Integrated Design of Spindle Speed Modulation and Cutting Vibration Suppression Controls Using Disturbance Observer for Thread Milling

In thread milling, there exists a trade-off between thread manufacturing efficiency and thread quality. In this study, an integrated design of spindle speed modulation (SSM) and cutting vibration suppression (CVS) controls using a disturbance observer were developed to simultaneously ensure superior quality and high manufacturing efficiency. The proposed integrated design not only controls the cutting torque while suppressing cutting vibrations but also ensures cost-effectiveness and mitigates the installation problems prevalent in existing sensor-based methods. The SSM control uses a disturbance observer to estimate the cutting torque required on the spindle during thread milling. The estimated cutting torque is used as a feedback signal so that the SSM control can modulate the spindle speed to make the cutting torque achieve a preset torque command. To further avoid cutting vibrations in thread milling, the CVS control analyzes the estimated cutting torque, detects the occurrence of cutting vibrations, and then adjusts the torque command of the SSM control to suppress the cutting vibrations. In this study, thread milling experiments were performed on a computer numerical control milling machine using the workpiece with stacked materials. The feasibility and performance of the proposed integrated design were validated by experiments.

Application of multi-sensor measurement system for machining process monitoring – a case study for sequential turning and burnishing processes

In this paper, the structure and operational functions of a measurement system, which was installed on a 3-axis CNC lathe for monitoring and optimization of the cutting process are presented. In general, the system records signals of the components of the resultant cutting force, acceleration signals (cutting vibrations) and EFM force signals generated for various machining conditions employed. As a result, the total power consumed was determined. The generated data were archived in the expert system which supports the optimization of the cutting process in terms of various optimization criteria including power/energy consumption.

Tool’s Edges Fragmentation at Gear Hobs – A Method to Reduce Cutting Vibrations

One of the reasons causing vibration for gear hob toothing is the shock at the tool’s entry, which is generated by the great length of the cutting edge entering the metal at the same time. This paper proposes a fragmentation of the cutting edge so that its length is much smaller. Moreover, the cutting scheme is also changed, so that the entire tooth line of the piece is made with four consecutive teeth of the tool. Therefore, the impact force input generating shock and vibration is significantly reduced.

A Tool Wear Monitoring System for Steel and Aluminium Alloys Based on the same Sensor Signals and Decision Strategy

This paper presents a tool wear monitoring system that uses the same signals and prediction strategy for monitoring the machining process of different materials, i.e., a steel and an aluminium alloy. It is an important requirement for a monitoring system to be applied in real applications. Experiments have been performed on a lathe over a range of different cutting conditions, and TiN coated tools were used. The monitoring signals used are the AC feed drive motor current and the cutting vibrations. The geometry tool parameters used as inputs are the tool angle and the radius. The performance of the proposed system was validated against different experiments. In particular, different tests were performed using different numbers of experiments obtaining a rmse for tool wear estimation of 17.63 μm and 13.45 μm for steel and aluminium alloys respectively.

Vibration energy harvesting to power condition monitoring sensors for industrial and manufacturing equipment

To enable self-sustaining long-lasting wireless condition monitoring sensors, a small mechanical vibration energy harvester using electromagnetic transduction was constructed and used to harvest vibrations from large industrial pump motors and machine tool. The prototype harvester was roughly the size of a cube with 2.5 cm long sides. Power ranging from 0.2 to 1.5 mW was harvested from 15 to 30 kW water pump motors. For a machine tool, metal cutting vibrations and rapid jog events were explored as possible harvestable sources of energy. Power ranging from 0.9 to 1.9 mW was harvested during facemilling operations, and it was shown that rapid jog events could be harvested. The power levels harvested from the pump motors and machine tools are sufficient to provide the time-averaged power requirements of commercial wireless sensor nodes, enabling sensor nodes to overcome the finite life of replaceable batteries.