Computer applications for the global community
In the 21st century metal processing industries must work more intelligently if they are to survive and to grow, says Jim Marder PhD, ASM Technical Director.
One way that industry can work "smarter, not harder", is by using computational modelling to dramatically increase the success rate of new forging, casting, heat treatment or surface treatment processes, while reducing the time and money required for a successful product development effort.
Industry uses a wide variety of computational tools, such as finite element analysis, to model materials behaviour, fabrication and component life prediction.
Computer models are also required to support the emerging disciplines of intelligent process planning and control.
These applications require accurate analytical models and databases of mechanical, physical, thermal and mass transport properties.
In addition, data to verify analytical predictions are required to refine the analytical tools that are used.
The National Academy of Sciences has reported that: "Materials engineering is at least a decade behind other engineering disciplines in developing a core set of computational tools".
A major reason for this deficiency is the lack of reliable data sets for use in modelling the behaviour of materials under processing conditions.
Most of our databases are devoted to material properties relevant to their application, rather than to their manufacture.
For example, titanium forging is generally carried out in the 1750-1850F temperature range, but it is used, at best, up to about 1200F.
It is clear that databases devoted to properties under processing conditions are necessary if the wider application of modelling can be expected.
With the approval of the Board of Trustees, ASM has taken on the task of assessing which processes should be examined first, and what the data set should look like.
Our assessment, using the expertise and input of our volunteer members, will directly affect how the metal processing industries will evolve in the world economy.
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