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A Feature-Based Engineering Methodology for Cyclic Modeling and AnalysisProcesses in Plastic Product Development

Md M. Uddin1 and Yongsheng Ma2

1University of Alberta, mdmoin@ualberta.ca2University of Alberta, yongsheng.ma@ualberta.ca

ABSTRACT

Developing a high quality plastic part must cyclically check against required product functionality,structural stability, moldability, and cost effectiveness. Information modeling and managing asso-ciations among multiple engineering aspects is essential to maintain engineering consistency. Afeature-based methodology is introduced here to facilitate cyclic processes involved in product devel-opment. The methodology starts with building product specification model based on specificationfeatures that enable capturing design intention and common product information at the onset of newproduct development. New feature types are introduced for information modeling of related engi-neering aspects. Then the methodology is elaborated with an example for iterative design evolvementthrough feature modifications based on CAE analyses.

Keywords: feature-based, cyclic modeling, performance analysis, injection molding.

1. INTRODUCTION

Due to globalization and rapid technological changes,modern enterprises are challenged for developinghigh quality products with innovative features at low-est cost in shortest time-to-market. Therefore productdesign and development methodologies become moreimportant than ever for companies to gain competi-tive advantages in marketplace. Generally, the devel-opment of a product undergoes several phases in itslifecycle including customer requirements analysis,conceptual design, detail design, structural analysis,manufacturability checking, process planning, manu-facturing, quality inspection and so on [18,21]. Vari-ous engineering aspects are supported with separatecommercial computer aided tools such as computeraided design (CAD), engineering (CAE), process plan-ning (CAPP), manufacturing (CAM), inspection (CAI)etc. It is the expectation that with those tools, design-ers and engineers can carry out different engineeringactivities efficiently for the realization of the endproduct [25]. The reality is that many of these engi-neering aspects are inter-related and mutually con-straining. Some parameters from an earlier stage maybe used as input parameters for generating productmodel in a later stage. If any modification is intro-duced based on any one aspect, such as product per-formance assessment, the inter-dependent product

models need to be updated to ensure engineeringprinciple and design consideration consistency acrossall engineering aspects [12,13]. The iterative design-analysis-redesign cycles among engineering aspectshence become unavoidable during product devel-opment process in a concurrent and collaborativeenvironment.

Injection molding parts are increasingly useddue to the material performance-cost advantageswith automated net-shape manufacturing process andrelatively complex geometries. However, designingplastic parts is a complex and tedious job involv-ing many modeling and analysis cycles for count-ing considerations from other downstream productengineering aspects. It is imperative to coherentlycheck the designed part meets functional require-ments, strength criteria under different loading sce-narios, moldability concerns, and cost effectiveness[15]. Therefore, information modeling for associa-tions among related engineering aspects is essen-tial to maintain product information consistency inthe cyclic design evolvement. A literature survey(described in section 2) carried out in this regardreveals that although many researchers have doneconsiderable works in product information sharingand integration, in-depth research is still requiredfor product performance-based design enhancement,

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capturing multi-facet engineering intents in thedesign process, and associating information acrosssoftware applications.

This research work is focused to developing afeature-based product engineering methodology inorder to facilitate cyclic processes involved amongengineering aspects during the development of aninjection molding plastic product. The methodol-ogy starts with building product specification modelbased on specification feature that enables capturingdesign intentions and common product informationat the onset of new product development. Then theemphasis is on feature-based associative informationmodeling of the iterative process and design enhance-ment modifications based on product performanceassessment.

The following sections are organized as fol-lows. Section 2 discusses related research workscarried out in cyclic design and analysis pro-cesses in product development. The framework ofthe proposed feature-based methodology and itscomponents for cyclic design evolvement based onfunctional and structural requirements evaluation hasbeen described in section 3. Section 4 illustrates themethodology for design enhancement through struc-tural feature modifications based on performanceanalysis with an industrial case study. Section 5 enu-merates conclusions and future research works to becarried out in cyclic process modeling for more auto-mated information flow among engineering aspects.

2. RELATED WORKS

Cyclic design processes for injection molding plasticpart involve collective considerations among multipleengineering aspects such as CAD modeling, struc-tural analysis, molding simulation, and cost estima-tion. Taking into account the effects of downstreamproduct aspects early in design stage helps reducethe number of costly design changes at later stages[18]. It is important to recognize that the ease ofpart manufacturability, structural stability, toolingrequirements and product cost will eventually bedetermined by design of the product [15]. There-fore, product and process information sharing andintegration among engineering aspects in the cyclicdesign processes are essential for product modelsconsistency and minimizing costly design changes.

Many research efforts have been made to shareand exchange product and process informationamong different application models to enhancethe integration among product engineering tools.Such research efforts in engineering informaticscan be categorized as four approaches, i.e. usingneutral-format data for file exchange, develop-ing integrated product development environments,meta-data based product engineering modeling, andmulti-facet feature-based engineering integration.

Using neutral standard formats such as IGES, STEP,DXF, and SAT for representing product data havebeen developed to overcome the issue of data inter-operability among heterogeneous CAx systems [16].However, transferring product model data back andforth among separate CAD modeling and analysis sys-tems becomes a tedious and time-consuming processof modifying design model, idealizing, re-meshingand reapplying boundary conditions in cyclic design-analysis process [9]. More seriously, this approachlacks of robustness of engineering consistency bycausing information loss during data translation pro-cesses and generates poorly-defined geometric enti-ties due to the differences of modeling tolerancesamong geometric modelers [7].

An integrated environment for product develop-ment accommodates geometric modeling, engineer-ing analyses and/or other modeling capabilities andeliminates the compatibility issue of geometry mod-eling kernel [23]. Therefore, researches have beenfocused on working with native CAD geometries forthe creation of CAE meshed model [5]. An early ideaon CAD-FEA integration was proposed by Arabshahiet al. [1] where he emphasized for automation ofCAD-FEA transformation and FEA model preparationactivities. Shephard et al. [19] proposed a simulation-based design approach which has four technical com-ponents that integrates existing CAD and CAE tools byenhancing simulation data management and adaptiveimprovement of simulation model. Lee [10] describedCAD/CAE-integrated approach using multi-resolutionand multi-abstraction modeling that creates a singlemaster model containing all of the geometric modelsrequired for both CAD and CAE. Smit et al. discussedthe idea of multiple-view feature modeling approachfor creating and associating analysis view along withother product views [20]. Hamri et al. proposed a newshape representation technique called mixed shaperepresentation that supports both B-Rep and polyhe-dral representation for creating CAD and CAE models[7]. Nowadays, almost all of the current major com-mercial CAx software packages such as Siemens NX,CATIA, Pro/E, and SolidWorks are being developedalong this direction. Although integrated packagescan host different engineering modules together, theintegration is achieved primarily on lower-level geo-metric entities. Higher-level feature information isstill missed in the process of transforming a CADmodel into the corresponding CAE model. Besides,since analyst has different views of the same prod-uct model than designer, he needs to modify a lotof the designer’s model to prepare it for the analysispurpose.

In order to support different product lifecycleaspects with commonly shared high-level informa-tion, researches on meta-data product informationmodeling for engineering processes have been con-ducted. The goal is to develop a base informa-tion model that facilitates achieving integration of

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design, analysis and other engineering activities atinformation level. In the past decade, product datamanagement (PDM) systems are developed to clusterengineering files for different product developmentphases, projects, configurations, and relevant depen-dencies at meta-attributes level [11], but they do notsolve data level integration issues. The researchersat national institute of standards and technology(NIST) [4] have developed a base-level product model,known as core product model (CPM), that is generic,simple, open, non-proprietary, extensible, and inde-pendent of any specific product development process.CPM is reported to be capable of capturing engi-neering context commonly shared in product devel-opment activities. CPM has further extended andmany researchers have based their works on CPM.Further, Sudarsan et al. [21] proposed a productinformation modeling framework to support the fullrange of product lifecycle management (PLM) infor-mation needs. Within the framework, it also definesa design-analysis integration model as part of thePLM concept. Product engineering information modelenhances product information consistency amongengineering aspects. However, it does not itself inte-grate separate engineering applications or enhanceiterative design evolvement. To be more realisticallyfeasible, Gujarathi et al. [6] developed a common datamodel (CDM) containing all required parametric infor-mation for both CAD modeling and CAE analysis forCAD/CAE parametric integration.

Although the concept of feature was initially asso-ciated to geometries of a part, its use has beenexpanded to other applications in different stages ofproduct lifecycles due to its flexibility and extensi-bility [13]. Shah states that features represent engi-neering meaning of the geometry of a part or anassembly, or represent a carrier of product informa-tion that may aid design or communication betweendesign and manufacturing or between other engi-neering tasks [17]. Vandenbrande defines features asregions or an object that are meaningful for a specificactivity or application [22]. All of the above definitionsrelate features back to shape aspects of a product.Thus features have been used extensively for informa-tion modeling of many product engineering aspectssuch as functional design, detailed design, assemblydesign, process planning, and machining. Hoffmannet al. [8] proposed a three-level multi-view semanticmodel for product feature description for enhancingsemantic integrity of feature information through-out product development. Since features carry non-geometric information along with geometric data,they are also being used for information modelingof new product engineering areas [2]. Feature-basedtechnologies such as feature extraction, conversionor feature association enhances integrating productdesign stage with other downstream lifecycle stages.Many feature-based integration efforts have beenreported [3,12,24]. Ma emphasizes on the generic

feature definition based unified feature scheme forachieving feature-based interoperability among engi-neering applications [14]. Since feature serves as aninformation unit having engineering meaning, featureconcepts can be expanded to model other applicationareas such as cost estimation etc and to exchangehigh-level engineering information along with geo-metric data across applications.

However, the reported research works have notthoroughly addressed cyclic modeling and analy-sis processes among multiple engineering aspects.Current research approaches do not support effec-tively capturing engineering intentions behind aproduct concept generation such as customer require-ments, required functions, technical specifications,and performance criteria in the modeling environ-ment. Design intentions and high-level product infor-mation, such as loading conditions, load amounts andanalysis meta data, cannot be shared across applica-tions. High-level feature information gets lost in thetransformation process from design model to analy-sis model. Existing modeling and analysis tools areusually good at data processing and image generation.The application tools have limitations in evaluationof product performance. Therefore, in this work, amethodology has been proposed that can enhance theiterative product design process capturing high-levelcommon product information as specification featureand making design improvement through structuralfeature modification for compliance to functional andstrength requirements.

3. FEATURE-BASED CYCLIC MODELING ANDANALYSES FOR PRODUCT DEVELOPMENT

3.1. Framework of Proposed Feature-BasedEngineering Methodology

The methodology starts with building product speci-fication model that facilitates capturing design inten-tions and commonly shared product informationsuch as customer requirements, required functions,technical specifications, engineering knowledge, per-formance criteria, and their relationships at thebeginning of new product development. Informationabout design process, structural analysis, moldingprocess and cost estimation necessary for injectionmolding product development is accumulated withseparate product and process information files. Engi-neering features considering their types, attributesand relationships are identified by investigating andanalyzing information stored in product and processinformation files. Feature-based information modelsfor engineering aspects are then developed by cre-ating feature hierarchy for each aspect. For exam-ple, design feature hierarchy is created to representconceptual and detailed CAD model development,and CAE feature hierarchy for representing structural

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engineering analysis process. Feature instances arecreated by taking their parameter values from prod-uct and process data files for automated updatingof product models if parameter values in the datafiles are modified. Fig. 1 outlines the framework ofthe proposed feature-based engineering methodologyfor cyclic modeling and analysis processes involvingmultiple engineering aspects.

CAD modeling of a product is progressively car-ried out to serve the required product functionscaptured from the product specification model. CADmodels of the product serves as the master modelsand newly introduced features and product specifi-cation model are connected with it using API func-tions. Product performance based on the CAD modelsis then analyzed. For example, with our example

Fig. 1: Framework of feature-based engineering methodology for cyclic modeling and analyses.

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(a) (b)

Fig. 2: An example plastic part design.

plastic part, i.e. an oil-drilling tube transport support-ing piece as shown in Fig. 2, its structural rigidity,manufacturability and updated cost estimation areevaluated with different computer tools. The anal-ysis results are assessed against predefined crite-ria for functionality, strength and moldability. Suchcriteria are managed by product performance eval-uation process. Based on the evaluation feedback,CAD models or simulation models are modified itera-tively through feature modifications. Existing featureattributes are then updated or new structural fea-tures are created for the iterative design enhance-ment. Information sharing and dependency relationsamong CAD model and analysis models are associatedexplicitly as cross-applications constraint relations.If any modification is done in inter-related engineer-ing models, feature parameters would be updatedaccordingly to generate updated product engineeringmodels. The detailed discussion on individual com-ponents of the framework is given in the followingsections.

3.2. Product Specification Model

For a typical product series, the design specificationstructure can be generically abstracted into a commondata structure with changing values of them for differ-ent instances. Such specification data can be formal-ized into software interpretable variables and sharedamong all of the engineering aspects for establishingengineering design criteria. Therefore, these specifica-tions should be modeled as a common data file inde-pendent of any CAx system. Design evolvement andanalysis evaluation results should be organized anddirected towards fulfilling customer requirementsand required functions through measureable productor part performance criteria. Generally, for many com-panies, such high-level specification variables are notcaptured at the onset of product development in acomputer interpretable manner.

Therefore, a product specification model is pro-posed to capture all of the information gathered andcreated at product idea generation stage based on

product specification feature. A specification modelconsists of a set of specification features. Fig. 3illustrates the product specification feature seman-tic definition and its composition. The proposedspecification feature data structure is defined asa class according to the object-oriented softwareengineering approach; it consists of other extendedlower level features, such as those modeled forcustomer needs, application requirements, requiredfunctions, performance expectation, material require-ment, and performance measures. For example, cus-tomer need features are mapped to capture thedescription of customer demands and preferences.Engineering knowledge is applied and implementedwithin the aforementioned features and the asso-ciated constraints. They could be specific in realworld application to reflect the expert knowledge inthe field, the best practice of the company, lessonslearned from past cases, engineering calculationsused in the product design, and relevant regulatorycodes.

From customer needs and engineering knowledge,customer requirements are documented which arecaptured as customer requirements feature. Thenrequired product functions are derived based on engi-neering knowledge and customer requirements andcaptured as function feature. Required functions arethe pillars of the foundation for initializing concep-tual product design. Conceptual design of a partshould always check against the attributes of requiredfunction features to serve the product’s intended use.All of different performance criteria for structuralanalysis, molding simulation and cost estimation aregathered as performance features so that the ana-lysts know beforehand what the expectations andmeasures are, and what to achieve in the analysisprocess. Potentially, inter-feature constraints can bemodeled and built into feature constraints to cap-ture the intricate engineering dependencies. This pro-posed methodology emphasizes on capturing designintentions and specifications as early as possible; andthe feature contents also serve as a common sourceof information and ensure information consistencyacross applications.

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-ProdSpecID-CustomerNeeds-CustomerRequirements-RequiredFunctions-TechSpecs-Materials-Performance-...

ProdSpecFeature

-CN_ID : int-CN_Description : string-...

CusNeedsFeature

-RF_ID : int-RF1 : string-RF2 : string-...

ReqFuncFeature

-TS_ID : int-TS1 : string-TS2 : string-TS3 : string-...

TechSpecsFeature

-PF_ID : int-FactorOfSafety : long-maxStress : long-maxDeformation : long-maxMoldingCycle : long-maxWarpage : long-...

PerformanceFeature

-LS_ID : int-Scenario1 : string-Load1 : long-Scenario2 : string-Load2 : long-...

LoadingScenariosFeature

-CR_ID : int-CR1 : string-CR2 : string-CR3 : string-...

CusReqFeature

-partMaterial : string-moldBaseMaterial : string-moldInsertMaterail : string-...

MaterialFeature

-EK_ID : int-expertKnowledge : string-bestPractices : string-lessonsLearned : string-enggCalculations : string-regulatoryCodes : string-...

EnggKnowFeature

-MC_ID : int-maxWallThickness : long-minDraft : long-minFilletRadius : long-...

MfgConsiderationFeature

1

*

1

*

1

*

1

*

1

*

-TS_ID : int-KP1 : string-KP2 : string-KP3 : string-...

KeyParametersFeature

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composition

association

Fig. 3: Product specification model.

3.3. Feature-Based Information Modeling ofMultiple Engineering Aspects

Features have the flexibility to capture both geometricand non-geometric engineering information charac-teristics for engineering modeling. This advantage canbe once again demonstrated by introducing the neces-sary new feature types to encapsulate attributes andbehaviors of related engineering consideration of dif-ferent aspects such as structural analysis, moldingsimulation and cost estimation. Feature informationrelated to product design, strength analysis, mold-ing process and cost estimation can be organizedin separate data storages. For example, the func-tional modeling method in CATIA has been used asa successful feature-based tool. In our preliminaryresearch, separate feature data files are used. In thenext paragraphs, from the feature modeling experi-ence accumulated so far, some new feature types and

their attributes have been identified for managing thecyclic plastic product design and analysis processes.

Fig. 4 shows a partial representation of feature-based information model of part design, CAE analysis,molding simulation and cost estimation. Product Fea-ture acts as the top parent class and feature modelsof different engineering aspects are created with theinheritance relationship with the product feature. Asa child class, Product Specification Feature is createdto contain hierarchical technical specifications andkey parameters related to both the set of customerrequirement features and the set of design features.Design features have been classified as conceptualfeatures and detailed design features. Conceptualfeatures are those associative features created thatreflect the function features in the specification modelas discussed in the previous section. Such conceptualfeatures are also linked to customer requirements

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-ProdID : int-ProdName : string-Customer : string-...

ProductFeature

-CF_ID : int-CF_Name : string-...

ConceptualFeature

-SF_ID : int-SF_Name : string-...

StructuralFeature

-CAEF_ID : int-CAEF_Name : string-...

CAEFeature

-MF_ID : int-MF_Name : string-...

MoldingFeature

-CEF_ID : int-CEF_Name : string-...

CostFeature

-RF_ID : int-RF_Name : string-BaseThickness : long-TopThickness : long-DraftAngle : long-Height : long

RibFeature

-GF_ID : int-GF_Name : string-BaseThickness : long-Length : long-DraftAngle : long

GussetFeature

-BF_ID : int-BF_Name : string-Height : long-ExternalDia : long-InternalDia : long-DraftAngle : long

BossFeature

-DF_ID : int-DF_Name : string-...

DetailedFeature

-ChF_ID : int-ChF_Name : string-...

ChamferFeature

-DF_ID : int-DF_Name : string-...

DraftFeature

-FF_ID : int-FF_Name : string-...

FilletFeature

-ID : int-LoadType : string-LoadAmount-ConstraintType-...

BoundaryFeature

-ID : int-Name : string-AnalysisType : string-...

AnalysisFeature

-ID : int-Material : string-Young'sModulus-PoissonRatio-MassDensity-TensileStrength-...

MaterialFeature

-ID : int-MeshType : string-ElementSize-...

MeshFeature

-ID : int-Name : string-...

UserInputFeature

-ID : int-Name : string-...

EstimationFeature

-ID : int-Name : string-...

FeedSystemFeature

-ID : int-Name : string-...

MoldMfgFeature

-ID : int-Name : string-...

MoldMaterialFeature

-ID : int-Name : string-...

EjectionFeature

-ID : int-Name : string-...

MoldBaseFeature

-ID : int-Name : string-...

MoldInsertFeature

-TF_ID : int-TF_Name : string-...

TransitionFeature

-ProdSpecID-CustomerNeeds-CustomerRequirements-RequiredFunctions-TechSpecs-Materials-Performance-...

ProdSpecFeature

-ID : int-CADPart-IdealizedPart-PolyhedralPart

CAEGeomFeature

-ID : int-MeltTemperature : long-MoldTemperature : long-InjectionPressure : long-FillingTime : long-PackingTime : long-CuringTime : long-V/PSwitchOver : long-EjectionTemp

ProcessFeature

-ID : int-MoldMaterial : string-MoldInsert : string-MoldOpenTime : long

MoldFeature

-ID : int-Name : string-InletTemperature : long-FlowRate : long-Pressure : long

CoolingFeature

-ID : int-Name : string-ClampingForce : string-MachineSize : long

MachineFeature

-ID : int-SimulationType : string-MeshType : string

SimulationFeature

Fig. 4: Partial feature-based information modeling of multiple engineering aspects.

which are mapped to measure the customer sat-isfaction levels in product specification model. Asshown in Fig. 2(a), the conceptual features give thehard-constrained outer shell for an injection mold-ing part; the preliminary design is shown in Fig. 2(b).Then detailed design features are added progres-sively based on strength evaluation by CAE analysis.Detailed features are grouped into structural featuresand transition features. Structural features such as

ribs, gussets and bosses are added for structuralenforcement to the initial part shell of a plastic part.Transition features such as fillet, chamfer, draft etcare not introduced to the design model until thedesign becomes structurally strong enough to sustainloading conditions in different usage scenarios.

When structural analyses are carried out with CAEtools, e.g. Siemens NX Nastran for strength evalu-ation. The analysis information can be modeled as

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CAE features such as CAE geometry feature, materialfeature, mesh feature, analysis feature and boundaryfeature. CAE geometry feature stores pointer to theCAD solid model, idealized part and polyhedral partwhich is suitable for carrying out CAE analysis. Inorder to plan for injection molding and the relatedsimulation process, molding features such as moldingprocess setup parameter feature, mold feature, injec-tion machine feature, simulation feature and coolingfeature have been created to represent necessarymolding process details. Similarly, cost feature and itsderived features can be created to represent differentmodule costs, constraints, and their correspondingestimation and evaluation methods, e.g. those compo-nents involved in mold cost estimation process. Moldcosting features include mold base, feed system, ejec-tion system etc. They are created to enable modularmold cost estimation process. The data input for all

feature parameters can be stored in spreadsheets andapplication models can be linked with spreadsheetsusing API functions for updating the models with thelatest parameter values.

3.4. Product Performance Evaluation Method

As the designer modeling a product, he needs toevaluate the model against predefined performancecriteria for its functionality, structural rigidity andmoldability. Fig. 5 depicts the cyclic verification pro-cess of design models based on functional evaluationand strength analysis, and feedback loops for iterativedesign modifications. The performance criteria to besatisfied by a conceptual design are captured as per-formance features in product specification model andderived from customer requirements and engineering

Required Functions

Key Parameters & Constraints

Conceptual Design Features

Structural Design Features

Conceptual CAD Model

Detailed CAD Model

CAE FeaturesCAE Analysis

Model

Static Loading Analysis

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Does the model serves

all required functions?

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Is factor of safety

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Drop-test Analysis

Is factor of safety

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Customer Requirements

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Fig. 5: Iterative design verification and modifications with functional and strength evaluations.

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knowledge. The designer adds conceptual features toembody the required functions collectively in designmodel. When all of the required functions have beenincorporated into the design, the conceptual partdesign is consolidated into a preliminary version.

With the completion of the conceptual design,the detailed design phase starts with more specificCAE analyses to verify different engineering con-straints, such as the structural stability of the plasticpart design in predefined loading scenarios whichcover static loading conditions, dynamic vibration,dropping-test, etc. Usually, static loading conditionsare checked first. The detailed design model needsto be prepared for CAE analyses. Capturing anal-ysis information as CAE features as mentioned insection 3.3 helps reducing repetitive tasks of remesh-ing, reapplying boundary conditions etc. CAE analysisresults are evaluated against predefined performancecriteria, such as maximum stress, maximum defor-mation, and factor of safety, which are containedin performance features in the product specificationmodel. If any performance criterion is not met, modi-fications for the design are warranted. For plastic partdesign, adding structural rib features is commonlypracticed. Interactive trial and error for choosing rightnumber of ribs as well as their patterns is necessary.

If the design exhibits sufficient strength understatic loading, then vibrational loading conditions arechecked. With the satisfactory results at this stage,the structural stability is then tested under drop-testscenarios. If a design possesses sufficient strength inall loading scenarios, then the design verification loopends there and the design is finalized.

4. ITERATIVE DESIGN EVOLVEMENT THROUGHSTRUCTURAL FEATURES - A CASE STUDY

A case study for design evolvement through struc-tural feature modifications based on CAE evaluationhas been carried out for a plastic part which wasintended to replace a traditional wooden support fortransporting oil-drilling tubes as shown in Fig. 2 withHDPE. Tensile strength of HDPE used was 27 MPa andfactor of safety (FoS) was chosen as 1.5 in all loadingscenarios. With the company’s preliminary design asshown in Fig. 2(b), the optimization of the design wasrequired; because the material use was high (2.05 lbper part), and the vibration and dropping tests werenot passed. FoS of the initial design in static loading,vibration and dropping were found to be 2.3, 1.3 and1.1 respectively.

The product redevelopment process starts withcapturing customer requirements, performance eval-uation criteria, required product functions, technicalspecifications and key design parameters as speci-fication features to construct product specificationmodel. The attributes and their parameter values ofthe specification features, design features, CAE fea-tures, molding features and cost features have been

captured in spreadsheet files in this conceptual stageof the research. Inter-dependent relationships amongdifferent features have been realized by embeddingthe relationships in spreadsheet cells. For exam-ple, technical specifications are dependent on cus-tomer requirements. If any parameter of customerrequirements feature is changed, the correspondingparameters of technical specification feature will beautomatically updated in the spreadsheet. On theother hand, design and analysis models are linkedto their corresponding spreadsheets. The updatingof product models is done manually by importingspreadsheets values from CAD/CAE environment. Asthe methodology will be implemented as a softwareprototype, API functions will be used to automate theupdating process.

The feature-based information model serves as theguiding framework for the cyclic processes involvedto derive the final satisfactory design. Since the designof a plastic part cannot be started with solid volumedue to long cooling time and excessive material use,making the outer shell-like structure first and thenadding structural features to reinforce the design isthe best practice. Fig. 6(a) shows a partial view of con-ceptual design feature parameters which are linkedto CAD model to realize the outer functional inter-facing shell to match the tube profile shapes. Theresulted model based on conceptual features is shownin Fig. 6(b). Next, the locking features and the innerhole for strapping the tube pile on a trailer are addedas functional features in the conceptual design asshown in Fig. 6(c). The output is a hard-constrainedouter shell of a plastic part. Obviously, the part designshould possess enough strength to withstand indus-trial loading conditions. The design model is then ana-lyzed for its structural stability under static loading,vibration and drop-test scenarios.

Therefore, the intermediate conceptual CADmodel is checked by strength evaluation, i.e. FEA withNX Nastran. The static loading conditions are shownin Fig. 6(d), and the result is shown in Fig. 6(e). It doesnot meet the basic strength criteria. As the designevolves, different configurations of structural rib fea-tures are added semi-automatically and optimizedaccording to FEA feedback to reinforce the design.Note that too much use of ribs increase material costand hampers creating cooling channels in the mold.If a design possesses sufficient FoS under static load-ing scenario, it is then checked for vibrational loadingconditions when transporting in a stack-up pile. Ifthe design fails to meet predefined FoS, the detaileddesign is modified by varying the number and patternof rib features.

One of the intermediate configurations is shownin Fig. 6(f) which uses vertical ribs. It satisfiedstatic and vibrational loading requirements but failedin dropping test simulation. The locations of thehighly stressed area in the part design were observedand different combinations of rib patterns wereincorporated to the design to make it stronger.

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(a) (b) (c)

(d) (e) (f) (g)

Fig. 6: Iterative design model evolvement through structural feature modifications: (a) a partial view of concep-tual design feature parameters; (b) the initial functional interfacing shell; (c) the intermediate conceptual partdesign; (d) the static loading conditions; (e) an intermediate static CAE analysis result; (f) a detailed design model;(g) final design satisfying all evaluations.

The final design is shown in Fig. 6(g) which usescombination of rib patterns and possesses a factor ofsafety higher than 1.5 in all loading conditions. Setsof vertical ribs, horizontal ribs and diagonal ribs withvarying angular orientations were used to reinforcethe design, while consuming 1.99 lb of material. Thefinal design satisfies all the functional and engineer-ing requirements. At the same time, amount of mate-rial is reduced by 2.9% than the preliminary companydesign, as shown in Fig. 2(b). Although consumingless material is the result of interactive design insteadof the direct consequence of feature-based approach,however, the feature-based cyclic design-analysis pro-cess helps to track and enable rib feature changes ina systematic manner which results in reduced dataassociation time by the designer, and hence shortensproduct development time.

5. CONCLUSIONS AND FUTURE WORKS

This paper introduces a cyclic plastic part design andanalysis engineering management methodology withthe advanced feature-based approach. The benefitof this approach is that the data interdependenciescan be managed in a more robust manner. It cap-tures all the related product and process information

in the feature data structure, such as specificationfeatures, conceptual features, CAE features, mold-ing features and cost features. The relationshipsamong inter-dependent features can be defined inthe feature-based information model for multipleaspects, and thus information consistency acrossengineering models can be ensured. In the authors’experience, during the iterative design and FEA anal-ysis cyclic process, the consistent design is ensuredto fulfil pre-defined strength criteria and customerrequirements. A case study for iterative design modelevolvement is given based on structural performanceanalysis. Currently, a prototype software implement-ing the methodology is underway by using NX APIfunctions; the details, such as data exchange automa-tion, can be expected in the next paper. The expe-rience we have had proves that the methodologybased on feature concepts, ranging from modeling,implementation and tracking of the cyclic processesbetween CAD modeling and other engineering analy-sis aspects, ensures capturing design intentions earlyin the process, and guides the design modificationstowards fulfilling preset criteria. The future work willinclude mapping CAD and CAE features and proto-typing a functional module to verify the scalabilityand the effectiveness of the proposed methodologywith a more cases. Then, associative modeling of

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specification, design, CAE and cost features is to befurther investigated for automated change evaluationand propagation.

ACKNOWLEDGEMENTS

The authors would like to acknowledge NSERC’sfinancial support via DISCOVERY and ENGAGE grants.They are also grateful for the technical input providedby Drader Manufacturing Industries Ltd.

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