Development of a New 3-Axis Force Sensor for Measuring Cutting Forces in a Lathe Machine

Despite the digital era and the emergence of simplified production paradigms enabled by digital twin technology, traditional manufacturing processes like lathe machining are invaluable because of their ability to meet various and multiple needs reliably and flexibly. To combine these processes into smart monitoring and control systems, including tool wear detection and fault diagnosis, precise multi-axis force measurement is necessary. Single-axis sensors are insufficient to measure the entire dynamics of cutting interactions. A new idea based on strain gauge technology for a self-decoupled three-axis force sensor is proposed in this paper, which aims to measure cutting forces and vibration in a lathe operation. During the cutting process, the sensor is designed to independently recognize the onset of forces at three orthogonal axes to enhance real-time process monitoring capabilities. The Timoshenko beam theory is used to design the mechanical structure, where sensitivity could be improved with minimal crosstalk. Finite element analysis (FEA) simulations were conducted to evaluate the sensor’s performance, stress distribution, modal assessments, and interference error. The interference error of 0.31 percent indicated by the results of the simulation is extremely low, indicating a successful decoupling of the force components. These encouraging simulation results indicate that there is a high possibility of applying the proposed sensor design to intelligent manufacturing systems. It presents an initial point of departure into the embodiment of sophisticated monitoring platforms for conventional machining processes, eliminating the discontinuity between old and new smart manufacturing systems.

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Publication Details

Published
2025-11-07
DOI
https://doi.org/10.3390/ecsa-12-26575
Citations
1
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.71

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article

Development of a New 3-Axis Force Sensor for Measuring Cutting Forces in a Lathe Machine

Anton Royanto Ahmad, Syed Humayoon Shah
1 citations
Advanced machining processes and optimization
0.71
article

Development of a New 3-Axis Force Sensor for Measuring Cutting Forces in a Lathe Machine

Anton Royanto Ahmad, Syed Humayoon Shah
article en
1 citations

Abstract

Despite the digital era and the emergence of simplified production paradigms enabled by digital twin technology, traditional manufacturing processes like lathe machining are invaluable because of their ability to meet various and multiple needs reliably and flexibly. To combine these processes into smart monitoring and control systems, including tool wear detection and fault diagnosis, precise multi-axis force measurement is necessary. Single-axis sensors are insufficient to measure the entire dynamics of cutting interactions. A new idea based on strain gauge technology for a self-decoupled three-axis force sensor is proposed in this paper, which aims to measure cutting forces and vibration in a lathe operation. During the cutting process, the sensor is designed to independently recognize the onset of forces at three orthogonal axes to enhance real-time process monitoring capabilities. The Timoshenko beam theory is used to design the mechanical structure, where sensitivity could be improved with minimal crosstalk. Finite element analysis (FEA) simulations were conducted to evaluate the sensor’s performance, stress distribution, modal assessments, and interference error. The interference error of 0.31 percent indicated by the results of the simulation is extremely low, indicating a successful decoupling of the force components. These encouraging simulation results indicate that there is a high possibility of applying the proposed sensor design to intelligent manufacturing systems. It presents an initial point of departure into the embodiment of sophisticated monitoring platforms for conventional machining processes, eliminating the discontinuity between old and new smart manufacturing systems.

King Fahd University of Petroleum and Minerals (SA), Yuan Ze University (TW)
Ministry of Science and Technology, Taiwan
Openalex Percentile: Top 24%
Advanced machining processes and optimization
0.71
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