Work

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

Year: 2026

Type: article

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 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 large-scale hybrid manufacturing case study with sparsely distributed machining segments, illustrating interaction between spatial sequencing, temporal feasibility and disturbance-aware optimisation under stated assumptions. The framework is methodological and provides a transferable foundation for future development and validation of disturbance-aware planning strategies for concurrent additive-subtractive manufacturing.

Source: Journal of Manufacturing and Materials Processing

DOI: 10.3390/jmmp10050158

Authors: Jan Schachtsiek, Bernd Kuhlenkötter

Institution: Ruhr University Bochum

Language: English

Topic: Manufacturing Process and Optimization

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,172

Funder: Deutsche Forschungsgemeinschaft