Quality management: A decisive factor for industrializing additive manufacturing
Additive manufacturing differs from traditional manufacturing methods in many ways. It allows for almost unlimited part designs, yet the use of new materials is creating new challenges when it comes to quality assurance. The traditional methods and approaches to quality management (such as verifying the part after manufacturing) will not deliver the desired quality for 3D printed parts.
This is especially true for industries such as aerospace, where certification requirements are high and part failures can have devastating consequences.
The challenges to achieving quality in additive manufacturing
Delivering high-quality additive manufactured parts requires manufacturers to mitigate a variety of challenges.
The quality of the parts printed is heavily dependent on the materials used, especially in metal printing. Inferior material input can be caused by several factors, such as the contamination often found in reused powder — since the composition of particles is changed caused by moisture, oxygen or nitrogen. The same is true for powder that is left on the build plate of the printer. Other material insufficiencies can stem from material transport, storage or handling.
Another major challenge is the lack of process control that should cover the process from engineering into production to post-processing of parts. Many parameters in this process influence the quality of a part. Success or failure can be dependent on the path and intensity of the laser used in the printer. Furthermore, the speed of the printer’s recoater blade plays a vital role, as well as the design of the support structure. Current quality assurance methods have a limited ability to solve these problems. The result is a kind of inefficient and costly trial-and-error approach that negate the major benefits of additive manufacturing — such as the efficient production of small and complex batches.
Human error is another challenge to additive manufacturing quality, since the human factor is highly involved in the complete process: design, manual checks of requirement fulfillment during print or inspection before post-processing. Since key performance and/or quality indicators are enforced manually, this inherits the danger of failure.
The solution: End-to-end process control approach
Since the industrialization of additive manufacturing is progressing driven by new possibilities the technology promises, these challenges must be overcome. Quality management in additive manufacturing requires an end-to-end approach — starting with the material and ending with post-processing of the printed part. How comprehensive this approach must be is determined by the particular industry and its quality expectations.
Obviously, an aerospace company will have tighter quality levels than a manufacturer of 3D-printed plastic parts being installed in a toy. Quality assurance in additive manufacturing must focus on design and build instead of verifying quality after manufacturing, like in conventional production. Manufacturers should strive for a closed-loop approach.
“Additive manufacturing is creating new challenges when it comes to quality assurance. Traditional methods and approaches to quality management will not deliver the desired quality for 3D printed parts. Quality management in additive manufacturing needs an end-to-end approach — starting with the material and ending with post-processing of the printed part.”
This approach will include simulation technologies that will give insights into how a part will behave in manufacturing before the part design is sent to the printer. This kind of simulation could include porosity prediction (for metal part manufacturing), thermal simulation or fatigue simulation. In addition, employing computer tomography can provide valuable data into the microstructure of the materials before they are used in production. It will also deliver data on how materials can be further improved to reduce material defects such as inclusions or intraparticle porosity.
This must be complemented by close monitoring of the 3D printing process. Solutions like the Atos Predictive Monitoring System use sensors built into the 3D printer to detect anomalies during the printing process. Complex algorithms will deliver valuable data to the production manager and printer operator in real time, allowing them to take action during the printing process. This is especially important for easing the certification of parts for the aerospace industry.
After the printing process, a comparison of the printed part with its digital counterpart (as stored in an additive manufacturing platform) will help operators judge the part quality before it enters post-production.
Thus, technology will play a vital role in improving quality levels in additive manufacturing, as common standards and certifications driven by organizations like AMST International or the National Institute of Standards and Technology (NIST) are progressing slowly.