Digital Engineering: Functional Virtual Prototyping (Part 1)
Leading global manufacturers are feeling
increasing pressure to rapidly institute enterprise-wide,
simulation-based design and virtual prototyping practices that can
insure greater product performance and quality at a fraction of both
the time and cost required with traditional build-and-test approaches.
As product complexity increases and competitive product development cycle times are reduced, hardware prototype creation and testing become major bottlenecks to successful new product launches. Due to these bottlenecks, leading global manufacturers are feeling increasing pressure to rapidly institute enterprise-wide, simulation-based design and virtual prototyping practices that can insure greater product performance and quality at a fraction of both the time and cost required with traditional build-and-test approaches.
How can companies make this transition and develop confidence in virtual prototype modeling and simulation? Part one of this two-part article outlines the requirements for successfully implementing virtual prototyping and looks at the technology itself. Part two of the article, to be published in Time-Compression Technologies Volume 5, Number 5, will look further into the virtual prototyping process and will examine how manufacturing companies are utilizing virtual prototyping already to huge advantage.
The current BMW 3-series sedan came to market amidst a flurry of accolades and awards. "Perfection down to the last detail" was an overriding philosophy throughout the design process used to create this latest version of "the Ultimate Driving Machine." According to BMW Magazine1, the development process involved five and a half years, 2.6 million man-hours, 130 hand-made system-level hardware prototypes created at a cost of roughly $350,000 per vehicle, and some 2,400 new components. Anti-lock braking systems, traction-control, advanced multi-link suspension systems, state-of-the art safety systems and a chassis/powertrain combination that operates in perfect unison are just a few of the complex engineering characteristics of this stellar vehicle (see Figure 1).
Based on the rate of change in the automotive industry, it is safe to say that the remarkable standard of excellence set by this BMW 3-series vehicle will be surpassed by many new vehicles within a few years. New vehicles will incorporate more advanced technology so that they ride smoother, react faster, have more pleasing sound qualities, last longer, require less maintenance, protect occupants better, and deliver more value to the customer. Moreover, these new vehicles will be developed in roughly half of the development time of the current 3-series. The cost of producing a system-level hardware prototype will probably not change substantially, but the overall development cost for these new vehicles is projected to plummet along with the development time - but - what will facilitate this remarkable advancement?
The answer is Virtual Prototyping Simulation-based design practices allow product designers, engineers and analysts to more quickly assess form, fit, function and manufacturability of new products throughout concept design, concept refinement, detailed design, release and production. No longer is it necessary to wait months to build a hardware prototype, instrument it, run tests on it and make a small number of expensive modifications to it in order to assess proposed design changes. Instead, participants in the design process are able to construct accurate virtual prototypes in less than a week, exercise the models through hundreds of tests with thousands of variations, and optimize the form, fit, function and manufacturing characteristics at a fraction of the cost of traditional hardware prototype processes (see Figures 2 and 3ab).
A number of questions arise when considering functional virtual prototyping, such as:
- What is required to implement a successful functional virtual prototyping process?
- Why hasn't this been done previously?
- What industry trends are enabling such a transition?
- What are potential pitfalls and limiting factors?
- What are the critical success-factors for a truly effective functional virtual prototyping system?
Traditional CAD/CAM/CAE versus System-Level Virtual Prototyping
Traditional CAD/CAM/CAE practices throughout the 1970s and 1980s
focused on a concept referred to as "art-to-part." Nearly all
engineering software activity was oriented toward the design,
development and manufacturing of higher quality parts. Detailed, 3-D
solid modelers (CAD) allowed for quick part design and understanding of
"form." Finite element software (CAE) made it feasible to perform
detailed meshing and analysis of structural effects, thermal effects
and vibratory characteristics, or "function," of individual parts.
Software aimed at improving "manufacturability" of parts (CAM) provided better control of machine tools, robots, mold procedures, stamping procedures, forging processes, etc. These traditional CAD/CAM/CAE tools and processes were embraced and implemented throughout major industries, including the automotive, aerospace, general machinery and electro-mechanical markets. For the most part, they lived up to their promise of dramatically improving part design. In the automotive industry, for example, automotive suppliers reported a 40 percent reduction in part defects over a recent five-year period. This significant improvement was accompanied by a corresponding drop in development and manufacturing costs attained through successful implementation of better CAD/CAM/CAE tools and processes.
Unfortunately, during the same five-year period that automotive part suppliers were achieving a 40 percent reduction in part defects, the vehicle manufacturers (OEMs) who were using these parts to assemble and market full vehicles experienced only a 20 percent reduction in warranty costs. In some sense, this was a surprise to many OEMs who expected a one-to-one correspondence between part defects and warranty costs. In retrospect, it seems perfectly sensible. Optimal part design rarely leads to optimal system design. For example, when perfectly good brakes are combined with a perfectly good suspension system and a fine chassis, the resulting combination often performs in a less-than-stellar manner. Clearly, the interaction of form, fit, function and assembly of all parts in a product is a major contributor to overall product quality. We may be reaching levels of diminishing return in applying CAD/CAM/CAE technologies to part design. The big opportunity to increase quality and reduce time and cost has now shifted to the system level.
More significant returns on investment can be realized today through the effective use of simulation-based design processes and functional virtual prototyping applied to system-level design. Manufacturers now need a means to quickly assess form and fit of entire assemblies of 3-D solid models comprising a product (Digital Mock-Up [DMU]). They need to be able to assess the operating function of the entire assembled product (Functional Virtual Prototyping), not just the component parts. And they need to investigate the entire manufacturing and assembly of the product (Virtual Factory Simulation), not just the creation of the parts. As global product manufacturers began to realize this fact over the last few years, it was natural for them to look for extensions to their traditional CAD/CAM/CAE systems to address system-level design. Part-focused CAD/CAM/CAE providers hurried to extend their software to address system-level designs with varying levels of success. But simple extensions of part design paradigms to system-level design often lead to impractical software products.
For instance, as designers and engineers tried to construct large assemblies of solid models to facilitate system-level interference detection and virtual fly-through, the rendering performance of most traditional CAD/CAM/CAE systems became unacceptably slow. Similarly, engineers and analysts investigating system level operating performance attempted to combine all of their component finite element models and perform non-linear finite element system simulations. These typically took Cray-weeks of simulation time to predict only seconds of real operating performance, thus making design trade-off investigations impractical. Similar problems occurred in manufacturing and assembly.
New methodologies, specifically oriented toward rapid system-level design, had to be adopted. The growth in simulation-based design tools has now shifted away from traditional CAD/CAM/CAE software and toward these newer system-focused solutions. Specifically, these system-level solutions include DMU tools to investigate product form and fit, Functional Virtual Prototyping tools to assess product function and operating performance, and Virtual Factory Simulation to assess manufacturability and assembly of the product. Enterprise-wide, Product Data Management (PDM) is the "glue" that enables these system-focused solutions to be successful by making all of the up-to-date component data readily available and manageable.
DMU offers solutions that make efficient use of tessellated three-dimensional component solid models and allow efficient design collaboration, mark-up, fly-through and interference/collision detection. Integrated with Product Data Management Systems, DMU products provide an excellent means to insure that all of the parts of the product will fit together properly and that the product will appear as specified.
Functional Virtual Prototyping solutions make efficient use of 3-D component solid models and modal representations of component finite element models to accurately predict the operating performance of the product in virtual lab tests and virtual field tests.
Virtual Factory Simulation solutions allow the entire manufacturing and assembly of products to be simulated, and assess the field maintenance of products as well.
The combination of DMU, Functional Virtual Prototyping and Virtual Factory Simulation provide a means for realizing an effective transition from hardware prototyping practices to software prototyping practices with all of the accompanying benefits. The remainder of this article will focus on the subject of Functional Virtual Prototyping and how it can be implemented.
Functional Virtual Prototyping
Effective Functional Virtual Prototyping allows the full operation of
the product to be considered and evaluated early enough in the design
process to allow for "function" to truly drive "form" and "fit." It
also allows multi-function optimization to be realized, such that a
true balance can be obtained between competing functional requirements
involving performance, safety, durability, cost, comfort, etc. These
two benefits were largely impractical in traditional development cycles
involving extensive reliance on hardware prototypes. In addition to
these benefits, functional virtual prototyping has proven effective in
facilitating tighter and more successful relationships between
manufacturers and their lead suppliers. Deployment of Functional
Virtual Prototyping typically involves five phases: Build, Test,
Validate, Refine and Automate. The first two phases will be discussed
here, the other three phases will be examined in Part two of this
article to be published in Volume 5, Number 5.
Build
During the Build phase, virtual prototypes are created of both the new
product concept and any target products which may already exist in the
market. In the early concept stage, the virtual prototype models of the
new product concept are kept simple and are most often driven by
desired functionality data curves, rather than by specific product
topologies. Appropriate target setting is, of course, very important.
The desired functionality data curves should be derived from a customer
Quality Function Deployment (QFD) study that identifies the desired
operating performance.
For instance, in the initial design of a vehicle suspension system, the virtual prototype model often involves only the overall vehicle body and a set of vehicle suspension curves that relate the movement of the body to the movement of the wheels. These data curves embody the desired suspension characteristics. During later model refinement, specific suspension topologies are chosen and the software optimizes suspension geometry and structural properties to yield the relationship described by the chosen curves. Similarly, to create models of target products, the actual target product is physically tested and its characteristics are accurately measured. This data is incorporated into a system-level model of the competitive vehicle to use later during the evaluation phases.
A modular system design process facilitates functional virtual prototyping and the manufacturer-supplier interaction. Clear inputs and outputs between various subsystems permit the development of multiple subsystem models with varying levels of model fidelity and complexity. These subsystem and system-level virtual prototypes are comprised of rigid and flexible representations of component parts connected through mathematically defined constraints. The geometry and mass properties for the parts are derived from component solid models; while the structural, thermal and vibratory properties are derived from component finite element models or experimental tests. The most effective implementations of functional virtual prototyping begin in this Build phase with a close cooperation between engineering analysts and test engineers. Also, up-front planning of the product parameters that may be varied in the design cycle and how manufacturers and suppliers are going to share models, can be tremendously helpful.
Test
Perhaps the single most important axiom for successful functional
virtual prototyping is to simulate as testing is performed. Testing of
hardware prototypes has traditionally involved both lab tests and field
tests in various configurations. With functional virtual prototyping,
virtual equivalents of the lab tests and the field tests need to be
created. By doing this, model validation is greatly facilitated through
testing, and cultural barriers to the adoption of functional virtual
prototyping practices are broken down. With regard to lab tests,
successful functional virtual prototyping dictates that virtual test
rigs that reproduce the test procedures and boundary conditions of the
real fixture and machine are constructed. With field tests, models that
represent the actual operating conditions of the product in the field
need to be constructed. This may involve virtual test tracks in
automotive, virtual landing strips in aircraft simulation, etc.
Effective implementations of Functional Virtual Prototyping require a tight synergy between physical testing of hardware prototypes (components and systems) as well as simulation-based testing of virtual prototypes (components and systems). Testing requirements vary during the different stages of the design process. At the outset of a new product design based on functional virtual prototyping, hardware testing is instrumental in two ways. First, component tests are performed using various real component alternatives. These tests provide good characteristic data for a complete system-level virtual prototype model. Secondly, full system hardware tests are conducted using target products. This allows for the simultaneous development of virtual prototypes of competing products so that performance comparisons can be made throughout the design and development cycle.
Subsequently, during concept design, virtual testing is used to exercise the new system model through a limited number of actual test scenarios such that performance data can be collected and validation can be performed. For companies that are initiating new functional virtual prototyping processes, it is imperative that they build a first system-level physical prototype at this stage in order to insure confidence in the simulation model. Companies who have been through this process a number of times have learned how to validate the modeling assumptions such that a physical prototype is unnecessary at this stage.
Once initial validation has been achieved by correlating the test results of the physical and virtual system prototypes, the true value of functional virtual prototyping begins to become apparent. Thousands of system variations, component choices, parameter choices and tolerances can be examined through simulation and the results can be used to confidently make design choices about the new product. Testing remains an important part of functional virtual prototyping throughout the design cycle. Virtual testing is conducted continuously. Physical testing is introduced at various stages to either re-validate the model after significant refinement or to test certain configurations of the product containing design parameters outside of those for which the model has been validated.
References
1. Bidrawn, Les and Kohnle, Thomas, "The New 3," BMW Magazine, Vol. 2, 1998, pp. 8-14.
