A Disturbance-Aware Multi-Objective Planning Framework for Concurrent Robotic Wire-Based DED-LB/M and Milling

Hybrid robotic manufacturing systems integrating additive and subtractive processes enable fabrication of complex, high-value components but are typically executed sequentially, resulting in long cycle times. Concurrent execution of Directed Energy Deposition (DED) and milling promises productivity gains but introduces coupled thermal, mechanical and spatial interactions that challenge conventional process planning. This work addresses the methodological problem of planning milling operations in the presence of an ongoing DED process. The concurrent planning task is formulated as a mixed-integer, nonlinear, multi-objective optimisation problem capturing sequencing and orientation decisions, cutting parameters and enabling temporal coupling to the deposition trajectory. A hierarchical, surrogate-assisted optimisation framework is proposed, combining unified decision-variable encoding, deterministic decoding and staged feasibility enforcement to ensure robotic executability. Disturbance mechanisms such as thermal interaction, particulate interference and pose-dependent dynamic compatibility are incorporated as modular objective abstractions, enabling systematic trade-offs between machining productivity and preservation of deposition process integrity. The proposed framework is demonstrated on a representative case study, enabling analysis of the interaction between spatial sequencing, temporal feasibility and disturbance-aware optimisation. The case study provides a controlled instantiation and illustrates its application to concurrent additive–subtractive planning under explicitly modelled temporal and disturbance constraints.

Authors

Institutions

Publication Details

Journal
Journal of Manufacturing and Materials Processing
Published
2026-04-30
DOI
https://doi.org/10.3390/jmmp10050158
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

A Disturbance-Aware Multi-Objective Planning Framework for Concurrent Robotic Wire-Based DED-LB/M and Milling

Jan Schachtsiek, Bernd Kuhlenkötter
Journal of Manufacturing and Materials Processing
Additive Manufacturing Materials and Processes
article

A Disturbance-Aware Multi-Objective Planning Framework for Concurrent Robotic Wire-Based DED-LB/M and Milling

Jan Schachtsiek, Bernd Kuhlenkötter
article en

Abstract

Hybrid robotic manufacturing systems integrating additive and subtractive processes enable fabrication of complex, high-value components but are typically executed sequentially, resulting in long cycle times. Concurrent execution of Directed Energy Deposition (DED) and milling promises productivity gains but introduces coupled thermal, mechanical and spatial interactions that challenge conventional process planning. This work addresses the methodological problem of planning milling operations in the presence of an ongoing DED process. The concurrent planning task is formulated as a mixed-integer, nonlinear, multi-objective optimisation problem capturing sequencing and orientation decisions, cutting parameters and enabling temporal coupling to the deposition trajectory. A hierarchical, surrogate-assisted optimisation framework is proposed, combining unified decision-variable encoding, deterministic decoding and staged feasibility enforcement to ensure robotic executability. Disturbance mechanisms such as thermal interaction, particulate interference and pose-dependent dynamic compatibility are incorporated as modular objective abstractions, enabling systematic trade-offs between machining productivity and preservation of deposition process integrity. The proposed framework is demonstrated on a representative case study, enabling analysis of the interaction between spatial sequencing, temporal feasibility and disturbance-aware optimisation. The case study provides a controlled instantiation and illustrates its application to concurrent additive–subtractive planning under explicitly modelled temporal and disturbance constraints.

Journal of Manufacturing and Materials ProcessingVol. 10(5)
Ruhr University Bochum (DE)
Deutsche Forschungsgemeinschaft
Decent work and economic growth
Openalex Percentile: Top 12%
Additive Manufacturing Materials and Processes
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.