SIST EN ISO/ASTM 52953:2025
(Main)Additive manufacturing for metals - General principles - Registration of data acquired from process monitoring and for quality control (ISO/ASTM 52953:2025)
Additive manufacturing for metals - General principles - Registration of data acquired from process monitoring and for quality control (ISO/ASTM 52953:2025)
This document sets and defines the minimum requirements for registration of data acquired from process monitoring and for quality control in additive manufacturing (AM), including the description of a procedure.
Furthermore, this document comprises actions that users shall execute to register multi-modal AM data and store them in an appropriate repository.
This document is not applicable for data cleansing, sensor calibration, and image processing.
This document is only applicable for data gathered and generated from non-destructive test methods and sensors, e.g. X-ray computer tomography (XCT), thermal sensor, cameras and coordinate measuring machines (CMM).
This document is only applicable to metallic parts produced by means of laser-based powder bed fusion (PBF-LB); nevertheless, the procedures described in this document can be applied to monitor other AM processes and materials (e.g. directed energy deposition, polymer or ceramic powder bed fusion, binder jetting, and photopolymerization), but this document does not provide any data or case studies for them.
Additive Fertigung von Metallen - Allgemeine Grundsätze - Registrierung von Daten aus der Prozessüberwachung und zur Qualitätskontrolle (ISO/ASTM 52953:2025)
Dieses Dokument definiert und spezifiziert die Mindestanforderungen für die Registrierung von Daten, die bei der Prozessüberwachung und der Qualitätskontrolle in der additiven Fertigung (AM) erfasst werden, einschließlich der Beschreibung eines Verfahrens.
Darüber hinaus beschreibt dieses Dokument Aktivitäten, die Anwender ausführen müssen, um multimodale AM-Daten zu registrieren und sie in einem geeigneten Repository zu speichern.
Dieses Dokument ist nicht anwendbar für die Bereiche Datenbereinigung, Sensorkalibrierung und Bildverarbeitung.
Dieses Dokument ist nur auf Daten anwendbar, die mit zerstörungsfreien Prüfverfahren und Sensoren, z. B. Röntgen-Computertomographie (XCT), Wärmesensoren, Kameras und Koordinatenmessgeräten (CMM, en: coordinate measuring machines), erfasst und erzeugt wurden.
Dieses Dokument ist nur auf Metallteile anwendbar, die mittels pulverbettbasiertem Schmelzen mittels Laserstrahl (PBF-LB) hergestellt wurden. Dennoch können die in diesem Dokument beschriebenen Verfahren zur Überwachung anderer AM Prozesse und Materialien [z. B. Materialauftrag mit gerichteter Energieeinbringung (DED, en: direct energy deposition), pulverbettbasiertes Schmelzen von Polymeren oder Keramiken, Freistrahl-Bindemittelauftrag und Photopolymerisation] angewendet werden. Allerdings enthält dieses Dokument dafür keine Daten oder Fallstudien.
Fabrication additive de métaux - Principes généraux - Enregistrement de données acquises à partir de la surveillance du procédé et pour le contrôle qualité (ISO/ASTM 52953:2025)
Le présent document fixe et définit les exigences minimales relatives à l'enregistrement de données acquises à partir de la surveillance du procédé et pour le contrôle qualité en fabrication additive (FA), y compris la description d'une procédure.
En outre, le présent document comprend des actions que les utilisateurs doivent exécuter pour enregistrer des données FA multimodales et les stocker dans un répertoire approprié.
Le présent document ne s'applique pas au nettoyage de données, à l'étalonnage du capteur et au traitement d'images.
Le présent document ne s'applique qu'aux données recueillies et générées à partir de méthodes d'essai non destructifs et de capteurs, par exemple, tomodensitométrie (TDM), les capteurs thermiques, les caméras et les machines à mesurer tridimensionnelles (MMT).
Le présent document ne s'applique qu'aux pièces métalliques produites par fusion laser sur lit de poudre (PBF-LB); néanmoins, les procédures décrites dans le présent document peuvent être appliquées pour surveiller d'autres procédés et matériaux de FA (par exemple, le dépôt de matière sous énergie concentrée, la fusion sur lit de poudre polymère ou céramique, la projection de liant, et la photopolymérisation), mais le présent document ne fournit aucune donnée ni étude de cas à leur sujet.
Dodajalna izdelava kovinskih izdelkov - Splošna načela - Registracija podatkov, pridobljenih pri spremljanju procesa in za kontrolo kakovosti (ISO/ASTM 52953:2025)
Ta dokument določa in opredeljuje minimalne zahteve za registracijo podatkov, pridobljenih pri spremljanju procesa in za kontrolo kakovosti v dodajalni izdelavi (AM), vključno z opisom postopka. Poleg tega ta dokument vključuje dejanja, ki jih morajo uporabniki izvesti za registracijo večmodalnih podatkov o dodajalni izdelavi in njihovo shranjevanje v ustrezno skladišče. Ta dokument se ne uporablja za čiščenje podatkov, kalibracijo senzorjev in obdelavo slik. Ta dokument se uporablja samo za podatke, zbrane in ustvarjene z neporušitvenimi preskusnimi metodami in senzorji, npr. rentgensko računalniško tomografijo (XCT), toplotnimi senzorji, kamerami ter koordinatnimi merilnimi stroji (CMM). Ta dokument se uporablja samo za kovinske dele, izdelane z lasersko fuzijo kovinskih prahastih plasti (PBF-LB); kljub temu je mogoče postopke, opisane v tem dokumentu, uporabiti za nadzor drugih procesov in materialov dodajalne izdelave (npr. usmerjeno nanašanje materiala z energijo, fuzija polimernih ali keramičnih prahastih plasti, brizganje veziva in fotopolimerizacija), vendar ta dokument ne vsebuje nobenih podatkov ali študij primerov zanje.
General Information
Standards Content (Sample)
SLOVENSKI STANDARD
01-november-2025
Dodajalna izdelava kovinskih izdelkov - Splošna načela - Registracija podatkov,
pridobljenih pri spremljanju procesa in za kontrolo kakovosti (ISO/ASTM
52953:2025)
Additive manufacturing for metals - General principles - Registration of data acquired
from process monitoring and for quality control (ISO/ASTM 52953:2025)
Additive Fertigung von Metallen - Allgemeine Grundsätze - Registrierung von Daten aus
der Prozessüberwachung und zur Qualitätskontrolle (ISO/ASTM 52953:2025)
Fabrication additive de métaux - Principes généraux - Enregistrement de données
acquises à partir de la surveillance du procédé et pour le contrôle qualité (ISO/ASTM
52953:2025)
Ta slovenski standard je istoveten z: EN ISO/ASTM 52953:2025
ICS:
25.030 3D-tiskanje Additive manufacturing
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
EN ISO/ASTM 52953
EUROPEAN STANDARD
NORME EUROPÉENNE
August 2025
EUROPÄISCHE NORM
ICS 25.030
English Version
Additive manufacturing for metals - General principles -
Registration of data acquired from process monitoring and
for quality control (ISO/ASTM 52953:2025)
Fabrication additive de métaux - Principes généraux - Additive Fertigung von Metallen - Allgemeine
Enregistrement de données acquises à partir de la Grundsätze - Registrierung von Daten aus der
surveillance du procédé et pour le contrôle qualité Prozessüberwachung und zur Qualitätskontrolle
(ISO/ASTM 52953:2025) (ISO/ASTM 52953:2025)
This European Standard was approved by CEN on 15 August 2025.
CEN members are bound to comply with the CEN/CENELEC Internal Regulations which stipulate the conditions for giving this
European Standard the status of a national standard without any alteration. Up-to-date lists and bibliographical references
concerning such national standards may be obtained on application to the CEN-CENELEC Management Centre or to any CEN
member.
This European Standard exists in three official versions (English, French, German). A version in any other language made by
translation under the responsibility of a CEN member into its own language and notified to the CEN-CENELEC Management
Centre has the same status as the official versions.
CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,
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Poland, Portugal, Republic of North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and
United Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION
EUROPÄISCHES KOMITEE FÜR NORMUNG
CEN-CENELEC Management Centre: Rue de la Science 23, B-1040 Brussels
© 2025 CEN All rights of exploitation in any form and by any means reserved Ref. No. EN ISO/ASTM 52953:2025 E
worldwide for CEN national Members.
Contents Page
European foreword . 3
European foreword
This document (EN ISO/ASTM 52953:2025) has been prepared by Technical Committee ISO/TC 261
"Additive manufacturing" in collaboration with Technical Committee CEN/TC 438 “Additive
Manufacturing” the secretariat of which is held by AFNOR.
This European Standard shall be given the status of a national standard, either by publication of an
identical text or by endorsement, at the latest by February 2026, and conflicting national standards
shall be withdrawn at the latest by February 2026.
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. CEN shall not be held responsible for identifying any or all such patent rights.
Any feedback and questions on this document should be directed to the users’ national standards
body/national committee. A complete listing of these bodies can be found on the CEN website.
According to the CEN-CENELEC Internal Regulations, the national standards organizations of the
following countries are bound to implement this European Standard: Austria, Belgium, Bulgaria,
Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland,
Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of
North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and the
United Kingdom.
Endorsement notice
The text of ISO/ASTM 52953:2025 has been approved by CEN as EN ISO/ASTM 52953:2025 without
any modification.
International
Standard
ISO/ASTM 52953
First edition
Additive manufacturing for metals —
2025-08
General principles — Registration
of data acquired from process
monitoring and for quality control
Fabrication additive de métaux — Principes généraux —
Enregistrement de données acquises à partir de la surveillance du
procédé et pour le contrôle qualité
Reference number
ISO/ASTM 52953:2025(en) © ISO/ASTM International 2025
ISO/ASTM 52953:2025(en)
© ISO/ASTM International 2025
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
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© ISO/ASTM International 2025 – All rights reserved
ii
ISO/ASTM 52953:2025(en)
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative reference . 1
3 Terms, definitions and abbreviated terms . 1
3.1 Terms and definitions .1
3.2 Abbreviated terms .2
4 Significance and use . 3
5 Data registration procedure . 3
6 Sensor categorization and metadata items . 4
6.1 Sensor categorization .4
6.2 Metadata in in-situ measurement .4
6.2.1 Laser-scanning-related data elements .4
6.2.2 Layer-wise images .5
6.2.3 Registering melt pool monitoring images .6
6.3 Ex-situ XCT measurements metadata elements .7
6.4 Sources of uncertainty .7
7 Data alignment with coordinate system transformations . 8
7.1 General .8
7.2 Methodology overview .8
7.3 Melt pool image, scan path, and layer-wise image alignment .10
7.3.1 General .10
7.3.2 Melt pool image to scan path alignment.10
7.3.3 Scan path to build platform alignment . 12
7.3.4 Layer-wise image to the build platform alignment . 13
7.4 Layer-wise images alignment.14
7.5 Layer-wise images to the related XCT model alignment . 15
7.6 CMM Model to CAD model alignment .16
7.7 Global coordinate system .17
Annex A (informative) Sensors and inspection systems categorization .18
Annex B (informative) Examples of candidate global coordinate systems .21
Annex C (informative) Edge fitting .22
Bibliography .24
© ISO/ASTM International 2025 – All rights reserved
iii
ISO/ASTM 52953:2025(en)
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out through
ISO technical committees. Each member body interested in a subject for which a technical committee
has been established has the right to be represented on that committee. International organizations,
governmental and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely
with the International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types
of ISO document should be noted. This document was drafted in accordance with the editorial rules of the
ISO/IEC Directives, Part 2 (see www.iso.org/directives).
ISO draws attention to the possibility that the implementation of this document may involve the use of (a)
patent(s). ISO takes no position concerning the evidence, validity, or applicability of any claimed patent
rights in respect thereof. As of the date of publication of this document, ISO had not received notice of (a)
patent(s) which may be required to implement this document. However, implementers are cautioned that
this may not represent the latest information, which may be obtained from the patent database available at
www.iso.org/patents. ISO shall not be held responsible for identifying any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
related to conformity assessment, as well as information about ISO's adherence to the World Trade
Organization (WTO) principles in the Technical Barriers to Trade (TBT), see www.iso.org/iso/foreword.html.
The committee responsible for this document is ISO/TC 261, Additive manufacturing, in cooperation with
ASTM Committee F42, Additive Manufacturing Technologies, on the basis of a partnership agreement
between ISO and ASTM International with the aim to create a common set of ISO/ASTM standards on
Additive Manufacturing, in collaboration with the European Committee for Standardization (CEN) Technical
Committee CEN/TC 438, Additive manufacturing, in accordance with the Agreement on technical cooperation
between ISO and CEN (Vienna Agreement).
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.
© ISO/ASTM International 2025 – All rights reserved
iv
ISO/ASTM 52953:2025(en)
Introduction
Additive manufacturing (AM) is the general term for those technologies that successively join material to
create physical objects as specified by their 3D design model data. Current AM technologies can fabricate
parts layer-by-layer using different material types as inputs. The resulting parts have complex geometries
that are needed for applications in a variety of manufacturing industries, where AM parts offer significant
advantages or where the parts cannot be made using the traditional manufacturing technologies, such as
machining and welding.
AM machines are being instrumented with various types of sensors which collect data throughout a build.
Often, each sensor is designed to collect only one type of measurement dataset in a unique coordinate
system. The use of this monitoring data for applications such as qualifying AM components is enhanced
when a diverse range of sensor datasets are used and compared to post-process inspection. This requires
multi-modal dataset registration including data alignment.
Registration of these datasets consists of recording necessary metadata and data alignment. A registered
dataset allows the extraction of features from data from different sensors to be appropriately registered to
post-process inspection. These features can be used for a range of applications including to control variations
in feedstock, melt-pool geometry, thermal stability, layer integrity, defect detection, and part quality.
It is the intention of this document to provide a procedure and methods to register AM data, including:
a) associating validated data with known time, locations, and origin, and
b) data alignment for process monitoring and control.
Laser-based powder bed fusion for metals (PBF-LB/M) is used to demonstrate the data registration
procedure. The procedure can be applied to monitor other AM processes, such as direct energy deposition,
polymer or ceramic powder bed fusion, binder jetting, and photopolymerization.
© ISO/ASTM International 2025 – All rights reserved
v
International Standard ISO/ASTM 52953:2025(en)
Additive manufacturing for metals — General principles —
Registration of data acquired from process monitoring and
for quality control
1 Scope
This document sets and defines the minimum requirements for registration of data acquired from process
monitoring and for quality control in additive manufacturing (AM), including the description of a procedure.
Furthermore, this document comprises actions that users shall execute to register multi-modal AM data and
store them in an appropriate repository.
This document is not applicable for data cleansing, sensor calibration, and image processing.
This document is only applicable for data gathered and generated from non-destructive test methods
and sensors, e.g. X-ray computer tomography (XCT), thermal sensor, cameras and coordinate measuring
machines (CMM).
This document is only applicable to metallic parts produced by means of laser-based powder bed fusion
(PBF-LB); nevertheless, the procedures described in this document can be applied to monitor other AM
processes and materials (e.g. directed energy deposition, polymer or ceramic powder bed fusion, binder
jetting, and photopolymerization), but this document does not provide any data or case studies for them.
2 Normative reference
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO/ASTM 52900, Additive manufacturing — General principles — Fundamentals and vocabulary
3 Terms, definitions and abbreviated terms
For the purposes of this document, the terms and definitions given in ISO/ASTM 52900 and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1 Terms and definitions
3.1.1
data alignment, noun
process of transforming different sets of geometrically or temporally related data into a single, global
coordinate system
3.1.2
data registration, noun
procedure of aligning data, recording metadata, and assigning a persistent identification to the aligned data set
© ISO/ASTM International 2025 – All rights reserved
ISO/ASTM 52953:2025(en)
3.1.3
digital imaging sensor, noun
detection device, usually photoelectric, that captures photographic images of an object in a digital format
Note 1 to entry: It is also called a digital, visible-light-imaging sensor.
3.1.4
ex-situ inspection, noun
measurement or examination performed on the part after it is extracted from the build chamber
3.1.5
fiduciary mark, noun
physical mark on a build plane or a layer to locate the scan tracks relative to the image coordinate system
3.1.6
global coordinate system, noun
unique coordinate system to which all the data is referenced
3.1.7
in-situ measurement, noun
measurement performed on the part during the build cycle
3.1.8
staring camera, noun
camera that is installed in a staring configuration used for layer-wise imaging or melt-pool imaging
3.1.9
layer image, noun
image of the layer taken by an image sensor, e.g., staring camera
Note 1 to entry: Other sensors that can be used include multi-colour pyrometer for taking thermal images, 3D scan by
triangulation, interferometry, and confocal microscopy.
3.1.10
melt pool image, noun
image of melt pool taken by either a coaxial camera or a staring camera.
3.1.11
X-ray computer tomography three-dimensional model
three-dimensional (3D) model constructed using sets of two-dimensional (2D) images of an X-ray Computed
Tomography (XCT)-scanned part.
3.2 Abbreviated terms
2D Two-dimensional
3D Three-dimensional
CAD Computer-aided design
CCD Charge-coupled device
CMOS Complementary metal oxide semiconductor
CS Coordinate system
HSI Hyperspectral imaging
ID Identification
LIPS Laser-induced plasma spectroscopy
© ISO/ASTM International 2025 – All rights reserved
ISO/ASTM 52953:2025(en)
LUS Laser-induced ultrasonic
LZW Lempel–Ziv–Welch
MPE Maximum permissible error
OCT Optical coherence tomography
SD Sphere distance
TIFF Tag image file format
XCT X-ray computed tomography
4 Significance and use
This document provides methods and procedures for users to register measurements and associated
metadata that they need for accurately qualifying complex metal additive manufacturing (AM)-built parts.
Registered data can satisfy additional user’s goals: detect AM processing instabilities, predict their impact
on the part quality, and implement process control if needed and possible. Registered data can be from the
following methods: in-situ photogrammetry, thermography, pyrometry, ex-situ XCT, CAD models and the
associated metadata. These data sets are generated from a variety of sources, e.g., melt-pool images, thermal
measurements, scan paths, layer images, and 3D models based on XCT.
This document enables the development of data registration software. The software can help users register
the data needed to validate the AM system states, optimize process parameters, and control part quality.
Data analytics and control software can be modified to use registered data extensively from a wide range of
measuring instruments.
5 Data registration procedure
As shown in Figure 1, the data registration procedure shall start with capturing metadata, which has the
information about sensors and their settings (see Clause 6). Then, in-situ and ex-situ sensing, data cleansing,
and assigning identification to data shall occur in that exact sequence. Data identifiers should be assigned
according to ISO/IEC 9834-8 or a company-specific scheme. Data alignment includes both temporal and
spatial alignment. Spatial alignment shall convert sensor data from its original, local coordinate system to
a global coordinate system in which all the data can be compared and fused correctly. Aligned data sets are
used as inputs to data analytics software that makes predictions needed for decision making and control.
Although data cleansing is out of scope, it can be a part of data registration.
Some examples of data cleansing in an image include, but are not limited to, correction of scaling because of
perspectives, correction of distortion because of lens geometry, handling of insensitive/dead pixels, offset
gain from laser speckles, denoising, and gamma correction. Image processing is out of scope.
© ISO/ASTM International 2025 – All rights reserved
ISO/ASTM 52953:2025(en)
Figure 1 — General data registration procedure
6 Sensor categorization and metadata items
6.1 Sensor categorization
For developing a data registration procedure, a categorization of the current use of sensors for in-situ
monitoring and ex-situ inspection is included in this clause. For more details, see Annex A. XCT coordinate
measuring machines as ex-situ measurement instruments are also included in Annex A.
6.2 Metadata in in-situ measurement
6.2.1 Laser-scanning-related data elements
Laser-scanning-related data elements shall provide spatial references for the spatial alignment of in-situ
measurements from different sensors. The scanning strategy registration method, which is process oriented,
is based on the scan, laser-spot positions, laser power, and camera-trigger timing. This method shall be used
primarily to register the position and the time when the image is taken by a camera. Required data elements
are shown in Table 1.
Table 1 — Laser-scanning-related metadata elements for registration
Data element Description
Machine ID Unique identification of the AM machine.
Build ID Unique identification of the associated build.
Part ID Unique identification of the associated part.
Scanning ID Unique identification of the associated scan in the build.
Layer number The part layer number.
Command time, t The time that a position command is sent.
Scan positions (X , Y ) The commanded location of the laser beam, i = 1 .n. Optional with Laser on or off at the scan
i i
position. If laser is on, the laser power (W) shall be specified.
© ISO/ASTM International 2025 – All rights reserved
ISO/ASTM 52953:2025(en)
TTaabbllee 11 ((ccoonnttiinnueuedd))
Data element Description
Melting laser beam ID The identification of the melting laser beam in a multi-laser beam system that the measure-
ment is associated with if a multi-laser beam system is used. If it is a single melting laser beam
system, this data element is not needed.
Programmed scanning The speed of laser beam as programmed in the scanning command file.
speed, V (mm/s)
Actual scanning speed (A The speed of laser beam calculated from the actual galvanometer positions and the sampling
mm/s) (optional) time. A is optional if programmed scanning speed (V) is sufficient.
Exposure time (t ) The camera exposure time (s).
expo
For general metadata registration, see ISO/IEC 11179-4, F3049, and SAE AMS 7003 for laser-based powder
bed fusion processes. For a sensor networking standard, see ISO/IEC 20005. AM metadata formats can be
[10]
found in ASTM F3490. Some general metadata format can be found in OCG Sensor ML .
6.2.2 Layer-wise images
When layer-wise images are used in monitoring the build of a layer, stacks (or folders) of such 2D images
shall be registered using the data elements in Table 2. Such stacks effectively describe a volume dataset.
One or more optical images can be acquired for pre-scanned or post-scanned powder layer(s). Metadata that
is the same for each image shall not be repeatedly registered for each image.
Table 2 — Layer-wise image metadata elements for registration
Data element Description
Image Name The name of the image or video.
Image ID Unique ID number of the image or video
Layer number The layer number of this image (potentially the same as image ID). The layer number 0 shall
be assigned to the base plate and layer number 1 to the first layer of powder spreading.
Time (s) The time that the image was taken with respect to the scan starting time.
o
Build chamber environ- The following factors shall be reported Temperature of the build in thermal equilibrium, (
mental factors C). Humidity (g/cm ), Oxygen concentration (%), and pressure (mmHg, hPa).
Flash condition If external lighting is used, a description of the lighting orientation with respect to machine CS
Sensor ID The identification of the image sensor.
Sensor description Sensor type (for example, InSb, CMOS, photodiode), purchase date, wavelength ranges, lens
distortion information, and other specifications, including filters and excitation sources
(see Table A.6).
Sensor calibration infor- The date of calibration, type, and method of calibration, for example, perspective transfor-
mation mations, pixel scale, and scaling of intensity values from original bit depth.
Data type (or Bit depth) The number of levels on greyscale or colour scale, for example, 8 bits, specifying the number
of computationally possible intensity levels.
Compression informa- Information about compression applied in the file format, for example, TIFF and LZW.
tion
Image size Post-calibration shape of image, in pixel numbers in both X and Y in the local CS. Height of
image is assumed to correspond to the depth of the build plate, as first approximation (note
offsets below).
Actual thickness of lay- Vertical spacings between images of the stack. If actual spacings are used, they shall be
ers imaged confirmed by a calibration process, especially as build layer thickness may be different from
powder layer thickness; therefore, the spacings between images of layer and the spacings
between images of build may be different. If a predefined thickness of layers is used, it should
be so noted.
Layer thickness multi- Not every built layer needs to be imaged. When this is the case, a multiplier (>1) of the nominal
pliers thickness shall be assigned. The multiplier shall be an integer.
© ISO/ASTM International 2025 – All rights reserved
ISO/ASTM 52953:2025(en)
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Data element Description
Rotational offsets to The three angles accounting for possible angular misalignment of (remapped) camera (local)
build coordinate system CS and the build plate CS, potentially to be determined by a calibration process.
Translational offsets to Linear offsets accounting for possible differences of camera CS origin and build plate CS
build coordinate system origin, including those caused by potential use of an imaging region of interest or support
structures under parts. Potentially to be determined by a calibration process.
Estimated positional The error of positions specified, reflecting, for example, the results of a standard geometric
uncertainty calibration process.
Estimated intensity The error of intensities specified, reflecting, for example, the results of a standard sensor
uncertainty noise and intensity calibration process.
Method of uncertainty Description of the approach adopted for estimating positional and intensity uncertainty
estimation
The data elements in Table 2 relate to the data from the camera system after calibration provided by the vendor.
Details of the calibration routines are out of scope of this document given that the focus of this document is
on aiding AM users.
An integrator setting up a camera to observe the build shall preprocess the raw camera outputs to provide
the data elements as outlined in Table 2.
Details of the calibration routines will inevitably impact the pixel-wise uncertainty estimates, and they
should be assessed for the data registration. Such a detailed assessment is out of scope because fully and
generically specifying inputs to obtain holistic uncertainty estimates is not the focus of this document.
A first-order uncertainty estimate should, however, be obtainable from the included uncertainty estimate-
related data elements. See 6.4.
6.2.3 Registering melt pool monitoring images
Melt pool monitoring images are usually still as individual video frames, acquired by a high-speed (frames/s)
camera that can capture thousands of images per layer depending on the area. Images are usually stored in
an electronic folder. Required data elements for registration are in Table 3. In a multi-laser beam scanning
system, each melting laser beam has a specific area to scan. The melting laser beam shall be uniquely
identified. The scanning time shall be referred to the scanning starting time of the multi-laser beam system.
Table 3 — Melt pool monitoring metadata elements for registration
Data element Description
Image name The name of the image.
Image ID A unique identification number of the image.
Triggering time The time when the camera is being triggered to take the picture, based on the scanning
commands for example, programmed in comma-separated values (csv) format.
Sensor ID The identification of the image sensor.
Sensor description Sensor type (for example, InSb, CMOS, photodiode), purchase date, wavelength ranges, lens
distortion information, and other specifications, including filters and excitation sources
(see Table A.6).
Sensor installation Installed date, installer.
Sensor configuration ID Identification of the sensor configuration (coaxial or staring).
Field of view The viewing area (mm × mm) in the machine CS.
Window size Size of the window on the detector (pixels × pixels)
Cropped (y/n)
If yes, define four corners of the area of interest.
Pixel pitch The width of a pixel (nm/pixel).
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TTaabbllee 33 ((ccoonnttiinnueuedd))
Data element Description
Magnification Magnification factor.
Data type (bit depth) The number of grayscale levels, for example, 16 bits.
Optical filter bandwidth Minimum and maximum wavelengths in nm.
Gamma correction The magnitude of the gamma correction in the image section.
Sensor calibration infor- The date of calibration, the method of calibration, person who performed the calibration,
mation and the calibration data.
6.3 Ex-situ XCT measurements metadata elements
Using XCT-scanned images (2D projections), a 3D model shall be reconstructed to represent the additively
manufactured part for detecting pores and internal feature dimensions. The XCT data elements are listed in
Table 4.
Table 4 — XCT metadata elements for registration
Data element Description
XCT scanner ID The identification of the XCT hardware used.
Source ID The identification of the XCT source used (for multi-source systems).
Detector ID The identification of the XCT detector used (for multi-detector systems).
Scan ID The identification of the XCT scan.
Volume ID The identification of the reconstructed volume (may be same as scan ID).
Part ID(s) The ID(s) of the part(s) imaged.
Time and date stamp Indication of when the scan was completed (supports traceability of stage of manufacturing
process chain during which scan was completed).
Voltage (V) The accelerating voltage in the XCT tube.
Current (A) The accelerating current in the XCT tube.
°
Sample temperature Temperature of sample in scanner, relevant if deviating from standard 20 C.
XCT scanner geometric As a high-level indication of geometric conformance of generated data volumes, maximum
specification, MPE permissible error (MPE), see ISO/IEC Guide 99.
System calibration infor- The date of calibration, reference artifact used, its date of last reference measurement, plus
mation limits of calibration validity for scan completed.
Geometric uncertainty If available, estimate of anticipated measurement uncertainty, describing method applied
estimate (noting this is an area of ongoing research and standardization efforts, for example, based
on ISO 15530-3).
Data type (bit depth) The number of grayscale levels, for example, 16 bits.
Compression information Information, if relevant, about compression applied in the file format, for example, TIFF and
LZW.
Volume height, width, and Shape of volume in numbers of pixels.
depth
Axes order Row major or column major for 1D data formats.
Voxel size (scaled volu- Physical extent of 3D pixels.
metric pixel size)
Slice thickness (µm) If the fan beam is applied, the thickness of a scan. The scan plane shall be placed in the middle
of the slice.
6.4 Sources of uncertainty
There is always uncertainty in the data collected from sensors. Some key sources of uncertainty for the
described data sources are summarized in Table 5.
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ISO/ASTM 52953:2025(en)
Table 5 — Non-exhaustive list of uncertainty sources
Sensor type Uncertainty source
Camera — View angle variation because of installation.
— Magnification factor variation because of the viewing angle.
— Field of view because of viewing angle.
— Variation in the focus of lens.
— Changes in the optics (altering, changing focus, and/or iris because of vibrations if they
are not fixed).
— Mounting during installation and remounting in case of maintenance.
— In case of coaxial imaging, two possible uncertainty sources: (1) focal shift in Z axis de-
pending on wavelength sensitivity of the camera compared to the laser wavelength (that is,
chromatic aberration in Z direction) and (2) chromatic aberration in X or Y directions or both
depending on spectral sensitivity of the camera compared to the laser wavelength including
rotation of the image.
— Geometric correction (calibration procedure of the camera, for example, extrinsic and
intrinsic matrices).
XCT scanner Factors affecting geometry of voxels:
— Detector tilts
— Detector curvature
— Rotation axis misalignments
— Source focus drift
Factors affecting determination of edges in volume:
— Beam hardening
— Scattering of X-rays
— Image noise
— Streaking artifacts because of photon starvation
Laser spot
— Will change over time as temperature changes
— Wrong positions sent to scanner to overcome optical distortions and in time.
— The optical distortions will change over time as temperature changes.
Galvo scanner — The actual laser spot position in the X and Y directions relative to the build plate coordi-
nates in the X and Y directions can deviate from the command position.
— Can deviate from the command position as temperature changes
Melt pool image — The laser spot is moving while the camera is taking a picture. Melt pool keeps changing
during the exposure. Uncertainty shall be embedded in the shape, size, and intensity of the
melt pool image.
7 Data alignment with coordinate system transformations
7.1 General
Each sensor dataset resides in its own, local coordinate system (CS). Related sensor datasets and their local
CS shall be transformed into a single, common CS. This coordinate transformation is called data alignment.
7.2 Methodology overview
The methodology to align datasets in different CSs requires both a data registration procedure and
coordinate transformation methods. The data registration procedure includes the following three steps:
a) Identify the precedence relations between two different datasets and choose the common Cartesian CS
to which they shall be registered.
b) For each dataset, define both the datum features and precedence relations to be registered. Datum
features are used to establish a datum reference frame for the common, Cartesian CS. Precedence can
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ISO/ASTM 52953:2025(en)
be primary datum, secondary datum, tertiary datum, etc. A datum feature is preferred for stability. If it
is unstable, one datum or a range of possible datums shall be chosen by the user to fit the need.
c) Use the datum features with their precedence to establish the common CS. The dataset can then be
transferred from its local CS to the common, Cartesian CS by applying a mathematical coordinate
transformation.
Specifically, this clause provides the dataset transformations among in-situ and ex-situ datasets to establish
a chain of relationships that are described in Figure 2.
Key
7.3.1 to 7.6 subclause numbers
Figure 2 — Datasets and coordinate systems
The procedure for in-situ datasets alignment is described in 7.3. The procedure shall include these steps:
a) aligning a melt pool image to scan path CS alignment as described in 7.3.1
b) aligning the scan path CS to the laser-beam CS to the build-platform CS as in 7.3.2
c) aligning layer-wise image with the build platform CS as in 7.3.3
d) aligning individual, layer-wise images into a stack of images as in 7.4
e) aligning layer-wise-image stack to the XCT model as in 7.5
f) aligning a CMM model to the XCT model as in 7.6. Both XCT and CMM models are results from ex-situ
inspection.
Melt pool images, scan paths, and layer-wise image stack are results from in-situ measurements. Both in-
situ and ex-situ datasets are aligned. The CAD model shall be used to identify datum features and needed
geometric features used for dataset alignment.
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ISO/ASTM 52953:2025(en)
7.3 Melt pool image, scan path, and layer-wise image alignment
7.3.1 General
This clause provides guidance to establish coordinate transformations:
a) relate the melt pool images CS to the scan path CS
b) relate the laser CS to the build platform CS
c) relate a layer-wise imaging CS to the build platform CS
The locations and directions of melt pool images are based on the scan command. The locations and
directions of scanning commands to heat the powders are executed by the positioning system. Since the
scanning is on the build plate, the laser CS is related to the build plate CS. The layer-wise image is on the
layer-wise imaging camera CS. The layer-wise image is an image of the scanned layer on the build plate. The
layer-wise image CS relates to the build plate CS.
7.3.2 Melt pool image to scan path alignment
The alignment of melt pool images with the scan path is shown in Figure 3. The centre of the heat source,
that is, laser spot, should be used as the reference point in the alignment. The point on the image taken with
a coaxial camera is in the image CS. The centre of the laser spot on the scan path is in the scanning laser CS.
There are at least three ways to describe a scan path:
[12]
a) the command position in the XY2-100 or G-code file
b) the intercepted encoder position of the positioning system, and
c) using an interpretation method to predict the true laser position based on the scanning speed.
The command position and the laser spot centre position are different. Motion blur can show up in the image.
Usually, it is small and negligible.
The location of heat source on the image can be determined in the following two methods. The first is to
use the laser to burn a circular mark on the build plate. The centre of the mark on the image indicates the
centre of the heat source in the image coordinate system. The second method is to predict the centre using
the hottest point or area on the image. If the area method is used, the centre of the area is the centre of the
heat source.
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