Advertisement

Cloud-Based Materials and Product Realization—Fostering ICME Via Industry 4.0

  • Anand Balu NellippallilEmail author
  • Zhenjun Ming
  • Janet K. Allen
  • Farrokh Mistree
Thematic Section: 5th World Congress on Integrated Computational Materials Engineering
  • 76 Downloads
Part of the following topical collections:
  1. 5th World Congress on Integrated Computational Materials Engineering

Abstract

Facilitating integrated computational materials engineering (ICME) in the digitized world necessitates facilitating a network of participants (material scientists, systems designers, software developers, service customers) to share material/product/manufacturing process/market data, information, knowledge, and resources instantly and collaborate so as to facilitate a cost-effective co-creation of value supporting open innovation. Industry 4.0, a transformative industrial revolution with its new product development paradigms like cloud-based design and cloud-based manufacturing, supports this need. In this paper, we present the architecture and functionalities of a cloud-based computational platform to facilitate mass collaboration and open innovation thereby supporting integrated material and product realization to institutionalize ICME in industry. We illustrate the efficacy of the proposed cloud-based platform using a hot rolling example problem to produce a steel rod. Using this example, we illustrate the utility of the cloud-based platform in seamless, yet controllable, information, knowledge, and resource sharing thereby supporting the integrated design of materials, products, and manufacturing processes.

Keywords

Cloud-based design for ICME Collaboration and sharing in design 

Notes

Acknowledgments

Anand Balu Nellippallil thanks the Systems Realization Laboratory, University of Oklahoma, for supporting him.

Funding Information

This work was financially supported by Tata Consultancy Services Research, Pune (Grant No. 105-373200) and by the John and Mary Moore Chairs and L.A. Comp Chair at the University of Oklahoma.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    National Research Council; Division on Engineering and Physical Sciences; National Materials Advisory Board; Committee on Integrated Computational Materials Engineering (2008) Integrated computational materials engineering: a transformational discipline for improved competitiveness and national security. National Academies PressGoogle Scholar
  2. 2.
    Horstemeyer MF (2012) Integrated computational materials engineering (ICME) for metals: using multiscale modeling to invigorate engineering design with science. John Wiley & SonsGoogle Scholar
  3. 3.
    Thames L, Schaefer D (2017) Cybersecurity for Industry 4.0. SpringerGoogle Scholar
  4. 4.
    Beitz W, Pahl G, Grote K (1996) Engineering design: a systematic approach. MRS Bull:71Google Scholar
  5. 5.
    Suh NP (1990) The principles of design. Oxford University Press on Demand, OxfordGoogle Scholar
  6. 6.
    Franke N, Von Hippel E, Schreier M (2006) Finding commercially attractive user innovations: a test of lead-user theory. J Prod Innov Manag 23(4):301–315Google Scholar
  7. 7.
    Wu D, Thames JL, Rosen DW, Schaefer D Towards a cloud-based design and manufacturing paradigm: looking backward, looking forward, Proc. ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers, pp 315–328Google Scholar
  8. 8.
    McDowell DL (2018) Microstructure-sensitive computational structure-property relations in materials design. Computational Materials System Design. Springer, pp 1–25Google Scholar
  9. 9.
    Nellippallil AB, Mohan P, Allen JK, Mistree F (2018) Robust concept exploration of materials, products and associated manufacturing processes. ASME IDETCGoogle Scholar
  10. 10.
    Mistree F, Smith W, Bras B, Allen J, Muster D (1990) Decision-based design: a contemporary paradigm for ship design, Transactions. Society of Naval Architects and Marine Engineers 98:565–597Google Scholar
  11. 11.
    Gero JS (1990) Design prototypes: a knowledge representation schema for design. AI Mag 11(4):26Google Scholar
  12. 12.
    Shupe JA (1988) Decision-based design: taxonomy and implementation, Ph.D. Dissertation, Department of Mechanical Engineering, University of Houston, Houston, Texas,Google Scholar
  13. 13.
    Hazelrigg GA (1996) Systems engineering: an approach to information-based design. Prentice Hall, Upper Saddle River, NJGoogle Scholar
  14. 14.
    Ming Z, Nellippallil AB, Yan Y, Wang G, Goh CH, Allen JK, Mistree F (2018) PDSIDES—a knowledge-based platform for decision support in the design of engineering systems. J Comput Inf Sci Eng 18(4):041001Google Scholar
  15. 15.
    Ming Z, Yan Y, Wang G, Panchal JH, Goh CH, Allen JK, Mistree F (2016) Ontology-based executable design decision template representation and reuse. Artif Intell Eng Des Anal Manuf 30:390–405Google Scholar
  16. 16.
    Musen MA (2015) The protégé project: a look back and a look forward. AI Matters 1(4):4–12Google Scholar
  17. 17.
    Ming Z, Wang G, Yan Y, Dal Santo J, Allen JK, Mistree F (2017) An ontology for reusable and executable decision templates. J Comput Inf Sci Eng 17(3):031008Google Scholar
  18. 18.
    Ming Z, Wang G, Yan Y, Panchal JH, Goh D, Allen JK, Mistree F (2017) Ontology-based representation of design decision hierarchies. J Comput Inf Sci Eng 18:011001Google Scholar
  19. 19.
    Mistree F, Hughes OF, Bras B (1993) Compromise decision support problem and the adaptive linear programming algorithm. Prog Astronaut Aeronaut 150:251–251Google Scholar
  20. 20.
    Mistree F, Lewis K, Stonis L (1994) Selection in the conceptual design of aircraft. AIAA J:1153–1166Google Scholar
  21. 21.
    Wang R, Nellippallil AB, Wang G, Yan Y, Allen JK, Mistree F (2018) Systematic design space exploration using a template-based ontological method. Adv Eng Inform 36:163–177Google Scholar
  22. 22.
    Chen W, Allen JK, Mistree F (1997) A robust concept exploration method for enhancing productivity in concurrent systems design. Concurr Eng 5(3):203–217Google Scholar
  23. 23.
    Simpson TW, Chen W, Allen JK, Mistree F Conceptual design of a family of products through the use of the robust concept exploration method. In: Proc. 6th. AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pp 1535–1545Google Scholar
  24. 24.
    Choi H, McDowell DL, Allen JK, Rosen D, Mistree F (2008) An inductive design exploration method for robust multiscale materials design. J Mech Des 130(3):031402Google Scholar
  25. 25.
    Nellippallil AB, Allen JK, Mistree F, Vignesh R, Gautham BP, Singh AK (2017) A goal-oriented, inverse decision-based design method to achieve the vertical and horizontal integration of models in a hot-rod rolling process chain. ASME Design Automation Conference Cleveland, OhioGoogle Scholar
  26. 26.
    Nellippallil AB, Rangaraj V, Gautham B, Singh AK, Allen JK, Mistree F (2018) An inverse, decision-based design method for integrated design exploration of materials, products, and manufacturing processes. J Mech Des 140(11):111403Google Scholar
  27. 27.
    Nellippallil AB (2018) The integrated realization of materials, products and associated manufacturing processes, Doctoral Dissertation, University of Oklahoma, NormanGoogle Scholar
  28. 28.
    Reddy R, Smith W, Mistree F, Bras B, Chen W, Malhotra A, Badhrinath K, Lautenschlager U, Pakala R, Vadde S (1992) DSIDES User Manual. Systems Design Laboratory, Department of Mechanical Engineering, University of Houston, Houston, TexasGoogle Scholar
  29. 29.
    Wu D, Rosen DW, Wang L, Schaefer D (2015) Cloud-based design and manufacturing: a new paradigm in digital manufacturing and design innovation. Comput Aided Des 59:1–14Google Scholar
  30. 30.
    Panchal JH, Fernández MG, Allen JK, Paredis CJ, Mistree F Facilitating meta-design via separation of problem, product, and process information. In: Proc. ASME 2005 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, pp 49–62Google Scholar
  31. 31.
    Panchal JH, Fernández MG, Paredis CJJ, Mistree F (2004) Reusable design processes via modular, executable, decision-centric templates. In: AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY Paper Number AIAA-2004-4601Google Scholar
  32. 32.
    Lewis K, Mistree F (1998) Collaborative, sequential, and isolated decisions in design. J Mech Des 120(4):643–652Google Scholar
  33. 33.
    Panchal JH, Gero Fernández M, Paredis CJ, Allen JK, Mistree F (2009) A modular decision-centric approach for reusable design processes. Concurr Eng 17(1):5–19Google Scholar
  34. 34.
    Montgomery DC (2008) Design and analysis of experiments. John Wiley & SonsGoogle Scholar
  35. 35.
    Simpson TW, Poplinski J, Koch PN, Allen JK (2001) Metamodels for computer-based engineering design: survey and recommendations. Eng Comput 17(2):129–150Google Scholar
  36. 36.
    Mistree F, Hughes OF, Bras BA (1993) The compromise decision support problem and the adaptive linear programming algorithm. In: Kamat MP (ed) Structural Optimization: Status and Promise. AIAA, Washington, DC, pp 247–286Google Scholar
  37. 37.
    Chen W, Allen JK, Tsui K-L, Mistree F (1996) A procedure for robust design: minimizing variations caused by noise factors and control factors. J Mech Des 118(4):478–485Google Scholar
  38. 38.
    Choi H-J, Austin R, Allen JK, McDowell DL, Mistree F, Benson DJ (2005) An approach for robust design of reactive power metal mixtures based on non-deterministic micro-scale shock simulation. J Computer-Aided Mater Des 12(1):57–85Google Scholar
  39. 39.
    Nellippallil AB, Song KN, Goh C-H, Zagade P, Gautham B, Allen JK, Mistree F (2017) A goal-oriented, sequential, inverse design method for the horizontal integration of a multistage hot rod rolling system. J Mech Des 139(3):031403Google Scholar
  40. 40.
    Shukla R, Goyal S, Singh AK, Panchal JH, Allen JK, Mistree F (2015) Design exploration for determining the set points of continuous casting operation: an industrial application. J Manuf Sci Eng 137(3):034503Google Scholar
  41. 41.
    Sinha A, Bera N, Allen JK, Panchal JH, Mistree F (2013) Uncertainty management in the design of multiscale systems. J Mech Des 135(1):011008Google Scholar
  42. 42.
    Fonville TF, Nellippallil AB, Horstemeyer MF, Allen JK, and Mistree F (2019) A goal-oriented, inverse decision-based design method for multi-component product design. ASME Design Automation ConferenceAnaheim, CA. Paper Number: IDETC2019–97388. AcceptedGoogle Scholar
  43. 43.
    Gautham B, Singh AK, Ghaisas SS, Reddy SS, Mistree F (2013) PREMΛP: a platform for the realization of engineered materials and products, ICoRD’13. Springer, pp 1301–1313Google Scholar
  44. 44.
    Milisavljevic-Syed J, Allen JK, Commuri S, Mistree F (2019) Design of networked manufacturing systems for Industry 4.0. In: CIRP manufacturing systems conferenceGoogle Scholar
  45. 45.
    Yadav A, Das AK, Allen JK, Mistree F (2019) A computational framework to support social entrepreneurs in creating value for rural communities in India ASME Design Automation ConferenceAnaheim, CA Paper Number: IDETC2019–97375. AcceptedGoogle Scholar

Copyright information

© The Minerals, Metals & Materials Society 2019

Authors and Affiliations

  1. 1.Center for Advanced Vehicular SystemsMississippi State UniversityStarkvilleUSA
  2. 2.Systems Realization Laboratory @ OUUniversity of OklahomaNormanUSA

Personalised recommendations