A Review on Cutting Force and Thermal Modeling, Toolpath Planning, and Vibration Suppression for Advanced Manufacturing

Achieving precise prediction and intelligent control remains a pivotal challenge in cutting processes. This need is addressed through a comprehensive survey of three critical enabling technologies: cutting force/temperature modeling, tool path planning, and vibration suppression. First, the evolution of cutting force and temperature modeling is analyzed, tracing its progression from traditional analytical methods and finite-element numerical simulations to data-driven models such as machine learning (ML) and physics-informed neural networks. This analysis highlights multiphysics coupling and model–data fusion as key to enhancing prediction accuracy. Subsequently, the evolution of tool path planning is examined, showing its development from a geometric interpolation problem into a multi-objective optimization challenge incorporating dynamic constraints, involving computational geometry, graph theory, and meta-heuristic algorithms. Finally, stability analysis based on time-delay differential equations, state identification via signal processing and ML, and active control strategies for vibration suppression are discussed. In conclusion, mathematical methods are shown to be fundamentally integrated throughout the ‘perception–prediction–decision–control’ closed-loop of the cutting process. This integration provides a solid theoretical foundation and technical support for building high-performance manufacturing systems dedicated to complex curved critical components.

Authors

Institutions

Publication Details

Journal
Machines
Published
2026-01-02
DOI
https://doi.org/10.3390/machines14010060
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Review on Cutting Force and Thermal Modeling, Toolpath Planning, and Vibration Suppression for Advanced Manufacturing

Juan Song, Qingyang Jiang
Machines
Advanced machining processes and optimization
article

A Review on Cutting Force and Thermal Modeling, Toolpath Planning, and Vibration Suppression for Advanced Manufacturing

Juan Song, Qingyang Jiang
article en

Abstract

Achieving precise prediction and intelligent control remains a pivotal challenge in cutting processes. This need is addressed through a comprehensive survey of three critical enabling technologies: cutting force/temperature modeling, tool path planning, and vibration suppression. First, the evolution of cutting force and temperature modeling is analyzed, tracing its progression from traditional analytical methods and finite-element numerical simulations to data-driven models such as machine learning (ML) and physics-informed neural networks. This analysis highlights multiphysics coupling and model–data fusion as key to enhancing prediction accuracy. Subsequently, the evolution of tool path planning is examined, showing its development from a geometric interpolation problem into a multi-objective optimization challenge incorporating dynamic constraints, involving computational geometry, graph theory, and meta-heuristic algorithms. Finally, stability analysis based on time-delay differential equations, state identification via signal processing and ML, and active control strategies for vibration suppression are discussed. In conclusion, mathematical methods are shown to be fundamentally integrated throughout the ‘perception–prediction–decision–control’ closed-loop of the cutting process. This integration provides a solid theoretical foundation and technical support for building high-performance manufacturing systems dedicated to complex curved critical components.

MachinesVol. 14(1)
Suzhou City University
Openalex Percentile: Top 99%
Advanced machining processes and optimization
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.