The ability to improve tooling and increase materials utilization is hindered by technology barriers that exist in several aspects of the forging process. These include lubrication, material property understanding, validated process modeling, measurement and testing, die making, die materials, and process control. Distinctions among these areas are fairly clear, although some barriers associated with measurement and testing, process control, and process modeling may be closely related.
Among the most critical barriers is the lack of effective lubrication methods between the die and the forged material. More precisely, there is a lack of technologies?innovative die materials, coatings, equipment, and processes?that would eliminate the need for lubricants altogether. Material-surface coatings are needed that provide very low heat transfer and can handle variability in the coefficient of friction. There is also inefficient use of lubricants because they are not applied locally to the portion of the tooling or under specific conditions that require lubrication.
Limitations in the area of validated process modeling span a wide range of needs. For example, there is a lack of universal geometrical models, understanding of tribological phenomena, materials models to predict micro-structure, cost models to determine minimum cost processes, and other data and methods that could improve modeling of the forging process. The greatest need, however, is in the integration and optimization of these models. In particular, there is a lack of integrated computer systems for forging that take into account all of the relevant process variables. Better integration is needed between the customer's CAD/CAM system, the forge shop's CAD/CAM system, tool design, and other design and process steps to effectively simulate the forging process and adjust part and die design based on this. The cost and the complication of developing and using 3-D simulation tools has resulted in a lack of efficient 3-D computational tools that could greatly improve process modeling. Furthermore, simulations are currently limited in their ability to depict actual conditions. For example, a single friction factor is currently used in simulations of hot forging even though actual friction is known to vary with temperature and materials.
Without integrated, validated process models, it is difficult to determine the optimal die design or material for the product requirement. A sophisticated model could reverse engineer the die and tooling based on the customer part specification and provide an optimal design that uses materials and tools more efficiently.
Among the most critical barriers is the lack of effective lubrication methods between the die and the forged material. More precisely, there is a lack of technologies?innovative die materials, coatings, equipment, and processes?that would eliminate the need for lubricants altogether. Material-surface coatings are needed that provide very low heat transfer and can handle variability in the coefficient of friction. There is also inefficient use of lubricants because they are not applied locally to the portion of the tooling or under specific conditions that require lubrication.
Limitations in the area of validated process modeling span a wide range of needs. For example, there is a lack of universal geometrical models, understanding of tribological phenomena, materials models to predict micro-structure, cost models to determine minimum cost processes, and other data and methods that could improve modeling of the forging process. The greatest need, however, is in the integration and optimization of these models. In particular, there is a lack of integrated computer systems for forging that take into account all of the relevant process variables. Better integration is needed between the customer's CAD/CAM system, the forge shop's CAD/CAM system, tool design, and other design and process steps to effectively simulate the forging process and adjust part and die design based on this. The cost and the complication of developing and using 3-D simulation tools has resulted in a lack of efficient 3-D computational tools that could greatly improve process modeling. Furthermore, simulations are currently limited in their ability to depict actual conditions. For example, a single friction factor is currently used in simulations of hot forging even though actual friction is known to vary with temperature and materials.
Without integrated, validated process models, it is difficult to determine the optimal die design or material for the product requirement. A sophisticated model could reverse engineer the die and tooling based on the customer part specification and provide an optimal design that uses materials and tools more efficiently.
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