Nonetheless, the name "DfAM" has value because it focuses attention on the way that commercializing AM in production roles is not just a matter of figuring out how to switch existing parts from subtractive to additive.
That is, it involves redesigning them because their entire earlier design—including even how, why, and at which places they were originally divided into discrete parts—was conceived within the constraints of a world where advanced AM did not yet exist.
For example, in 2017, GE Aviation revealed that it had used DfAM to create a helicopter engine with 16 parts instead of 900, with great potential impact on reducing the complexity of supply chains.
"[3] In other words, the disruptive innovation that AM can allow can logically extend throughout the enterprise and its supply chain, not just change the layout on a machine shop floor.
[4] Comparing to traditional manufacturing technologies such as CNC machining or casting, AM processes have several unique capabilities.
Moreover, traditional feature-based CAD tools are also difficult to deal with irregular geometry for the improvement of functional performance.
To solve this issue, additive manufacturing processes can be applied to fabricate topology optimization result.
[6] However, it should be noticed, some manufacturing constraints such as minimal feature size also need to be considered during the topology optimization process.
[20][21] Thermal modelling can be used to inform part design and the choice of process parameters for manufacture, in place of expensive empirical testing.
[22][23][24] Additively manufactured metallic structures with the same (macroscopic) shape and size but fabricated by different process parameters have strikingly different microstructures and hence mechanical properties.
[25] Therefore, in principle, one could simultaneously 3D-print the (macro-)structure as well as the desirable microstructure depending on the expected performance of the specialized AM component under the known service load.
In this context, multi-scale and multi-physics integrated computational materials engineering (ICME) for computational linkage of process-(micro)structure-properties-performance (PSPP) chain can be used to efficiently search an AM design subspace for the optimum point with respect to the performance of the AM structure under the known service load.
[26] The comprehensive design space of metal AM is boundless and high dimensional, which includes all the possible combinations of alloy compositions, process parameters and structural geometries.
It is hypothesized that the optimal design approach is essential for unraveling the full potential of metal AM technologies and thus their widespread adoption for production of structurally critical load-bearing components.