As reported by Ford
* Partnering with top-ranked national and international universities, the Ford “Atoms to Engines” team challenged skeptics to develop the world’s first virtual materials modeling prediction tool that allows the team to simulate the microstructures of a material before the first prototype is built.
* The Atoms to Engines team blends engineering and science to develop physics-based computer models that predict how properties and materials will behave and change during the manufacturing process.
* Building these computer models integrates the study of product performance, manufacturing and materials; in some cases it requires analyzing metals down to their atomistic level.
* The result? Components that are more durable and efficiently constructed, which saves the company considerable development time and money. In fact, the process is estimated to save Ford between $2 and $5 million a year in reducing test requirements and product development time.
CONTEXT / BACKGROUND:
Computational materials engineering is anything but simple. It involves analyzing the properties of metal, sometimes down to its very atoms, to determine how they will alter during the manufacturing process. At Ford, a blended team of engineers and scientists is using this approach to develop software models that predict when and how those changes will occur, and performs computer simulations that eliminate the need for physical tests. It’s such a complex field, in fact, that when Ford entered it back in the late 1990s, team members like John Allison were initially doubted before they were heralded as leaders in a new field in materials research.
Members of Ford’s Atoms to Engines team are highly regarded in the auto industry and beyond. Why? Because gaining that intimate knowledge of these materials – finding out how even a small change at microscopic levels can make a significant difference – can lead to major changes in the big picture. Such changes as lighter, durable, more fuel-efficient construction are precisely the elements behind Ford’s ascent to exceptional quality.
DETAILS:
Computational materials engineering, in its most basic form, is about researching materials and structure, using that knowledge to build models, and predicting how vehicle parts will perform – even before they’re built.
In the beginning
* John Allison, senior technical leader in advanced metals, is a key developer of the Virtual Aluminum Castings software tool set, which pinpoints potential stress points in parts for engine blocks and cylinder heads while they’re on the drawing board, eliminating the need for imprecise, costly testing.
* The Atoms to Engines team, known formally as the Integrated Computational Materials Engineering Team, developed a partnership with renowned experts from universities around the world, including professor Wayne Jones from the University of Michigan, professor Peter Lee from Imperial College in London and professor Baicheng Lui from Tsinghua University in Beijing. Five other universities round out the list, including Penn State, Ohio State, Northwestern University, University of Wisconsin and University of Illinois.
* The software has been used in development of more than 15 new engine programs and has enabled cost avoidance of more than $100 million.
* Computational materials engineering also has been used on the recently released 3.5-liter EcoBoost™ block and head and the soon-to-be-released 6.7-liter Power Stroke® diesel, where the technology enabled the use of aluminum cylinder heads, for a 160-pound weight savings.
Branching out
The team has now branched out from powertrains to other aspects of manufacturing. The work of Allison’s team with magnesium enabled development of a lighter-weight liftgate for the 2010 Lincoln MKT. Using magnesium for this part – the largest magnesium die casting in the world – allowed for a 40 percent weight savings.
photo:Ford
* Partnering with top-ranked national and international universities, the Ford “Atoms to Engines” team challenged skeptics to develop the world’s first virtual materials modeling prediction tool that allows the team to simulate the microstructures of a material before the first prototype is built.
* The Atoms to Engines team blends engineering and science to develop physics-based computer models that predict how properties and materials will behave and change during the manufacturing process.
* Building these computer models integrates the study of product performance, manufacturing and materials; in some cases it requires analyzing metals down to their atomistic level.
* The result? Components that are more durable and efficiently constructed, which saves the company considerable development time and money. In fact, the process is estimated to save Ford between $2 and $5 million a year in reducing test requirements and product development time.
 |
| EcoBoost engine. |
CONTEXT / BACKGROUND:
Computational materials engineering is anything but simple. It involves analyzing the properties of metal, sometimes down to its very atoms, to determine how they will alter during the manufacturing process. At Ford, a blended team of engineers and scientists is using this approach to develop software models that predict when and how those changes will occur, and performs computer simulations that eliminate the need for physical tests. It’s such a complex field, in fact, that when Ford entered it back in the late 1990s, team members like John Allison were initially doubted before they were heralded as leaders in a new field in materials research.
Members of Ford’s Atoms to Engines team are highly regarded in the auto industry and beyond. Why? Because gaining that intimate knowledge of these materials – finding out how even a small change at microscopic levels can make a significant difference – can lead to major changes in the big picture. Such changes as lighter, durable, more fuel-efficient construction are precisely the elements behind Ford’s ascent to exceptional quality.
DETAILS:
Computational materials engineering, in its most basic form, is about researching materials and structure, using that knowledge to build models, and predicting how vehicle parts will perform – even before they’re built.
In the beginning
* John Allison, senior technical leader in advanced metals, is a key developer of the Virtual Aluminum Castings software tool set, which pinpoints potential stress points in parts for engine blocks and cylinder heads while they’re on the drawing board, eliminating the need for imprecise, costly testing.
* The Atoms to Engines team, known formally as the Integrated Computational Materials Engineering Team, developed a partnership with renowned experts from universities around the world, including professor Wayne Jones from the University of Michigan, professor Peter Lee from Imperial College in London and professor Baicheng Lui from Tsinghua University in Beijing. Five other universities round out the list, including Penn State, Ohio State, Northwestern University, University of Wisconsin and University of Illinois.
* The software has been used in development of more than 15 new engine programs and has enabled cost avoidance of more than $100 million.
* Computational materials engineering also has been used on the recently released 3.5-liter EcoBoost™ block and head and the soon-to-be-released 6.7-liter Power Stroke® diesel, where the technology enabled the use of aluminum cylinder heads, for a 160-pound weight savings.
Branching out
The team has now branched out from powertrains to other aspects of manufacturing. The work of Allison’s team with magnesium enabled development of a lighter-weight liftgate for the 2010 Lincoln MKT. Using magnesium for this part – the largest magnesium die casting in the world – allowed for a 40 percent weight savings.
photo:Ford