Overcoming synchronization challenges in machining digital twins: transpiling legacy NC dialects to enhance interoperability

Digital Twin (DT) technology is a key enabler of smart manufacturing, with extensive research devoted to virtual replicas of physical assets in both subtractive and additive processes. In this context, numerical control (NC) programs are central to synchronizing physical and virtual twins, yet they are typically based on G-code, a low-level language introduced in the 1960s. Although standardized at its core, G-code has been widely extended by CNC system developers, leading to multiple dialects and significant interoperability issues across heterogeneous machines. These differences hinder effective synchronization, particularly due to the difficulty of aligning timestamps among NC programs. This study proposes a methodology to improve synchronization and interoperability by transpiling NC dialects into a higher-level abstraction based on a comprehensive and fine-grained set of machining functions. The methodology is implemented as an extensible object-oriented framework. Validation through the successful transpilation of a legacy NC dialect demonstrates the ability to compute accurate event timelines, providing a foundation for the development of robust Digital Twins for G-code-based manufacturing processes.

Authors

Institutions

Publication Details

Journal
The International Journal of Advanced Manufacturing Technology
Published
2026-02-24
DOI
https://doi.org/10.1007/s00170-026-17723-4
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Overcoming synchronization challenges in machining digital twins: transpiling legacy NC dialects to enhance interoperability

Dalberto Dias da Costa, Francisco Ricardo Taborda Aguiar, Claudimir José Rebeyka
The International Journal of Advanced Manufacturing Technology
Digital Transformation in Industry
article

Overcoming synchronization challenges in machining digital twins: transpiling legacy NC dialects to enhance interoperability

Dalberto Dias da Costa, Francisco Ricardo Taborda Aguiar, Claudimir José Rebeyka
article en

Abstract

Digital Twin (DT) technology is a key enabler of smart manufacturing, with extensive research devoted to virtual replicas of physical assets in both subtractive and additive processes. In this context, numerical control (NC) programs are central to synchronizing physical and virtual twins, yet they are typically based on G-code, a low-level language introduced in the 1960s. Although standardized at its core, G-code has been widely extended by CNC system developers, leading to multiple dialects and significant interoperability issues across heterogeneous machines. These differences hinder effective synchronization, particularly due to the difficulty of aligning timestamps among NC programs. This study proposes a methodology to improve synchronization and interoperability by transpiling NC dialects into a higher-level abstraction based on a comprehensive and fine-grained set of machining functions. The methodology is implemented as an extensible object-oriented framework. Validation through the successful transpilation of a legacy NC dialect demonstrates the ability to compute accurate event timelines, providing a foundation for the development of robust Digital Twins for G-code-based manufacturing processes.

The International Journal of Advanced Manufacturing Technology
Enghouse Systems (Norway) (NO), Universidade Federal do Paraná (BR)
Universidade Federal do Paraná
Openalex Percentile: Top 48%
Digital Transformation in Industry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.