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Our business case throughout this thesis originates from the product develop- ment domain, i.e., our ontologies, rules, queries and the subjacent methodology are designed and modeled in order to support this area. More precise, our run- ning examples and case studies often refer and relate to an automotive Research & Development (R&D) domain.

Therefore, this section provides basic knowledge about product lifecycles in gen- eral, classifies the (virtual) product development and introduces several primary technical terms.

Figure 2.8 helps to classify various relevant design stages and development pro- cesses in a product lifecycle. The business domain we are interested in is out- lined by a red ellipse, namely, the product development which is implemented by a“Product Development Process”(PDP). Common steps during a PDP are the idea generation, screening, business analysis, concept and embodiment design, prototype (virtual and physical) and market testing, detail design and finally the

Figure 2.8.: The different phases of a product, i.e., the product lifecycle and design work (Birkhofer2011).

product launch preparations. These process phases, especially their stakehold- ers, importance, manifestations, concurrency, dependencies and order, are indi- vidual to a company and several different state-of-the-art PDPs exist. Naturally, a plethora of enterprise divisions, for instance, marketing, R&D and finance, have to cooperate and collaborate in order to create a new product which makes this process even more complex. A universal important process milestone is theStart of Production (SOP) which is the release of a product into production, i.e., the handover between the R&D and production divisions. However, the PDP con- tinues, because stakeholders do post launch evaluations and begin to plan and realize improvements for future product version, i.e., facelifts in the automotive domain, which start a new, pruned and customized PDP.

Nowadays, a lot of IT systems support the PDP andProduct Lifecycle Management (PLM)in general. When these systems support the process extensively, we use the termvirtualproduct development, creationorlifecycle (cf.Figure 2.8) that make use of the discipline ofVirtual Engineering.

Definition 2.3 (Virtual Product Creation)

Continuous IT support during product and production creation with an intense application of simulation, validation and verification techniques on the basis of realistic models. The goal is to attain early product and production knowledge, a premature detection of product properties, as well as a reduction of physical

prototypes (Eigner and Stelzer2009b, trans.).

Definition 2.4 (Virtual Engineering)

Virtual Engineeringis the timely,continuous,interconnected(process view) and

integrated(system view) support of the Product Creation Process (PCP) concern- ingcoordination,assessmentand ascertainmentof the development results of all

partners with the aid of virtual prototypes (Ovtcharova2009, trans.).

Example software solutions supporting or carrying a virtual PDP or even a vir- tualPCP, highlighted by the blue ellipse in Figure 2.8, are authoring tools, solu- tions for simulations and calculations, software for planning and simulating pro- duction and assembling as well as cooperative applications (Eigner and Stelzer

2009b). As the case may be, theComputer Aided Design (CAD)andComputer Aided

Engineering (CAE)tools we describe in this thesis belong to this class. The physi- cal mock-ups and prototypes that cannot be reduced due to regulations or func- tional obstacles, are heavily supported by IT systems or even a hybrid, like Hard- ware in the Loop (HiL), and relate directly to the introducedComputer Aided Test- ing (CAT).

In order to manage these systems, solutions and the necessary data, most impor- tant product data, enterprises utilizeProduct Data Management (PDM) solutions during the PDP and PLM applications during the entire lifecycle, occasionally already supported by ontologies (cf. Matsokis 2010). Because product data of vehicles, vehicle parts and the associated product structure is used during the whole lifecycle by many organization units, they have to be pervasive and stan- dardized. Therefore, they are usually based on theSTandard for the Exchange of Product model data (STEP)(ISO2014, AP 214) in the automotive domain, which is also applied and explained in our method ontology in section 4.6.1.

Developing products virtually bears many advantages in comparison to the con- ventional physical development as depicted in Figure 2.9.

Enterprises that apply virtual development and production commonly benefit in a number of ways, but mainly, the applications of the very cost and time intense

resources time

Virtual

Engineering

Conventional

Development

program start start of production

processes te ch n olo gy methods

Figure 2.9.: Shifting of result critical sub-processes and resources towards early phases of development. According to Eigner and Stelzer (2009b).

physical simulations with real prototypes can be reduced by substituting them with Digital Prototypes (DPs) which in turn leads to a considerably shortened PDP, as illustrated and hence, we have an earlier SOP and market launch (Eigner and Stelzer2009b).

However, this shifting is only feasible with an increased application of new tech- nology, (virtual) methods and resources. As a consequence, our business motiva- tion for this dissertation.

Furthermore, virtual prototypes, often calledDPs, are often cheaper than physi- cal ones, especially when performing lots of crash simulations. Besides, the sim- ulations can be set up, modified, repeated and optimized more simply and their execution time is usually decreased. Moreover, a virtual model can be shared, reused and compared among divisions, suppliers and partners globally and in- stantaneously.

DPsrepresent a virtual, often executable, model of a usually former physical pro- totype. While a model is by definition a pragmatic and reduced mapping to a real system, nowadays, some physical systems are not constructed at all anymore, i.e., they only exist virtually (they are still models, though). The model’s purpose is usually a validation or verification of an assembly’s form, function and behavior

that can be achieved by running sundry simulations, e.g., Finite Element Method (FEM), Multi Body Simulation (MBS) or Computational Fluid Dynamics (CFD). One important term associated with DPs is Digital MockUp (DMU), significant in section 7.3, which represents a 3D model of an optimally complete product – DPs embrace many more facets, i.e., they correspond to a wide range of assem- blies, areas and disciplines of the development, for instance, they involve kine- matics, product structure, electr(on)ics, lighting, sound, driving behavior, me- chanical strength and many more aspects.

Next to these disciplines, the virtual product development includes several other ones, for instance, the application of Virtual Reality (VR) or Augmented Reality (AR).

For further information on DPs and (virtual) product development in general, please resort to this section’s various sources (Ehrlenspiel and Meerkamm2013; Eigner and Stelzer2009c; Ovtcharova2009; Iparraguirre2013; Autodesk2007).