Dr Rich Martukanitz, of the Commonwealth Center for Advanced Manufacturing and the University of Virginia, explains how a performance qualification protocol in traditional manufacturing can be adapted for AM
Laser-based additive manufacturing (AM) of metallic materials is receiving considerable attention for use in several industries, based on its ability to dramatically increase design complexity with minimal increase in cost, its capability to easily customise products, and its capacity to act as a ‘point of manufacturing’ for on-demand items. Because AM is currently considered a relatively low production-rate process that commands a premium, many of its potential applications are directed at high-value components, and in most instances these components have high performance requirements. This means that a high level of quality and repeatability must be maintained throughout all stages of additive manufacturing – including design, material qualification and processing – in order to meet the performance requirements dictated by the applications of the high-value components being made.
The traditional method of maintaining a specified level of quality in a manufacturing process is to define and conduct the process based on a performance qualification protocol. This approach, used throughout many industries, relies on sufficient defining and documenting of the important process parameters that enable key performance requirements specific to the product and application. Test results are used to confirm that the process defined using these parameters is capable of meeting the requirements of the product. Once the process is established and provides the desired outcome, these essential parameters are monitored and maintained. A concept for applying this approach to AM is shown below.
A concept for utilising a performance qualification protocol for additive manufacturing.
This concept has been formulated to address several unique features regarding AM. This includes the critical link between the design and manufacturing functions, the important aspects of material feedstock quality and processing system stability, and the potential use of process monitoring and/or sensing to ensure process reliability. The design verification and process definition stage is an iterative process. Once the design and process are defined, qualification of the material, AM system, and entire process is conducted by confirming that the resultant product will meet the intended performance requirements established during the design verification and process definition stage. This is achieved by producing actual components, or simulated components, using the defined process, and testing the resultant product to confirm properties and/or characteristics that may define performance. The AM process is conducted while thoroughly documenting all materials, systems, and processing conditions that may influence the process and resultant product. If the desired properties are attained from the performance tests, the process is formally specified as being qualified to produce the design using these prescribed parameters and conditions.
Essential variables that define the process are monitored or verified to assure conformity. By continually tracking the variation of critical parameters and conditions, indications of trends may be used to intercede before exceeding established limits for controlling the process. Monitoring and controlling essential variables may also be augmented through real-time sensing of process characteristics. Various sensing methods have been developed that offer insight into the process, as well as improve resolution for assigning consistency to the AM process. These sensor techniques, as they relate to the laser-based powder bed fusion AM process, include high resolution imaging for identifying layer anomalies or defects, acoustic emission sensing for indicating crack generation, and diode sensors for measuring laser attenuation and process stability. The potential of linking and synchronising critical processing information, such as scan path vectors, with additional sensor data, may provide a powerful method of defining process stability and, ultimately, part quality.