Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes PDF
Preview Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes
Anand Balu Nellippallil · Janet K. Allen · B. P. Gautham · Amarendra K. Singh · Farrokh Mistree Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes Anand Balu Nellippallil Janet K. Allen (cid:129) (cid:129) B. P. Gautham Amarendra K. Singh (cid:129) (cid:129) Farrokh Mistree Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes 123 Anand BaluNellippallil Janet K.Allen Department ofMechanical andCivil Schoolof Industrial andSystems Engineering Engineering Florida Institute of Technology University of Oklahoma Melbourne, FL,USA Norman, OK, USA B. P.Gautham Amarendra K.Singh TCSResearch,TRDDC Department ofMaterials Science TataConsultancy Services andEngineering Pune,India Indian Institute of Technology Kanpur Kanpur,India Farrokh Mistree Schoolof Aerospace andMechanicalEngineering University of Oklahoma Norman, OK, USA ISBN978-3-030-45323-7 ISBN978-3-030-45324-4 (eBook) https://doi.org/10.1007/978-3-030-45324-4 ©SpringerNatureSwitzerlandAG2020 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. 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ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Foreword Since the establishment of the Integrated Computational Materials Engineering (ICME) initiative in 2008 and the Materials Genome Initiative in 2011, focus has been increasingly drawn toward the use of computational materials science and mechanics tools and methods to predict material process–structure–property rela- tions. One branch of inquiry has focused on predictive materials computation to discovernewmaterials,acceleratedusingcombinatorialstrategies.Anotherpursuit involves enhancement of materials selection for design applications, which had been the overarching goal of “materials design” in the late twentieth century. Sometime around 2005, Professors Farrokh Mistree, Janet K. Allen, and I envisionedthepressingneedtoextendformalengineeringsystemsdesign,namely conceptsofdecision-makingindesignandmultidisciplinarydesignoptimization,to addressthehierarchical structure ofmaterials, along with processpath dependence of this structure and resulting properties. This collaboration at Georgia Tech ulti- mately led to the first monograph in this area, Integrated Design of Multiscale, Multifunctional Materials and Products, published by Butterworth-Heinemann in 2010 (ISBN 978-1-85617-662-0) and co-authored with some of our joint Ph.D. students (Carolyn C. Seepersad, Hae-Jin Choi, and Jitesh H. Panchal). That initial body of work focused on the integration of product design specifications with the top-down requirements on material properties/responses. An inductive design exploration framework was introduced to pursue multilevel robust inverse design across length scales of material structure comprising physical products. A fundamental assertion was that materials design is a process that necessitates an engineering systems approach, and cannot be addressed in a decoupled way as a materials selection problem without greatly compromising the breadth of available solutions.Moreover,uncertaintyplaysa keyrole inmaterials design,necessitating the notion of robust design across a set of objectives or goals rather than single point/goal optimization. That initial book ended with a discussion offuture direc- tions in distributed, collaborative concurrent design of materials and products and distributed product realization. The resulting concepts of decision-based materials v vi Foreword design are central to unleashing the real power of computation and experiment in acceleratingtherateofdevelopmentofnewandimprovedmaterialsforapplications. Ithasbecomeapparentintheyearsfollowingour2010bookthatoneofthemost underdeveloped aspects of this vision of multilevel integrated design of materials and products has to do with the consideration of manufacturing processes. In particular, materials processing/synthesis is extremely complex to model, often involvinghighlynonlinearandnon-equilibriumevolutionofthematerialstructure. Evolutionofmaterial structurestrongly affectsproperties,andistightlycoupledto the selected product manufacturing route. Often, only heuristics are available to provide guidance for material process–structure relations, which carry high uncertainty. Though part of the vision of our earlier monograph, the relation of materials process path to structure and properties was not emphasized, the link to manufacturing processes was evident, but not elaborated to a significant extent. In thisnewworkwiththeirformerstudentDr.NellippallilandcolleaguesatTataand IITKanpur,ProfessorsAllenandMistreehavefocusedonthecouplingofmaterial process–structure–property relations with product design and manufacturing. Doingsorequiresmoreformaltreatmentofidentificationofmaterialstructuresand processingpathsthatareconstrainedbyavailablemanufacturingprocessesandthe satisfaction of certain required product and manufacturing process-level properties and performance. This requires detailed mappings of steps involved in materials processingthatprecedesorassociateswithproductmanufacture.Moreover,models framedatvariouslevelsoffidelityanduncertaintyquantificationmustbeemployed. Tothisend,theworkinthisvolumepursuestheconceptsofverticalandhorizontal integration of information from models and experiments/sensors; vertical integra- tion addresses multiscale modeling over relevant material length and time scales, while horizontal integration relates to integration of manufacturing processes. This advancement ofthe inverse decision-based design paradigm isnecessary to realize true integration of various manufacturing processes in concurrent materials and product design. Design variables lie within the triad of material, product, and manufacturing process. This is truly rich and fertile ground for materials design research and points to the need to extend next-generation CAD systems in our increasingly digital manufacturing-materials world. Broadly speaking, I think this is the way engi- neeringdesignwillbetaught sometime inthe(hopefullynottoodistant) future.In the meantime, this new foundational work identifies and addresses research gaps andchallenges inrobust concept explorationasaprecursortodetail design,which isanimportantfirststepinaligninginvestmentstrategiestowardfeasiblesolutions that include available manufacturing routes. The networking of stakeholders involved in co-creation of value supporting open innovation is defined by the authors as enabling the capability to carry out co-design. Linking co-design to achievinggoalsofintegratedmaterialsandproductdesignasrequiredbyICMEisa critical aspect of this volume. Accordingly, the authors address future cloud-based design support systems for networked workflows and collaboration among widely distributed experts and stakeholders. Moreover, they include the role of emergent data science methods, including machine learning. Foreword vii I am pleased to recommend this stimulating and insightful book on integrated design material, product, and manufacturing process to your personal library, organization, university, or company (whether Fortune 500 or a start-up). I would also encourage the ideas presented here to become part of a broader conversation regarding design education at the interface of various engineering disciplines, including materials science and engineering, as well as materials physics and chemistry. Their approach to robust co-design is systematic and well-conceived, helping the reader organize the relevant challenges and opportunities for transfor- mational change. I trust its value will endure. David L. McDowell Regents’ Professor and Carter N. Paden Jr. Distinguished Chair in Metals Processing Georgia Institute of Technology Atlanta, GA, USA Preface In the context of the emerging Integrated Computational Materials Engineering (ICME) and Digital Manufacturing and Design Innovation(DMDI)paradigms,we presentinthismonographourvision,thatis,tocollaboratively(withacademicand industrialpartners)definetheemergingfrontiersforarchitectingrobustco-designof materials, products, and associated manufacturing processes. We recognize in this monograph that in order to foster the integrated realization of materials, products, and manufacturing processes, there is a need to not just design, but facilitate co-design. We define co-design as the ability of a network of participants, which includes material scientists, systems designers, software developers, and end cus- tomers to come together and share material/product/manufacturing process/market data, information, knowledge, and resources instantly and thereby collaborate to facilitate cost-effective co-creation of value supporting open innovation. Our foundational premise is that systems-based co-design makes it possible for tailoringmaterials,theirprocessingpaths,andtheendproductsconstitutedbythese materialsinanintegratedfashionfor challengingapplicationstosatisfyconflicting productandprocess-levelpropertyandperformancerequirements.Accordingly,we establish a systems-based design architecture that includes systems-level synthesis methods and tools for the robust co-design of complex materials, products, and associated manufacturing processes starting from the end requirements. The core question that we address is: What are the theoretical, mathematical, and computational foundations needed for establishing a comprehensive systems-based design architecture to realize the robust co-design of the product, its environment, manufacturing processes and material as a system? The major research challenges addressed in this monograph are: (cid:129) Integration of models of different fidelities (material, process, and product) to establish processing–structure–property–performance relationships. (cid:129) Goal-oriented, inverse design of material microstructures and processing paths to meet multiple conflicting performance/property requirements. ix x Preface (cid:129) Robust concept exploration by managing uncertainty across process chains. (cid:129) Systematic, domain-independent, modular, reconfigurable, reusable, computer interpretable,archivable,andmultiobjectivedecisionsupportintheearlystages of design to different users. The components of the systems-based design architecture proposed in this monograph to address these research challenges are shown in Fig. 1. The compo- nents include: (cid:129) Systematic model integration and information flow. (cid:129) Systematic concept exploration. (cid:129) Systematic inverse design exploration. (cid:129) Systematic robust concept exploration by managing uncertainty. (cid:129) Knowledge-based platform for decision support. (cid:129) Cloud-based decision support. The key features of the systems-based design architecture adding value to the emerging ICME and DMDI paradigms are: (cid:129) Systematic function structure-based identification and integration of material, process, and product models and workflows to define processing–structure– property–performance mapping and information workflow. (cid:129) A framework supporting systematic design and solution space exploration. (cid:129) A generic method for inverse design of materials and products across process chains. (cid:129) Metrics, robust design constraints, and goals for facilitating robust design by managing uncertainty across process chains for multiple conflicting goals. Fig.1 Componentsofthesystems-baseddesignarchitecturefortherobustco-designofmaterials, products,andmanufacturingprocessesasproposedinthismonograph Preface xi (cid:129) Capture knowledge using original design, maintain consistency using adaptive design, and provide a package of documented knowledge using variant design. (cid:129) Cloud-based decision support platform that embodies the above-said features andfunctionalitiesenablingnetworkeddecision-baseddesignworkflows,design collaborations, instant communication, and feedback. This monograph is comprised of eight chapters; see Fig. 2. While we recom- mendreadingthechapterssequentially,eachchapterisself-contained,andchapters canbereadindependentlyorinanypreferredsequence.Followingtheintroductory chapter, in Chap. 2, a review of the existing efforts associated with materials and Fig.2 Organizationofthemonograph
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