Additive Manufacturing Preparation

The preparation step of the additive manufacturing process is to set up the system before the manufacturing process is carried out. This includes manufacturing settings that are highly relevant to the result of the part produced with AM. Nonetheless, it is difficult to provide an outline of the subject and there are no general guidelines. The types of settings that are available depend on which machine and which software is used to control the machine. Which settings are optimal also depends on the material, the geometry, and whether the other components are made at the same time. The manufacturing settings could be divided into four types: Energy-related, scan-related, powder-related, and temperature-related. Energy-related settings include energy source power, spot size, pulse duration, and pulse frequency. Scan-related settings include scanning speed, scanning spacing, and scanning pattern. Powder-related settings are connected to the substance used and include the shape and size of the particle as well as how the powder is dispersed and the thickness of the coating used. Temperature-related parameters include the temperature of the powder bed, the feeder, and the temperature consistency. Both parameters are highly dependent on each other, and changing one would also affect the other parameters. Many additive manufacturing companies use standard settings for various materials and machines, making it difficult for the design engineer to change the settings. Instead, the most common way is to change the design if there are manufacturing errors. In a perfect future, the design phase would involve a feedback loop where geometry and manufacturing settings are managed together to optimize the device as a whole.

Validation of Build Time and Cost

The estimation of the construction time of the part is crucial in order to be able to calculate the cost of production. In the area of cost simulations for additive manufacturing, Costabile et al. (2017) carried out a comprehensive review of the different research studies and concluded that, no matter which AM technique is used, the cost model looks similar. Several different models are highlighted and presented in more detail. Chiu and Lin (2016) investigated the possibility of producing a simulated business case to determine whether or not a product is suitable for conversion to AM, including a cost model combined with design for additive manufacturing to optimize costs based on design and production techniques.

Additive Manufacturing Simulation

Numerous methods have been used in both research and commercial applications to model the additive manufacturing process, resulting in efficiency, surface quality, and dimensional accuracy of the final component. Bikas et al. (2016) divided the simulation approaches into three categories—analytical, numerical, and empirical—on the basis of which principle is used. Analytical simulation models are based on physical laws that have the advantage that they can be easily adapted to different processes, machines, and machine settings.

However, they are limited by the initial observations that need to be made in order to apply the laws of physics. The analytical method is focused on observation and is therefore reliable for the exact set-up of the test, but is more difficult to adjust to other devices and set-ups. The numerical approaches attempt to combine the two other methods and start with an analytical model that is combined with a numerical model.

 
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