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Integrated Design of Materials, Products, and Associated Manufacturing Processes

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Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes

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Abstract

In practice, “design” involved the selection of a suitable material for a given application (Nortan 1996; Shigley 1972; Ashby and Cebon 1993, Pahl and Beitz 2013). The performance of many engineered systems involving materials and products is limited by the available properties of the constituent materials. The difficulty here with material selection is the inherent inability to tailor a material microstructure and constituents for satisfying application-specific requirements.

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References

  • Adams, B. L., Kalidindi, S., & Fullwood, D. T. (2013). Microstructure-sensitive design for performance optimization. Butterworth-Heinemann.

    Google Scholar 

  • Afshari, H., Peng, Q., & Gu, P. (2016). Design optimization for sustainable products under users’ preference changes. Journal of Computing and Information Science in Engineering, 16(4), 041001–041007.

    Google Scholar 

  • Allen, J. K., Seepersad, C., Choi, H., & Mistree, F. (2006). Robust design for multiscale and multidisciplinary applications. Journal of Mechanical Design, 128(4), 832–843.

    Article  Google Scholar 

  • Allen, J. K., Panchal, J., Mistree, F., Singh, A. K., & Gautham, B. (2015). Uncertainty management in the integrated realization of materials and components. In Proceedings of the 3rd World Congress on Integrated Computational Materials Engineering. John Wiley & Sons.

    Google Scholar 

  • Amarel, S. (1990). Artificial intelligence and design. In Proceedings of the 5th Jerusalem Conference on Information Technology, IEEE.

    Google Scholar 

  • Anapagaddi, R., Shukla, R., Mangal, S., & Singh, A. K. (2013). Exploring the design space of a continuous casting tundish for improved inclusion removal and reduced dead volume.

    Google Scholar 

  • Anapagaddi, R., Shukla, R., Goyal, S., Singh, A. K., Allen, J. K., Panchal, J. H., & Mistree, F. (2014). Exploration of the design space in continuous casting Tundish. ASME Design Automation Conference. Paper Number: DETC2014-34254.

    Google Scholar 

  • Ashby, M. F., & Cebon, D. (1993). Materials selection in mechanical design. Le Journal de Physique IV, 3(C7), C7-1–C7-9.

    Google Scholar 

  • Ashby, M. F., & Johnson, K. (2013). Materials and design: The art and science of material selection in product design. Butterworth-Heinemann.

    Google Scholar 

  • Ashby, M. F., Evans, T., Fleck, N. A., Hutchinson, J., Wadley, H., & Gibson, L. (2000). Metal foams: A design guide. Elsevier.

    Google Scholar 

  • Beitz, W., Pahl, G., & Grote, K. (1996). Engineering design: A systematic approach. MRS Bulletin, 71.

    Google Scholar 

  • Berg, L. P., & Vance, J. M. (2016). An industry case study: Investigating early design decision making in virtual reality. Journal of Computing and Information Science in Engineering, 17(1), 011001–011007.

    Google Scholar 

  • Box, G. E. (1979). In the strategy of scientific model building. Robustness in statistics. Elsevier, pp. 201–236.

    Google Scholar 

  • Box, G. (1988). Signal-to-noise ratios, performance criteria, and transformations. Technometrics, 30(1), 1–17.

    Article  MathSciNet  MATH  Google Scholar 

  • Bras, B., & Mistree, F. (1993). Robust design using compromise problems. Engineering Optimization, 21(3), 213–239.

    Article  Google Scholar 

  • Chen, W., Tsui, K.-L., Allen, J. K., & Mistree, F. (1995). Integration of the response surface methodology with the compromise problem in developing a general procedure. In ASME Design Automation Conference, Boston, Massachusetts, pp. 485–492.

    Google Scholar 

  • Chen, W., Allen, J. K., Tsui, K.-L., & Mistree, F. (1996). A procedure for: Minimizing variations caused by noise factors and control factors. Journal of Mechanical Design, 118(4), 478–485.

    Article  Google Scholar 

  • Chen, W., Allen, J. K., & Mistree, F. (1997). A robust method for enhancing productivity in concurrent systems design. Concurrent Engineering, 5(3), 203–217.

    Article  Google Scholar 

  • Chen, W., Simpson, T. W., Allen, J. K., & Mistree, F. (1999). Satisfying ranged sets of design requirements using as metrics. Engineering Optimization, 31(5), 615–619.

    Article  Google Scholar 

  • Chiu, D. K. W., Cheung, S. C., Hung, P. C. K., & Leung, H. F. (2005). Facilitating e-negotiation processes with semantic web technologies. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS’05) Track 1, p. 36a.

    Google Scholar 

  • Choi, H.-J., Austin, R., Allen, J. K., McDowell, D. L., Mistree, F., & Benson, D. J. (2005). An approach for of reactive power metal mixtures based on non-deterministic micro-scale shock simulation. Journal of Computer-Aided Materials Design, 12(1), 57–85.

    Article  Google Scholar 

  • Choi, H.-J., Mcdowell, D. L., Allen, J. K., & Mistree, F. (2008a). An inductive design exploration method for hierarchical systems design under uncertainty. Engineering Optimization, 40(4), 287–307.

    Article  Google Scholar 

  • Choi, H., McDowell, D. L., Allen, J. K., Rosen, D., & Mistree, F. (2008b). An inductive design exploration method for robust multiscale materials design. Journal of Mechanical Design, 130(3), 031402.

    Article  Google Scholar 

  • Daskilewicz, M. J., & German, B. J. (2012). Rave: A computational framework to facilitate research in design decision support. Journal of Computing and Information Science in Engineering, 12(2), 021005–021009.

    Google Scholar 

  • Eberhart, M. E., & Clougherty, D. P. (2004). Looking for design in materials design. Nature Materials, 3(10), 659.

    Article  Google Scholar 

  • Georgescu, C., & Boonstra, V. F. (1990). Concept exploration models for merchant ships.

    Google Scholar 

  • Gero, J. S. (1990a). Design prototypes: A knowledge representation schema for design. AI Magazine, 11(4), 26.

    Google Scholar 

  • Gero, J. S. (1990). Knowledge-based design systems. Addison-Wesley.

    Google Scholar 

  • Gero, J. S. (1996). Creativity, emergence and evolution in design. Knowledge-Based Systems, 9(7), 435–448.

    Article  Google Scholar 

  • Horstemeyer, M. F. (2012). Integrated computational materials engineering () for metals: Using to invigorate engineering design with science. John Wiley & Sons.

    Google Scholar 

  • Horstemeyer, M. F. (2018). Integrated computational materials engineering () for metals: Concepts and case studies. John Wiley & Sons.

    Google Scholar 

  • Howard, R. A. (1966). Information value theory. IEEE Transactions on Systems Science and Cybernetics, 2(1), 22–26.

    Article  Google Scholar 

  • Isukapalli, S., Roy, A., & Georgopoulos, P. (1998). Stochastic response surface methods (SRSMs) for uncertainty propagation: Application to environmental and biological systems. Risk Analysis, 18(3), 351–363.

    Article  Google Scholar 

  • Kalidindi, S. R. (2015). Hierarchical materials informatics: Novel analytics for materials data. Elsevier.

    Google Scholar 

  • Kalidindi, S. R., Niezgoda, S. R., Landi, G., Vachhani, S., & Fast, T. (2010). A novel framework for building materials knowledge systems. Computers, Materials, & Continua, 17(2), 103–125.

    Google Scholar 

  • Kalidindi, S. R., Niezgoda, S. R., & Salem, A. A. (2011). Microstructure informatics using higher-order statistics and efficient data-mining protocols. JOM Journal of the Minerals Metals and Materials Society, 63(4), 34–41.

    Article  Google Scholar 

  • Kern, P. C., Priddy, M. W., Ellis, B. D., & McDowell, D. L. (2017). pyDEM: A generalized implementation of the inductive design exploration method. Materials & Design, 134, 293–300.

    Google Scholar 

  • Kuppuraju, N., Ganesan, S., Mistree, F., & Sobieski, J. S. (1985). Hierarchical decision-making in system-design. Engineering Optimization, 8(3), 223–252.

    Article  Google Scholar 

  • Li, C., & Mahadevan, S. (2016). Role of calibration, validation, and relevance in multi-level uncertainty integration. Reliability Engineering & System Safety, 148, 32–43.

    Google Scholar 

  • Liu, S., Duffy, A. H. B., Boyle, I. M., & Whitfield, R. I. (2008). Knowledge re-use for decision support. In Realising network enabled capability 2008, 2008-10-13–2008-10-14, Oulton Hall Hotel, Leeds.

    Google Scholar 

  • Liu, S., Duffy, A. H. B., Whitfield, R. I., Boyle, I. M., & McKenna, I. (2009). Towards the realisation of an integratated decision support environment for organisational decision making. International Journal of the Decision Support System Technology, 1(4), 35–58.

    Article  Google Scholar 

  • Matthews, J., Klatt, T., Morris, C., Seepersad, C. C., Haberman, M., & Shahan, D. (2016). Hierarchical design of negative stiffness metamaterials using a Bayesian network classifier. Journal of Mechanical Design, 138(4), 041404.

    Article  Google Scholar 

  • McDowell, D. L. (2018). Microstructure-sensitive computational structure-property relations in materials design (pp. 1–25). Computational Materials System Design: Springer.

    Google Scholar 

  • McDowell, D. L., & Kalidindi, S. R. (2016). The materials innovation ecosystem: A key enabler for the materials genome initiative. MRS Bulletin, 41(4), 326–337.

    Article  Google Scholar 

  • McDowell, D. L., & LeSar, R. A. (2016). The need for microstructure informatics in process–structure–property relations. MRS Bulletin, 41(8), 587–593.

    Article  Google Scholar 

  • McDowell, D. L., & Olson, G. (2008). Concurrent design of hierarchical materials and structures (pp. 207–240). Scientific Modeling and Simulations: Springer.

    Google Scholar 

  • McDowell, D., & Story, T. (1998). New directions in materials design science and engineering. In Report of a Workshop Sponsored by the US National Science Foundation, Georgia Institute of Technology and Morehouse College, Atlanta, GA.

    Google Scholar 

  • McDowell, D. L., Choi, H. J., Panchal, J., Austin, R., Allen, J., & Mistree, F. (2007). Plasticity-related microstructure-property relations for materials design. Key Engineering Materials: Trans Tech Publ.

    Google Scholar 

  • McDowell, D. L., Panchal, J., Choi, H.-J., Seepersad, C., Allen, J., & Mistree, F. (2009). Integrated design of multiscale, multifunctional materials and products. Butterworth-Heinemann.

    Google Scholar 

  • Messer, M. (2008). A systematic approach for integrated product, materials, and design-process design. Ph.D. Dissertation, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology.

    Google Scholar 

  • Ming, Z., Nellippallil, A. B., Yan, Y., Wang, G., Goh, C. H., Allen, J. K., et al. (2018). PDSIDES—A knowledge-based platform for decision support in the design of engineering systems. Journal of Computing and Information Science in Engineering, 18(4), 041001.

    Article  Google Scholar 

  • Mistree, F., Hughes, O. F., & Bras, B. (1993). Compromise problem and the adaptive linear programming algorithm. Progress in Astronautics and Aeronautics, 150, pp. 251–251.

    Google Scholar 

  • Mullins, J., & Mahadevan, S. (2016). Bayesian uncertainty integration for model calibration, validation, and prediction. Journal of Verification, Validation and Uncertainty Quantification, 1(1), 011006.

    Article  Google Scholar 

  • Murphy, T. E., Tsui, K.-L., & Allen, J. K. (2005). A review of methods for multiple responses. Research in Engineering Design, 15(4), 201–215.

    Article  Google Scholar 

  • Nair, V. N., Abraham, B., MacKay, J., Box, G., Kacker, R. N., Lorenzen, T. J., et al. (1992). Taguchi’s parameter design: A panel discussion. Technometrics, 34(2), 127–161.

    Article  MathSciNet  Google Scholar 

  • Nellippallil, A., Song, K., Goh, C.-H., Zagade, P., Gautham, B., Allen, J., & Mistree, F. (2016). A goal oriented, sequential process design of a multi-stage hot rod rolling system. ASME Design Automation Conference, Paper Number: DETC2016-59402.

    Google Scholar 

  • Nellippallil, A. B., Allen, J. K., Mistree, F., Vignesh, R., Gautham, B. P., & Singh, A. K. (2017a). 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, Paper Number: DETC2017‐67570.

    Google Scholar 

  • Nellippallil, A. B., Song, K. N., Goh, C.-H., Zagade, P., Gautham, B., Allen, J. K., & Mistree, F. (2017b). A goal-oriented, sequential, inverse design method for the horizontal integration of a multistage hot rod rolling system. Journal of Mechanical Design, 139(3), 031403.

    Google Scholar 

  • Nellippallil, A. B., Vignesh, R., Allen, J. K., Mistree, F., Gautham, B. P., & Singh, A. K. (2017c). A decision-based design method to explore the solution space for microstructure after cooling stage to realize the end mechanical properties of hot rolled product. In 4th World Congress on Integrated Computational Materials Engineering, Ypsilanti, Michigan, USA.

    Google Scholar 

  • Nellippallil, A. B., Mohan, P., Allen, J. K., & Mistree, F. (2018a). Robust of materials, products and associated manufacturing processes. ASME Design Automation Conference, Paper Number: DETC2018-85913.

    Google Scholar 

  • Nellippallil, A. B., Rangaraj, V., Gautham, B. P., Singh, A. K., Allen, J. K. & Mistree, F. (2018b). An inverse, decision-based design method for integrated design exploration of materials, products and manufacturing processes. ASME Journal of Mechanical Design, 140(11), 111403-111403-17

    Google Scholar 

  • Nellippallil, A. B., Ming, Z., Allen, J. K., & Mistree, F., (2019a). Cloud-based materials and product realization—Fostering ICME via Industry 4.0, Integrating Materials and Manufacturing Innovation, 8(2), 107–121.

    Google Scholar 

  • Nellippallil, A. B., Mohan, P., Allen, J. K., & Mistree, F. (2019b). Inverse Thermo-Mechanical Processing (ITMP) design of a steel rod during hot rolling process. ASME Design Automation Conference, Paper Number: IDETC2019-97390.

    Google Scholar 

  • Nellippallil, A. B., Mohan, P., Allen, J. K., & Mistree, F. (2020). An inverse, decision-based design method for robust concept exploration. Journal of Mechanical Design, https://doi.org/10.1115/1.4045877.

  • Norton, R. L. (1996) Machine design: An integrated approach. Prentice-Hall Inc: NJ, USA.

    Google Scholar 

  • Olson, G. B. (1997). Computational design of hierarchically structured materials. Science, 277(5330), 1237–1242.

    Article  Google Scholar 

  • Olson, G. B. (2000). Designing a new material world. Science, 288(5468), 993–998.

    Article  Google Scholar 

  • Pahl, G., & Beitz, W. (2013). Engineering design: A systematic approach. Springer Science & Business Media.

    Google Scholar 

  • Panchal, J. H. (2005). A framework for simulation-based integrated design of multiscale products and design processes, Ph.D. Dissertation, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology.

    Google Scholar 

  • Panchal, J. H., Choi, H.-J., Shephard, J., Allen, J. K., McDowell, D. L., & Mistree, F. (2005). A strategy for simulation-based multiscale, multi-functional products and associated design processes. ASME Design Automation Conference, Paper Number: DETC2005-85316.

    Google Scholar 

  • Panchal, J. H., Paredis, C. J., Allen, J. K., & Mistree, F. (2006). Simulation model refinement for decision making via a value-of-information based metric. ASME Design Automation Conference, Paper Number: DETC2006-99433.

    Google Scholar 

  • Panchal, J. H., Kalidindi, S. R., & McDowell, D. L. (2013). Key computational modeling issues in integrated computational materials engineering. Computer-Aided Design, 45(1), 4–25.

    Article  Google Scholar 

  • Parkinson, A., Sorensen, C., & Pourhassan, N. (1993). A general approach for robust optimal design. Journal of Mechanical Design, 115(1), 74–80.

    Article  Google Scholar 

  • Pedersen, K., Emblemsvag, J., Bailey, R., Allen, J., & Mistree, F. (2000a). The ‘Validation Square’–Validating Design Methods. In ASME Design Theory and Methodology Conference, New York: ASME.

    Google Scholar 

  • Pedersen, K., Emblemsvag, J., Bailey, R., Allen, J. K., & Mistree, F. (2000b). Validating design methods and research: The validation square. ASME Design Engineering Technical Conferences, DETC2000/DTM-14579.

    Google Scholar 

  • Pollock, T.M., Allison J. E., et al. (2008). Integrated computational materials engineering: a transformational discipline for improved competitiveness and national security. National Academies Press.

    Google Scholar 

  • Rockwell, J. A., Grosse, I. R., Krishnamurty, S., & Wileden, J. C. (2010). A semantic information model for capturing and communicating design decisions. Journal of Computing and Information Science in Engineering, 10(3), 031008.

    Article  Google Scholar 

  • Rühle, M., Dosch, H., Mittemeijer, E., & Van de Voorde, M. (2001). European White book on fundamental research in materials science.

    Google Scholar 

  • Schoop, M., Becks, A., Quix, C., Burwick, T., Engels, C., & Jarke, M., (2002) Enhancing decision and negotiation support in enterprise networks through semantic web technologies, www.sewasie.org/documents/xsw2002.pdf.

  • Seepersad, C. C., Pedersen, K., Emblemsvåg, J., Bailey, R., Allen, J. K., & Mistree, F. (2006). The validation square: How does one verify and validate a design method? (pp. 303–314). New York: ASME Press.

    Google Scholar 

  • Shahan, D. W., & Seepersad, C. C. (2012). Bayesian network classifiers for set-based collaborative design. Journal of Mechanical Design, 134(7), 071001.

    Article  Google Scholar 

  • Shigley, J. E. (1972). Mechanical engineering design. McGraw-Hill, New York, NY.

    Google Scholar 

  • Shoemaker, A. C., Tsui, K.-L., & Wu, C. J. (1991). Economical experimentation methods for. Technometrics, 33(4), 415–427.

    Article  Google Scholar 

  • Shukla, R., Anapagaddi, R., Singh, A. K., Panchal, J. H., Allen, J. K., & Mistree, F. (2015). Exploring the design set points of refining operation in ladle for cost effective desulfurization and inclusion removal. ASME Design Automation Conference, Paper Number: DETC2015-46265.

    Google Scholar 

  • Sinha, A., Bera, N., Allen, J. K., Panchal, J. H., & Mistree, F. (2013). In the design of multiscale systems. Journal of Mechanical Design, 135(1), 011008.

    Google Scholar 

  • Smith, W., Mistree, F. (1994). The development of top level ship specifications: A decision-based approach.

    Google Scholar 

  • Soria, N., Colby, M. K., Tumer, I. Y., Hoyle, C., & Tumer, K. (2017). Design of complex engineered system using multiagent coordination. Journal of Computing and Information Science in Engineering, 18(1), 011003-1-13.

    Google Scholar 

  • Sundaresan, S., Ishii, K., & Houser, D. R. (1995). A robust optimization procedure with variations on design variables and constraints. Engineering Optimization + A35, 24(2), 101–117.

    Google Scholar 

  • Taguchi, G. (1986). Introduction to quality engineering: Designing quality into products and processes. Quality Resources.

    Google Scholar 

  • Taguchi, G. (1993). Robust technology development. Mechanical Engineering-CIME, 115(3), 60–63.

    Google Scholar 

  • Taguchi, G., & Clausing, D. (1990). Robust quality. Harvard Business Review, 68(1), 65–75.

    Google Scholar 

  • Tong, C., & Sriram, R. D. (1997). Artificial intelligence in engineering design. Academic Press.

    Google Scholar 

  • Tsui, K.-L. (1992). An overview of Taguchi method and newly developed statistical methods for. IIE Transactions, 24(5), 44–57.

    Article  Google Scholar 

  • Vining, G. G., & Myers, R. H. (1990). Combining Taguchi and response surface philosophies: A dual response approach. Journal of Quality Technology, 22(1), 38–45.

    Article  Google Scholar 

  • Wang, R., Nellippallil, A. B., Wang, G., Yan, Y., Allen, J. K., & Mistree F. (2018) Systematic design space exploration using a template-based ontological method. Advanced Engineering Informatics, 36,163–177.

    Google Scholar 

  • Wang, R., Nellippallil, A. B., Wang, G., Yan, Y., Allen, J. K., & Mistree, F. (2019). Ontology-based uncertainty management approach in designing of robust decision workflows. Journal of Engineering Design, 30(10–12), 726–757.

    Article  Google Scholar 

  • Welch, W., Yu, T., Kang, S. M., & Sacks, J. (1990). Computer experiments for quality control by parameter design. Journal of Quality Technology, 22(1), 15–22.

    Article  Google Scholar 

  • Zha, X. F., Lim, Y. E., & Lu, W. F. (2003a). A knowledge intensive multi-agent system for cooperative/ collaborative assembly modeling and process planning. Journal of Integrated Design and Process Science, 7(1), 99–122.

    Google Scholar 

  • Zha, X. F., Sriram, R. D., & Lu, W. F. (2003b). Knowledge-Intensive Collaborative Decision Support For Design Processes. ASME Design Automation Conference, Paper Number: DETC2003/DAC-48747.

    Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL, USA

    Anand Balu Nellippallil

  2. School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK, USA

    Janet K. Allen

  3. TCS Research, TRDDC, Tata Consultancy Services, Pune, India

    B. P. Gautham

  4. Department of Materials Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India

    Amarendra K. Singh

  5. School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK, USA

    Farrokh Mistree

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  1. Anand Balu Nellippallil
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Nellippallil, A.B., Allen, J.K., Gautham, B.P., Singh, A.K., Mistree, F. (2020). Integrated Design of Materials, Products, and Associated Manufacturing Processes. In: Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes. Springer, Cham. https://doi.org/10.1007/978-3-030-45324-4_1

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