CHAPTER 1 Introduction to e-Design Chapter Outline 1.1 Introduction 2 1.2 The e-Design Paradigm 6 1.3 Virtual Prototyping 8 1.3.1 Parameterized CADProduct Model 8 Parameterized ProductModel 9 Analysis Models 9 Motion SimulationModels 11 1.3.2 Product Performance Analysis 12 Motion Analysis 12 Structural Analysis 13 Fatigue andFracture Analysis 13 Product Reliability Evaluations 13 1.3.3 Product Virtual Manufacturing 14 1.3.4 ToolIntegration 16 1.3.5 DesignDecision Making 16 DesignProblem Formulation 17 DesignSensitivity Analysis 18 Parametric Study 19 DesignTrade-Off Analysis 20 What-If Study 21 1.4 Physical Prototyping 22 1.4.1 RapidPrototyping 22 1.4.2 CNCMachining 24 1.5 Example: Simple Airplane Engine 26 System-Level Design 26 Component-Level Design 27 DesignTrade-Off 29 Rapid Prototyping 30 1.6 Example: High-Mobility Multipurpose Wheeled Vehicle 30 Hierarchical ProductModel 31 Preliminary Design 32 Detail Design 34 DesignTrade-Off 35 1.7 Summary 38 Questions and Exercises 39 References 39 Sources 40 ProductPerformanceEvaluationusingCAD/CAE.http://dx.doi.org/10.1016/B978-0-12-398460-9.00001-9 Copyright(cid:1)2013ElsevierInc.Allrightsreserved. 1 2 Chapter 1 Conventionalproductdevelopmentemploysadesign-build-testphilosophy.Thesequentially executed development process often results in prolonged lead times and elevated product costs. The proposed e-Design paradigm employs IT-enabled technology for product design, including virtual prototyping (VP) to support a cross-functional team in analyzing product performance, reliability, and manufacturing costs early in product development, and in makingquantitativetrade-offsfordesigndecisionmaking.Physicalprototypesoftheproduct designarethenproducedusingtherapidprototyping(RP)techniqueandcomputernumerical control (CNC) to support designverification and functional prototyping, respectively. e-Design holds potential for shortening the overall product development cycle, improving productquality,andreducingproductcosts.Itoffersthreeconceptsandmethodsforproduct development: • Bringing product performance, quality, and manufacturing costs together early in design for consideration. • Supporting design decision making based on quantitative product performance data. • Incorporating physical prototyping techniques to support designverification and functional prototyping. 1.1 Introduction A conventional product development process that is usually conducted sequentially suffers theproblemofthedesignparadox(Ullman1992).Thisreferstothedichotomyormismatch betweenthedesignengineer’sknowledgeabouttheproductandthenumberofdecisionstobe made (flexibility) throughout the product development cycle (see Figure 1.1). Major design decisions are usually made in the early design stage when the product is not very well understood. Consequently, engineering changes are frequently requested in later product Figure 1.1: The design paradox. Introduction to e-Design 3 development stages, when product design evolves and is better understood, to correct decisions made earlier. Conventional product development is a design-build-test process. Product performance and reliability assessments depend heavily on physical tests, which involve fabricating functional prototypes of the product and usually lengthy and expensive physical tests. Fabricating prototypes usually involves manufacturing process planning and fixtures andtoolingforaverysmallamountofproduction.Theprocesscanbeexpensiveandlengthy, especially when a design change is requested to correct problems found in physical tests. In conventional product development, design and manufacturing tend to be disjoint. Often, manufacturability of a product is not considered in design. Manufacturing issues usually appear when the design is finalized and tests are completed. Design defects related to manufacturing in process planning or production are usually found too late to be corrected. Consequently, more manufacturing procedures are necessary for production, resulting in elevated product cost. Withthishighlystructuredandsequentialprocess,theproductdevelopmentcycletendstobe extended, cost is elevated, and product quality is often compromised to avoid further delay. Costs and the number of engineering change requests (ECRs) throughout the product development cycle are often proportional according to the pattern shown in Figure 1.2. It is reported that only 8% of the total product budget is spent for design; however, in the early stage, design determines 80% of the lifetime cost of the product (Anderson 1990). Realistically,today’sindustrieswillnotsurviveworldwidecompetitionunlesstheyintroduce new products of better quality, at lower cost, and with shorter lead times. Many approaches and concepts have been proposed over the years, all with a common goaldto shorten the product development cycle, improve product quality, and reduce product cost. Anumberofproposedapproachesarealongthelinesofvirtualprototyping(Lee1999),which isasimulation-basedmethodthathelpsengineersunderstandproductbehaviorandmake Figure 1.2: Cost/ECR versus time in a conventional design cycle. 4 Chapter 1 designdecisionsinavirtualenvironment.Thevirtualenvironmentisacomputational frameworkinwhichthegeometricandphysicalpropertiesofproductsareaccuratelysimulated andrepresented.Anumberofsuccessfulvirtualprototypeshavebeenreported,suchas Boeing’s777jetliner,GeneralMotors’locomotiveengine,Chrysler’sautomotiveinterior design,andtheStockholmMetro’sCar2000(Lee1999).Inadditiontovirtualprototyping,the concurrentengineering(CE)conceptandmethodologyhavebeenstudiedanddevelopedwith emphasisonsubjectssuchasproductlifecycledesign,designforX-abilities(DFX),integrated productandprocessdevelopment(IPPD),andSixSigma(Prasad1996). Althoughsignificantresearchhasbeenconductedinimprovingtheproductdevelopment process,andsuccessfulstorieshavebeenreported,industryatlargeisnottakingadvantageof newproductdevelopmentparadigms.Themainreasonisthatsmallandmid-sizecompanies cannotaffordtodevelopanin-housecomputertoolenvironmentlikethoseofBoeingandthe Big-Threeautomakers.Ontheotherhand,commercialsoftwaretoolsarenottailoredtomeet thespecificneedsofindividualcompanies;theyoftenlackproperengineeringcapabilitiesto supportspecificproductdevelopmentneeds,andmostofthemarenotproperlyintegrated. Therefore,companiesareusingcommercialtoolstosupportsegmentsoftheirproduct developmentwithoutemployingthenewdesignparadigmstotheirfulladvantage. The e-Design paradigm does not supersede any of the approaches discussed. Rather, it is simply a realization of concurrent engineering through virtual and physical prototyping with a systematic and quantitative method for design decision making. Moreover, e-Design specializes in performance and reliability assessment and improvement of complex, large-scale, compute-intensive mechanical systems. The paradigm also uses design for manufacturability (DFM), design for manufacturing and assembly (DFMA), and manufacturing cost estimates through virtual manufacturing process planning and simulation for design considerations. The objective of this chapter is to present an overview of the e-Design paradigm and the sample tool environment that supports a cross-functional team in simulating and designing mechanical products concurrently in the early design stage. In turn, better- quality products can be designed and manufactured at lower cost. With intensive knowledge of the product gained from simulations, better design decisions can be made, breaking the aforementioned design paradox. With the advancement of computer simulations, more hardware tests can be replaced by computer simulations, thus reducing cost and shortening product development time. The desirable cost and ECR distributions throughout the product development cycle shown in Figure 1.3 can be achieved through the e-Design paradigm. A typical e-Design software environment can be built using a combination of existing computer-aided design (CAD), computer-aided engineering (CAE), and computer-aided manufacturing (CAM) as the base, and integrating discipline-specific software tools that Introduction to e-Design 5 Figure 1.3: (a) Cost/ECR versus e-Design cycle time; (b) product knowledge versus e-Design cycle time. are commercially available for specific simulation tasks. The main technique in building the e-Design environment is tool integration. Tool integration techniques, including product data models, wrappers, engineering views, and design process management, have been developed (Tsai et al. 1995) and are described in Design Theory and Methods using CAD/CAE, a book in The Computer Aided Engineering Design Series. This integrated e- Designtoolenvironmentallowssmallandmid-sizecompaniestoconductefficientproduct development using the e-Design paradigm. The tool environment is flexible so that additional engineering tools can be incorporated with a lesser effort. In addition, the basis for tool integration, such as product data management (PDM), is well establishedincommercialCADtoolsandsonowheelneedstobereinvented.Thee-Design paradigm employs three main concepts and methods for product development: • Bringing product performance, quality, and manufacturing cost for design considerations in the early design stage through virtual prototyping. 6 Chapter 1 • Supporting design decision making through a quantitative approach for both concept and detail designs. • Incorporating product physical prototypes for designverification and functional tests via rapid prototyping and CNC machining, respectively. In this chapter the e-Design paradigm is introduced. Then components that make up the paradigm, including knowledge-based engineering (KBE) (Gonzalez and Dankel 1993), virtual prototyping, and physical prototyping, are briefly presented. Designs of a simple airplane engine and a high-mobility multipurpose wheeled vehicle (HMMWV) are briefly discussed to illustrate the e-Design paradigm. Details of modeling and simulation are provided in later chapters. 1.2 The e-Design Paradigm As shown in Figure 1.4, in e-Design, a product design concept is first realized in solid model form by design engineers using CAD tools. The initial product is often established based on the designer’s experience and legacy data of previous product lines. It is highly desirable to capture and organize designer experience and legacy data to support decision making in a discrete form so as to realize an initial concept. The KBE (Gonzalez and Dankel 1993) that computerizes knowledge about specific product domains to support design engineers in arriving at a solution to a design problem supports the concept design. Inaddition,aKBEsystemintegratedwithaCADtoolmaydirectlygenerateasolidmodel of the concept design that directly serves downstream design and manufacturing simulations. Figure 1.4: The e-Design paradigm. Introduction to e-Design 7 With the product solid model represented in CAD, simulations for product performance, reliability, and manufacturing can be conducted. The product development tasks and the cross-functionalteamareorganizedaccordingtoengineeringdisciplinesandexpertise.Based on a centralized computer-aided design product model, simulation models can be derived with proper simplifications and assumptions. However, a one-way mapping that governs changes from CAD models to simulation models must be established for rapid simulation model updates (Chang et al. 1998). The mapping maintains consistency between CAD and simulation models throughout the product development cycle. Product performance, reliability, and manufacturing can then be simulated concurrently. Performance, quality, and costs obtained from multidisciplinary simulations are brought together for review by the cross-functional team. Designvariablesdincluding geometric dimensions and material properties of the product CAD models that significantly influence performance, quality, and costdcan be identified by the cross-functional team in the CAD productmodel.Thesekeyperformance,quality,andcostmeasures,aswellasdesignvariables, constituteaproductdesignmodel.Withsuchamodel,asystematicdesignapproach,including aparametricstudyforconceptdesignandatrade-offstudyfordetaildesign,canbeconducted to improve the product with a minimum number of design iterations. The product designed in the virtual environment can then be fabricated using rapid prototyping machines for physical prototypes directly from product CAD solid models, without tooling and process planning. The physical prototypes support the cross-functional team for designverification and assembly checking. Change requests that are made at this point can be accommodated in the virtual environment without high cost and delay. The physics-based simulation technology potentially minimizes the need for product hardware tests. Because substantial modeling and simulations are performed, unexpected design defects encountered during the hardware tests are reduced, thus minimizing the feedbackloopfordesignmodifications.Moreover,theproductionprocessissmoothsincethe manufacturing process has been planned and simulated. Potential manufacturing-related problems will have been largely addressed in earlier stages. A number of commercial CAD systems provide a suite of integrated CAD/CAE/CAM (cid:3) capabilities (e.g., Pro/ENGINEER and SolidWorks ). Other CAD systems, including (cid:3) CATIA andNX,supportoneormoreaspectsoftheengineeringanalysis.Inaddition,third- party software companies have made significant efforts in connecting their capabilities to CADsystems.Asarepresentativeexample,CAEandCAMsoftwarecompaniesworkedwith SolidWorks and integrated their software into SolidWorks environments such as (cid:3) CAMWorks . Each individual tool is seamlessly integrated into SolidWorks. Inthisbook,Pro/ENGINEERandSolidWorks,withabuilt-insuiteofCAE/CAMmodules, are employed as the base for the e-Design environment. In addition to their superior solid 8 Chapter 1 (cid:3) modelingcapabilitybasedonparametrictechnology(Zeid1991),Pro/MECHANICA and SolidWorks Simulation support simulations of nominal engineering, including structural and thermal problems. Mechanism Design of Pro/ENGINEER and SolidWorks Motion support motion simulation of mechanical systems. Moreover, CAM capabilities implemented in CAD, such as Pro/MFG (Parametric Technology Corp., www.ptc.com), and CAMWorks, provide an excellent basis for manufacturing process planning and simulations. Additional CAD/CAE/CAM tools introduced to support modeling and simulationofbroaderengineeringproblemsencounteredingeneralmechanicalsystemscan be developed and added to the tool environment as needed. 1.3 Virtual Prototyping Virtualprototypingisthebackboneofthee-Designparadigm.Aspresentedinthischapter, VP consists of constructing a parametric product model in CAD, conducting product performance simulations and reliability evaluations using CAE software, and carrying out manufacturing simulations and cost estimates using CAM software. Product modeling and simulationsusingintegratedCAD/CAE/CAMsoftwarearethebasicandcommonactivities involvedinvirtualprototyping.However,asystematicdesignmethod,includingparametric study and design trade-offs, is indispensable for design decision making. 1.3.1 Parameterized CAD Product Model A parametric product model in CAD is essential to the e-Design paradigm. The product model evolves to a higher-fidelity level from concept to detail design stages (Chang et al. 1998). In the concept design stage, a considerable portion of the product may contain non-CAD data. For example, when the gross motion of the mechanical system is sought the non-CAD data may include engine, tires, or transmission if a ground vehicle is beingdesigned.Engineeringcharacteristicsofthenon-CADpartsandassembliesareusually described by engineering parameters, physics laws, or mathematical equations. This non-CADrepresentationis oftenaddedtotheproductmodel inthe conceptdesignstagefor acompleteproductmodel.Asthedesignevolves,non-CADpartsandassembliesarerefined into solid-model forms for subsystem and component designs as well as for manufacturing process planning. Aprimarychallengeinconductingproductperformancesimulationsisgeneratingsimulation modelsandmaintainingconsistencybetweenCADandsimulationmodelsthroughmapping. Challenges involved in model generation and in structural and dynamic simulations are discussed next, in which an airplane engine model in the detail design stage, as shown in Figure 1.5, is used for illustration. Introduction to e-Design 9 Figure 1.5: Airplane engine model: (a) CAD model and (b) model tree. Parameterized Product Model A parameterized product model defined in CAD allows design engineers to conveniently explore design alternatives for support of product design. The CAD product model is parameterized by defining dimensions that govern the geometry of parts through geometric features and by establishing relations between dimensions within and across parts. Through dimensions and relations, changes can be made simply by modifying a few dimensional values. Changes are propagated automatically throughout the mechanical product following the dimensions and relations. A single-piston airplane engine with a change in its bore diameter is shown in Figure 1.6, so as illustrating change propagation through parametric dimensionsandrelationships.Morein-depthdiscussionofthemodelingandparameterization oftheengineexamplecanbefoundinProductDesignModelingusingCAD/CAE,abookin The Computer Aided Engineering Design Series. Analysis Models For product structural analysis, finite element analysis (FEA) is often employed. In addition to structural geometry, loads, boundary conditions, and material properties can be convenientlydefinedintheCADmodel.MostCADtoolsareequippedwithfullyautomatic meshgenerationcapability.ThiscapabilityisconvenientbutoftenleadstolargeFEAmodels with some geometric discrepancy at the part boundary. Plus, triangular and tetrahedral elements are often the only elements supported. An engine connecting rod example meshed using Pro/MESH (part of Pro/MECHANICA) with default mesh parameters is shown in