The role of virtual technology in automotive design
Ford’s Mario Felice on the company’s quick shift to a virtual powertrain design process
Shifting from traditional V engineering processes and going virtual is a challenge for practically all the automotive OEMs. Like many other brands, Ford has drastically and rapidly streamlined its product development process known internally as GPDS (Global Product Development System) to improve process efficiencies and deliver faster products to the market that meet high quality standards without exceeding cost limitations. Mario Felice, Manager Powertrain NVH CAE, is quick to credit the virtual revolution as partially responsible for this success.
“Fully integrating CAE into GPDS was crucial to increase efficiency because it drives design optimization upfront in the development process – substantially reducing late design changes and prototype testing. GPDS is a major departure from the previous test driven development process which mostly used CAE downstream for analysis evaluation and design verification prior to final product test validation,” said Mario Felice. “What Ford has done over the past two to three years has drastically changed the process. Our commitment to the Drive One campaign and this new GPDS process has put us very close to the number one quality spot.”
The fast and furious pace of Ford’s new development cycles
Today at Ford, CAE and CAD people work together to make sure that the design meets all its targets – attributes and functional targets – as well as meeting the extremely short design freeze dates. After the design is frozen, the parts are made and the hardware validated while, at the same time, the CAE department makes sure that their models validate. Then they backtrack and use lessons learned to improve the process the next time. “Our new GPDS process is very efficient. It is a continuous loop. There is no room for fooling around. You don’t have the luxury. You just don’t have the time,” quipped Mario Felice.
In the past, CAE at Ford was a secondary task. Now it is clearly taking a front seat in the development process. The CAE process is driving the design and the team at Ford is finding out that it needs to make sure that everyone has the right tools to optimize and achieve design robustness.
“Especially working as a global company, sharing models with North America, Europe and South America, it is very important that we use the same software tools and technology. At the end of the day, if we have to compare Design A with Design B, we better make sure that the people use the software and do the analysis the same way. That is a real challenge – the communization of the process,” remarked Mario Felice.
The route to multi-attribute optimization
As part of these process improvements, Ford has decided to standardize globally on Dassault Systèmes’ CATIA, a platform that tightly integrates CAE techniques. Ford teams are now busy integrating and revamping various CAE methods and optimization techniques in line with global best practices.
“Today, optimization iterates on the design until the targets are met. In the past, the NVH people were doing the NVH. And the durability analysts were doing durability and the engineers were trying to integrate all the different CAE attributes together for a robust design.This is changing now thanks to multi- physics software, like LMS Virtual.Lab and LMS Imagine.Lab,” states Mario Felice.
No more data juggling
To deal with different physic domains from various dynamics to hydraulics and fluids, Mario Felice and his team are also reaping the benefits of the 1D and 3D simulation strengths of LMS Imagine.Lab AMESim together with LMS Virtual.Lab. They are using LMS Virtual.Lab for everything from multi-body dynamics to frequency response analysis on FE models and acoustic modeling as well as LMS Imagine.Lab for 1D fluid dynamics. For hybrid engineering tasks, they are importing test data from LMS Test.Lab to create numerical models for analysis.
“We took days out of our analysis process. There were huge gains in time efficiency. Now, we don’t need to reshuffle data and jump from software to software. With the old situation, there was no interaction; it was really a one-way street,” clarified Mario Felice. “With multi-attribute engineering, you must be able to work in multi-disciplines with an optimization code. This is key to our process, but at the end of the day the customer doesn’t care whether it is NVH or durability. They want toughness, quietness and they want performance. Our new CAE approach and tools cross those attributes to deliver what our customers want.”
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