ISO/DTR 23247-101

ISO/TC 184/SC 4/WG 15
Secretariat: ANSI
Date: 2025-10-302026-01-26
Automation systems and integration — Digital twin framework
for manufacturing — —
Part 101:
Use case on management of robotic multilayer and multipass gas-
shielded metal arc welding process
Cas d'usage sur la gestion du procédé de soudage à l'arc avec fil métallique et protection gazeuse robotisé
multicouche et multi-passes
DTR stage
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ISO #####-#:####(X/DTR 23247-101:(en)
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© ISO #### 2026 – All rights reserved
iv
Contents
Foreword . vi
Introduction . vii
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Overview . 2
5 Operational sequences . 6
5.1 Process flow . 6
5.2 Phase 1: Select and provisioning . 7
5.3 Phase 2: Welding preprocessing . 8
5.4 Phase 3: Welding operation . 8
5.5 Phase 4: Inspection and operations after welding . 9
5.6 Phase 5: Document . 9
6 Mapping to the framework . 10
6.1 Overview . 10
6.2 Implementation using the framework . 12
6.3 Mapping of the process digital twin to the digital twin entity . 14
6.4 Mapping of the welding equipment digital twin to the digital twin entity . 16
6.5 Mapping of the workpiece digital twin to the digital twin entity . 18
7 Conclusion . 20
Bibliography . 21

v
ISO #####-#:####(X/DTR 23247-101:(en)
Foreword
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bodies (ISO member bodies). The work of preparing International Standards is normally carried out through
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The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1Part 1. In particular, the different approval criteria needed for the different
types of ISO documentsdocument should be noted. This document was drafted in accordance with the editorial
rules of the ISO/IEC DirectivesIEC Directives, Part 2Part 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
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This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration,
Subcommittee SC 4, Industrial data.
A list of all parts in the ISO 23247 series can be found on the ISO website.
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 #### 2026 – All rights reserved
vi
Introduction
The multilayer and multipass gas-shielded metal arc welding is a critical process for thick plate welding, which
is widely used in the welding of large metal structures in engineering machinery, ships, aerospace and other
fields.
Although robotic technology has enhanced automation, reduced manual intervention, and improved quality
in multilayer and multipass gas-shielded metal arc welding, the process remains challenging for highly
customized, large-scale workpieces such as tunnel boring machine cutterheads. Key issues include reliance on
manual parameter optimization and insufficient real-time process control, leading to poor adaptability,
inconsistent weld quality, and unplanned downtime.
A digital twin of robotic multilayer and multipass gas-shielded metal arc welding can effectively address these
challenges. By simulating and optimizing the entire process in a virtual environment, it reduces reliance on
manual experience and enables real-time monitoring, early warning, and dynamic adjustment of welding
parameters. This significantly enhances welding quality control and process stability.
The application of a digital twin for monitoring and controlling the robotic multilayer and multipass gas-
shielded metal arc welding offers the following advantages:
— Monitoring and Early Warningearly warning: A digital twin facilitates continuous real-time monitoring of
the welding process, displaying key parameters— - such as current, voltage, travel speed, and molten pool
state— - and triggers immediate alerts upon anomaly detection to prompt corrective operator actions.
— Process parameter optimization: A digital twin can analyzeanalyse the influence of groove forms (e.g.,. V-
groove, J-groove) and their geometry parameters on stress, heat input, and deformation to optimize
selection and design. Additionally, it monitors weld quality and joint characteristics layer-by-layer,
enabling predictive optimization of subsequent welding parameters.
— Process plan optimization: A digital twin can evaluate the deformation and residual stress under various
welding sequences to identify the optimal welding sequence scheme. Using sensor-derived deformation
data, it also simulates straightening strategies to determine the most effective pressure, temperature, and
positioning parameters.
— Predictive maintenance of equipment: A digital twin enables predictive maintenance of welding
equipment by continuously monitoring and analyzinganalysing its operational status. This allows for early
detection of potential faults, facilitating proactive interventions that minimize unplanned downtime.
— Training and simulation: A digital twin supports operator and engineer training through a virtual
environment that simulates diverse welding scenarios without physical equipment, improving skills,
enabling solution testing, and enhancing risk response capabilities.
A digital twin enhances precision in monitoring and optimizing the robotic multilayer and multipass gas-
shielded metal arc welding process, reducing defects and facilitating intelligent management of the full
workflow. By leveraging this technology, manufacturers achieve deeper process insight, improved parameter
optimization, strengthened quality control, and enhanced overall productivity and efficiency.
This document is structured into an overview, operational sequences, framework mapping, and a conclusion.
Following the ISO 23247 series, the use case analysis yields a systematic implementation view and a high-level
digital twin design, ready for direct implementation with standard-compliant tools and languages.
vii
ISO/PWIDTR 23247-101:2025(:(en)
Automation systems and integration — Digital twin framework for
manufacturing — —
Part 101:
Use case on the management of robotic multilayer and multipass gas-
shielded metal arc welding processesprocess
1 Scope
This document describes a digital twin system for monitoring and managing the robotic multilayer and
multipass gas-shielded metal arc welding process.
2 Normative references
There are no normative references in this document.
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 23247-1, Automation systems and integration — Digital twin framework for manufacturing — Part 1:
Overview and general principles
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 23247-1 and the following apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp
Field Code Changed
— IEC Electropedia: available at https://www.electropedia.org/
Field Code Changed
3.1 3.1
welding
joining process in which two or more parts are united producing a continuity in the nature of the workpiece
material(s) by means of heat or pressure or both, and with or without the use of filler material
3.2 3.2
gas-shielded metal arc welding
metal arc welding using a wire electrode in which the arc and the weld pool are shielded from the atmosphere
by a shroud of gas supplied from an external source
3.3 3.3
multipass welding
a welding process in which the entire weld is completed using more than two weld passes
Note 1 to entry: The weld beads of multipass welding are usually deposited continuously within the same layer. Special
attention can be paid to adjusting welding parameters such as welding current and welding voltage to ensure the
compactness and mechanical properties of the weld joint.
3.4 3.4
multilayer welding
process whereby the weld joint is completed by depositing two or more weld layers, where each weld layer
consists of one or more weld beads
EXAMPLE Multilayer welding is typically used for thick plate welding. During the welding of shield
tunnelingtunnelling machines and their related structural components, the thickness of each weld layer is usually
controlled within the range of 3- mm to 6 mm.
Note 1 to entry: During the multilayer welding process, the welding sequence can be properly planned to avoid welding
deformation and cracks, and to ensure the compactness and mechanical properties of the weld joint.
4 Overview
Robotic multilayer and multipass gas-shielded metal arc welding is a key process for thick-plate welding of
large structural components, given its high efficiency, high precision, and excellent weld quality. In view of the
characteristics of thick-plate welding, process engineers reasonably design the groove form (e.g. the single-V
groove), groove angle, root gap, and land, and adopt a multilayer and multipass welding strategy. For example,
the root pass uses single-pass welding to ensure full root penetration, the filling passes use multipass welding
to achieve uniform groove filling, and the capping passes use multipass welding to ensure good surface
formation. Combined with precisely controlled welding parameters (such as welding current, welding voltage,
and travel speed), this strategy ensures welding quality while improving production efficiency and process
stability. The schematic diagram of the single-V groove weld and multilayer and multipass weldingiswelding
is shown in Figure 1Figure 1.
capping pass
single-V filling pass
multilayer
groove weld
root pass
Key
1 single-V groove weld
2 multilayer
3 root pass
4 filling pass
5 capping pass
© ISO #### 2026 – All rights reserved
ISO/PWIDTR 23247-101:2025(:(en)
Figure 1 — Schematic diagram of single-V groove weld and multilayer and multipass welding
With reference to the production of thick-plate structural components for shield tunnelingtunnelling
machines, the conventional procedures of the robotic multilayer and multipass gas-shielded metal arc welding
are as follows:
a) Workpiece selection and process provisioning: Operators select a welding part to be processed according
to production planning requirements, and download the welding process plan from the manufacturing
operations management (MOM) system based on the type of welding part. The plan includes the 3D model
of the welding part, material specifications, technical parameters, hardware equipment information,
operator qualifications, operating methods, and quality control requirements, ensuring that the welding
process meets product requirements and technical specifications.
b) Convert and transmit: Based on the 3D model and technical parameters in the welding process plan,
combined with the welding robot system configuration, a welding working condition environment is
constructed in the offline programming system of the upper computer. Robot instructions and programs
are generated according to the weld information and process parameters, and then issued.
c) Preparation of welding conditions: In accordance with the welding process plan, welding consumables,
the shielding gas, welding equipment, welding accessories, and jigs are selected. Meanwhile, the safety of
the working environment is confirmed, including wind protection measures, humidity control, and safety
isolation. These steps ensure that material performance, equipment functionality, and the welding
environment meet the requirements of production operations.
d) Joint preparation: Cleaning and degreasing of the appropriate area; in accordance with process
requirements, adopt process measures such as jigging, preheating and backing.
e) Program verification: Operators perform welding program verification based on the workpiece position,
weld position, and joint dimensions.
f) Welding equipment operation: Operators strictly follow the requirements of the process plan, start the
welding equipment, and the welding robot system performs the welding operation.
g) Inspection during welding: Operators conduct inspections on the root pass and capping pass, and perform
regular sampling inspections on the filling pass in accordance with process requirements.
h) Welding parameters adjustment: Based on the results of the inspection during welding, operators
promptly adjustsadjust parameters such as welding sequence, welding trajectory, and welding current to
ensure that the weld quality meets the requirements of the welding process plan.
i) Visual testing of the finished welding: The weld surface is inspected to check whether defects such as
cracks, surface pores, and undercuts deviate from the acceptance criteria.
j) Straightening: The workpiece undergoes straightening to meet the design dimensions, shape, and
assembly requirements.
k) Non-destructive testing and repair: Operators conduct non-destructive testing on the welds, repair the
welds based on the test results, and ensure that the weld quality meets the requirements of the welding
process plan.
Although robot technology has significantly improved the automation level of the multilayer and multipass
gas-shielded metal arc welding, the process still faces many challenges in the welding of highly customized
and complex large-size workpieces such as tunnel boring machine cutterheads. For example, the optimization
of welding parameters depends on manual experience, and the dynamic perception and real-time adjustment
ability of the welding process is insufficient. These problems lead to poor process adaptability, fluctuation of
welding quality, and even accidental shutdown.
A digital twin of the robotic multilayer and multipass gas-shielded metal arc welding can effectively address
these challenges. By simulating and optimizing the entire process in a virtual environment, it reduces reliance
on manual experience and enables real-time monitoring, early warning, and dynamic adjustment of welding
parameters. This significantly enhances welding quality control and process stability.
Furthermore, a digital twin enables the optimization and iterative update of robotic welding process plans for
customized products, ensuring that welding quality complies with relevant standards, improving production
efficiency, reducing operational errors, lowering production costs, and enhancing the quality and reliability of
the overall product.
Table 1Table 1 summarizes the drawbacks and advantages of the conventional robotic multilayer and
multipass welding process and the solutions offered by a digital twin.
Table 1 — Comparison of conventional robotic multilayer and multipass welding process and digital
twin solutions
Stages of robotic
multilayer and Drawbacks of the Advantages of the digital
Solutions by digital twin
multipass welding conventional method twin solution
process
Workpiece selection and The welding process plan The optimal plan is derived Iterative optimization and
process provisioning lacks a mechanism for based on past production consistent management of
iterative optimization and conditions welding process plans
unified management
Convert and transmit The functions of the Constructing a welding Integrated digital
software are limited by virtual environment and management and flexible
developers, resulting in generating the robotic function development
insufficient functional program
scalability
Preparation of welding Reliance on operator skill The status of production Precise and consistent
production elements factors check using sensor quality levels of welding
and machine vision production elements
technologies
Workpiece Process omissions and Real-time monitoring and Consistent processing
preprocessing quality degradation due to feedback for processing process leading to
manual operations process standardized outcomes
Program debugging and Reliance on operator Measurement and Reduced errors caused by
calibration measurement and verification using sensors manual operations
operation
Welding equipment Reliance on human Conducting automated Reduced the equipment's
operation judgment control and predictive downtime and
maintenance on welding maintenance costs
equipment
Inspection during Manual inspection can miss Automated inspection Efficient and reliable
welding subtle defects using machine vision and inspection process
AI
Welding parameters Reliance on operator AI-controlled parameters Higher welding quality and
adjustment experience adjustment based on real- stable
time feedback
© ISO #### 2026 – All rights reserved
ISO/PWIDTR 23247-101:2025(:(en)
Stages of robotic
multilayer and Drawbacks of the Advantages of the digital
Solutions by digital twin
multipass welding conventional method twin solution
process
Visual testing of the Reliance on human Automated inspection Higher efficiency and
finished welding operation and judgment using machine vision accuracy inspection results
Straightening Reliance on manual AI-controlled optimal Higher correction precision
experience and unstable correction plan and efficiency
precision, low efficiency
Non-destructive testing Manual judgment can miss Inspection result Higher defect detection
and repair detections and determination using rate and consistency
misjudgmentsmisjudgemen machine vision and AI
ts
Integrating a digital twin into the robotic multilayer and multipass welding process can bring significant
advantages and resolve challenges associated with conventional methodologies. It offers a more intelligent
control and optimization method, delivering better results in terms of quality, efficiency, and safety.
Table 2 describes the use case for the management of the robotic multilayer and multipass welding process
using a use case template given by ISO 23247-4:2021, Annex B.
Table 2 — Summary of the example for the management of the robotic multilayer and multipass
welding process
ID Case Number 101
Use case name Management of the robotic multilayer and multipass welding process
Application field Smart Manufacturing
Life cycle
stage(s)/phase(s) Production
coverage
Status In-operation
Scope The robotic multilayer and multipass gas-shielded metal arc welding process
The optimization of welding parameters depends on manual experience, and the
Initial (Problem)
dynamic perception and real-time adjustment ability of the welding process is
Situationproblem)
insufficient. These problems lead to poor process adaptability, fluctuation of welding
situation
quality, and even accidental shutdown.
Automated robotic multilayer and multipass welding reduces welding defects and
Objective(s)
improves welding quality
Developing a digital twin of the robotic multilayer and multipass welding process can

provide the following:
a) Developing a digital twin of the robotic multilayer and multipass welding process can
provide the following:Monitoring and Early Warningearly warning: A digital twin
facilitates continuous real-time monitoring of the welding process, displaying key
parameters— - such as current, voltage, travel speed, and molten pool state— - and
triggers immediate alerts upon anomaly detection to prompt corrective operator
Short description
actions.
b) Process parameter optimization: A digital twin can analyzeanalyse the influence of
groove forms (e.g.,. V-groove, J-groove) and their geometry parameters on stress,
heat input, and deformation to optimize selection and design. Additionally, it
ID Case Number 101
monitors weld quality and joint characteristics layer-by-layer, enabling predictive
optimization of subsequent welding
...