 737–760.CrossRef Thompson, M. K., et al. (2016). Design for additive manufacturing: Trends, opportunities, considerations, and constraints. CIRP Annals-Manufacturing Technology,65(2), 737–760.CrossRef
Zurück zum Zitat Tonhäuser, C., & Rudolph, S. (2017). Individual coffee maker design using graph-based design languages. In Design computing and cognition ’16 (pp. 513–533). Springer, Cham. Tonhäuser, C., & Rudolph, S. (2017). Individual coffee maker design using graph-based design languages. In Design computing and cognition ’16 (pp. 513–533). Springer, Cham.
Zurück zum Zitat Venkatachalam, A. R., Mellichamp, J. M., & Miller, D. M. (1993). A knowledge-based approach to design for manufacturability. Journal of Intelligent Manufacturing,4(5), 355–366.CrossRef Venkatachalam, A. R., Mellichamp, J. M., & Miller, D. M. (1993). A knowledge-based approach to design for manufacturability. Journal of Intelligent Manufacturing,4(5), 355–366.CrossRef
Zurück zum Zitat Zhang, X., Nassehi, A., & Newman, S. T. (2014). Feature recognition from CNC part programs for milling operations. The International Journal of Advanced Manufacturing Technology,70, 397–412.CrossRef Zhang, X., Nassehi, A., & Newman, S. T. (2014). Feature recognition from CNC part programs for milling operations. The International Journal of Advanced Manufacturing Technology,70, 397–412.CrossRef
Metadaten
Titel
An application to Stereolithography of a feature recognition algorithm for manufacturability evaluation
verfasst von
Giampaolo Campana
Mattia Mele
Publikationsdatum
06.08.2018
Verlag
Springer US
Erschienen in
Journal of Intelligent Manufacturing / Ausgabe 1/2020
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI
https://doi.org/10.1007/s10845-018-1441-8

Weitere Artikel der Ausgabe 1/2020

Journal of Intelligent Manufacturing 1/2020 Zur Ausgabe

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.