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Standard Guide for In-Process Monitoring Using Optical and Thermal Methods for Laser Powder Bed Fusion
1.1Â This guide provides information on emerging in-process monitoring sensors, sensor configurations, sensor data analysis, and sensor data uses for the laser powder bed fusion additive manufacturing process.
1.2Â The sensors covered produce data related to and affected by feedstock, processing parameters, build atmosphere, microstructure, part geometry, part complexity, surface finish, and the printing equipment being used.
1.3Â The parts monitored by the sensors covered in this guide are used in aerospace applications; therefore, their final inspection requirements for discontinuities are different and more stringent than for materials and components used in non-aerospace applications.
1.4Â The metal materials under consideration include, but are not limited to, aluminum alloys, titanium alloys, nickel-based alloys, cobalt-chromium alloys, and stainless steels.
1.5Â This guide discusses sensor observation of parts while they are being fabricated. Sensor data analysis may take place concurrently or after the manufacturing process has concluded.
1.6Â The sensors discussed in this guide may be used by cognizant engineering organizations to detect both surface and volumetric flaws.
1.7Â The sensors discussed in this guide may be used by cognizant engineering organizations to detect process stability or drift, or both.
1.8Â The sensors discussed in this guide are primarily configured in staring, co-axial, or mounted configurations.
1.9Â This guide does not recommend a specific course of action, sensor type, or configuration for application of in-process monitoring to additively manufactured (AM) parts. It is intended to increase the awareness of emerging in-process sensors, sensor configurations, data analysis, and data usage.
1.10Â Recommendations about the control of input materials, process equipment calibration, manufacturing processes, and post-processing are beyond the scope of this guide and are under the jurisdiction of ASTM Committee F42 on Additive Manufacturing Technologies. Standards under the jurisdiction of ASTM F42 or equivalent are followed whenever possible to ensure reproducible parts suitable for NDT are made.
1.11Â Recommendations about the inspection requirements and management of fracture critical AM parts are beyond the scope of this guide. Recommendations on fatigue, fracture mechanics, and fracture control are found in appropriate end user requirements documents, and in standards under the jurisdiction of ASTM Committee E08 on Fatigue and Fracture.
Note 1:Â To determine the deformation and fatigue properties of metal parts made by additive manufacturing using destructive tests, consult Guide F3122.
Note 2:Â To quantify the risks associated with fracture critical AM parts, it is incumbent upon the structural assessment community, such as ASTM Committee E08 on Fatigue and Fracture, to define critical initial flaw sizes (CIFS) for the part to define the objectives of the NDT.
1.12Â This guide does not specify accept-reject criteria used in procurement or as a means for approval of AM parts for service. Any accept-reject criteria are given solely for purposes of illustration and comparison.
1.13 Units—The values stated in SI units are to be regarded as the standard. No other units of measurement are included in this standard.
1.14Â This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.
1.15Â This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
1.1Â This guide provides information on emerging in-process monitoring sensors, sensor configurations, sensor data analysis, and sensor data uses for the laser powder bed fusion additive manufacturing process.
1.2Â The sensors covered produce data related to and affected by feedstock, processing parameters, build atmosphere, microstructure, part geometry, part complexity, surface finish, and the printing equipment being used.
1.3Â The parts monitored by the sensors covered in this guide are used in aerospace applications; therefore, their final inspection requirements for discontinuities are different and more stringent than for materials and components used in non-aerospace applications.
1.4Â The metal materials under consideration include, but are not limited to, aluminum alloys, titanium alloys, nickel-based alloys, cobalt-chromium alloys, and stainless steels.
1.5Â This guide discusses sensor observation of parts while they are being fabricated. Sensor data analysis may take place concurrently or after the manufacturing process has concluded.
1.6Â The sensors discussed in this guide may be used by cognizant engineering organizations to detect both surface and volumetric flaws.
1.7Â The sensors discussed in this guide may be used by cognizant engineering organizations to detect process stability or drift, or both.
1.8Â The sensors discussed in this guide are primarily configured in staring, co-axial, or mounted configurations.
1.9Â This guide does not recommend a specific course of action, sensor type, or configuration for application of in-process monitoring to additively manufactured (AM) parts. It is intended to increase the awareness of emerging in-process sensors, sensor configurations, data analysis, and data usage.
1.10Â Recommendations about the control of input materials, process equipment calibration, manufacturing processes, and post-processing are beyond the scope of this guide and are under the jurisdiction of ASTM Committee F42 on Additive Manufacturing Technologies. Standards under the jurisdiction of ASTM F42 or equivalent are followed whenever possible to ensure reproducible parts suitable for NDT are made.
1.11Â Recommendations about the inspection requirements and management of fracture critical AM parts are beyond the scope of this guide. Recommendations on fatigue, fracture mechanics, and fracture control are found in appropriate end user requirements documents, and in standards under the jurisdiction of ASTM Committee E08 on Fatigue and Fracture.
Note 1:Â To determine the deformation and fatigue properties of metal parts made by additive manufacturing using destructive tests, consult Guide F3122.
Note 2:Â To quantify the risks associated with fracture critical AM parts, it is incumbent upon the structural assessment community, such as ASTM Committee E08 on Fatigue and Fracture, to define critical initial flaw sizes (CIFS) for the part to define the objectives of the NDT.
1.12Â This guide does not specify accept-reject criteria used in procurement or as a means for approval of AM parts for service. Any accept-reject criteria are given solely for purposes of illustration and comparison.
1.13 Units—The values stated in SI units are to be regarded as the standard. No other units of measurement are included in this standard.
1.14Â This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.
1.15Â This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
4.1Â Metal additive manufacturing has broadened design space, enabling production of more complex and customized products. Additive technology along with the broadened design space is pushing the limits of inspection capabilities and has led to challenges in process and product qualification, verification, certification, etc. In-process monitoring technologies have been developed to help address these challenges.
4.2 In-process monitoring in AM is emerging from the realm of Research and Development (R&D). As such, there are not yet well-established procedures for incorporating AM process monitoring within a qualification or certification framework outside of a specific company or institution’s internal use. Practical application of in-process monitoring data spans multiple disciplines and parts of the production cycle, each with well-established practices, terminology, expectations, etc. This guide draws on these where appropriate.
4.3 Inspection and Statistical Process Control (SPC)— A primary motivation for using in-process monitoring technologies is to aid in process and product qualification, verification, certification of AM components that are increasingly difficult to inspect. AM process monitoring functions can be broadly separated into two categories of application: in-process inspection and process control. In-process inspection refers to the identification of in-process signatures that correlate to the formation of physical flaws and defects in additively manufactured component. This is discussed further in 5.2 on Flaw Detection. Statistical Process Control (SPC) encompasses measurement or observation of process signatures or metrics associated with the stability or repeatability of the additive manufacturing process. This is discussed further in 5.3 on Statistical Process Control (SPC). Real-time feed-forward or feed-back control methods and techniques may be considered subcategories under process control, and can make use of the same in-process monitoring measurement tools. Currently, these concepts and techniques are still largely under research and development not generally implemented in commercial LPBF systems. They are not discussed further in this guide.
4.4 Production and Development Uses— Production of finished components using additive manufacturing requires some combination of inspection to ensure the component meets design requirements for the ultimate product functionality and process qualification. Both inspection and process control applications of in-process monitoring may be integrated into an overall product or process qualification, verification, or certification strategy, or a combination thereof, in the production environment. In-process monitoring tools are also valuable in the development both of the additive process and build design, providing support for engineering decisions on parameter selection (for example, laser power, scan speed) for new materials, scan strategy, part geometry, part placement on an AM build platform, etc. A prerequisite to SPC is establishing the normal variation of the process which can be evaluated using in-process monitoring tools during process development.
4.5 Economic Justification— In-process monitoring can be economically justified through its contribution to cost reduction and yield improvements in addition to its value to the additive manufacturing enterprise as an element of an overall process or product qualification, verification, or certification strategy, or a combination thereof. For high value products, in-process monitoring has been shown to reduce the scrap fraction rate by at least 10 % according to recent literature.7 The realization of the cost/part reduction in the scrap fraction rate over time is dependent on the diagnostic capability of the in-process monitoring strategy as measured in false alarm (false positive) and undetected defect (false negative) performance. Further in-process monitoring can produce per part cumulative yield improvements through enabling process engineering diagnosis capabilities within part manufacturing such that SPC charts can be tuned to optimize the system’s diagnostic performance.
4.6 Identifying Part Quality from Process Signatures— Ultimately, final part quality metrics and associated mechanical or functional performance of AM parts are of greatest concern. Guide E3166, pertaining to ex-situ NDT, identifies two correlations of interest: process-flaw correlation and flaw-property correlation. In the context of this guide, measurements of material flaws or properties are considered part quality metrics. As noted in Guide E3166, part quality metrics may be correlated to the process or process parameters, such as laser power, laser scan speed, etc. as shown in Fig. 1. In-process monitoring pertains to the observation and measurement of process signatures, or observable phenomena that occur during the AM process, for example, electromagnetic emissions from the melt pool, acoustic emissions, etc. Process signatures are correlated to process parameters. While process parameters are generally commanded or set point values, process signatures provide a measured voice of process. Process signatures may also be correlated to part quality metrics, as shown in Fig. 1. As part of a product inspection and validation strategy, in-process monitoring aims to utilize the correlation between these process signatures and part quality metrics. In-process monitoring can thus be used to in conjunction with or in-lieu of post-process inspection methods (for example, NDE).
4.6.1 Process Signature Taxonomy— Many different terms have been used in AM to describe process signatures or part quality metrics in the context of in-process monitoring (for example, defect, fault, flaw, anomaly, imperfection, etc.). The following provides a high-level taxonomy used in this guide to further define and categorize deleterious process signatures in AM process monitoring. As noted in 4.3, in-process monitoring is primarily used as part of an overall quality plan, either as a supplement to or replacement of traditional component inspection methods (for example, NDE) or to enable statistical process control. These two functions are mapped to corresponding taxonomies are mapped in Fig. 2.
4.6.2Â For the in-process enabled inspection case, this taxonomy builds upon established standards or work items (see Terminology E1316, Guide E3166, and ISO/ASTM TR 52905).
4.6.3Â Statistical process control (SPC) uses statistical methods to improve quality by reducing the variability of one or more process outputs. For in-process monitoring enabled statistical process control, one or more process signatures are the outputs of
| SDO | ASTM: ASTM International |
| Document Number | E3353 |
| Publication Date | July 1, 2022 |
| Language | en - English |
| Page Count | 29 |
| Revision Level | 22 |
| Supercedes | |
| Committee | E07.10 |
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