Abstract Carbon fiber reinforced plastic (CFRP) composites were widely used in machinery, automobile, and aerospace industries due to the superior properties of high stiffness, high strength-to-weight ratio, high fatigue resistance, and good wear resistance. In these applications, hole making on CFRP composites was needed for assembly purpose. In different hole making processes, delamination was considered as a crucial issue, leading to premature failure of products. Compared with the conventional CFRP hole making processes (such as twist drilling, milling, grinding, etc.), rotary ultrasonic machine (RUM) had advantages of low cutting force and torque, low surface roughness, and long tool life. Therefore, numbers of researchers worked on RUM processes. The reported investigations mainly focused on the effects of input variables (including machining variables, tool variables, and workpiece properties) on cutting force, torque, surface roughness, and tool life, etc. In addition, effects of cutting tool variables on delamination were also reported. However, there were no reported investigations on effects of machining variables on delamination in RUM of CFRP composites. This investigation, for the first time, reported the effects of ultrasonic power, tool rotation speed, and feedrate on delamination as well as its associated cutting force. Based on the experiments, the results showed that delamination decreased with ultrasonic power increasing, tool rotation speed increasing, or feedrate decreasing. The relationships between cutting force and delamination were also studied.

Application of small quantity lubrication (SQL) technology in high speed machining is being recognized as a sustainable approach for achieving suitable cooling/lubrication in machining zone. Present investigation focused on effectiveness of SQL with nanofluids in high speed turning of AISI 4140 steel with a TiN-top coated multilayered carbide insert and explored the advantages of using a twin-jet SQL system instead of a single jet one. SQL system was developed in-house with external-mix nozzles. The experiment was conducted varying the cutting velocity at two different feed rates (0.05mm/rev and 0.10mm/rev) with conventional coolant and nanofluids. Immediate improvement in machinability and the quality of turned surface was observed with twin-jet nanofluid SQL. A significant reduction of force and specific energy could be achieved by using 3vol% alumina and 1vol% multi walled carbon nano tube (MWCNT) nanofluid instead of soluble oil. The MWCNT nanofluid was found to be superior to alumina nanofluid in reduction of tensile residual stress. Such a reduction is typically an indirect indication of reduction of cutting zone temperature, which could be achieved due to enhanced level of lubricity at chip-tool interface and enhanced level of heat dissipation ability of the nanofluids. Improvement in retention of sharpness of tool cutting edges was also observed under nanofluid-SQL environment, which could have played important role in improvement of surface quality.

A new model to predict cutting force and temperature is developed by incorporating the lubrication and cooling effects generated from minimum quantity lubrication (MQL) machining. The boundary lubrication theory is utilized to estimate the friction behavior in prediction model. The model is capable of predicting cutting force and temperature in MQL machining directly from given cutting conditions, as well as material properties. Subsequently, the response of temperature distributions to chip formation and MQL is quantified on the basis of a moving heat source/loss model which iterates with the initial cutting force to achieve the final predictions. The predicted cutting temperature and cutting force are validated by the experimental data for AISI 9310 steel and AISI 1045 steel, respectively. Results show that under cutting speeds of 223–483 m/min, feed rates 0.10–0.18 mm/rev, depth of cut 1.0mm, the predicted cutting temperature at the tool-chip interface are generally lower than experimental measurements by 2% to 19%. And the model provides an average error of 11% for temperature prediction. With respect to cutting force prediction, the model provides a prediction error of 13% on the average in the cutting direction and 12% in the thrust direction within the experimental test condition range (cutting speeds of 45.75–137.25m/min, feeds 0.0508–0.1016 mm/rev, and depth of cut 0.508–1.016mm). In actual machining, the effects of possible tool wear causing higher temperature and force can contribute to deviations from model predictions involving only sharp tools.

High-definition metrology (HDM) systems with fine lateral resolution are capable of capturing the surface shape on a machined part that is beyond the scope of measurement systems employed in manufacturing plants today. Such surface shapes can precisely reflect the impact of cutting processes on surface quality. Understanding the cutting processes and the resultant surface shape is vital to identifying opportunities for high-precision machining process monitoring and control. This paper presents modeling and experiments of a face milling process to extract surface patterns from measured HDM data and correlate these patterns with cutting force variation. A relation is established between instantaneous cutting forces and the observed dominant patterns along the feed and circumferential directions. Potential applications of such relationship in process monitoring, diagnosis, and control are also discussed.

A mechanistic model for cutting force in ultrasonic-vibration-assisted grinding (UVAG) (also called rotary ultrasonic machining) of brittle materials is proposed for the first time. Fundamental assumptions include: (1) brittle fracture is the dominant mechanism of material removal, and (2) the removed volume by each diamond grain in one vibration cycle can be related to its indentation volume in the workpiece through a mechanistic parameter. Experiments with UVAG of silicon are conducted to determine the mechanistic parameter for silicon. With the developed model, influences of six input variables on cutting force are predicted. These predicted influences trends are also compared with those determined experimentally for several brittle materials.

Many experiments on rotary ultrasonic machining (RUM) have been conducted to study how input variables (including tool rotation speed, ultrasonic power, feedrate, and abrasive size) affect output variables (such as cutting force, torque, surface roughness, and edge chipping) by using diamond tools. However, a literature review has revealed that there is no reported study on CBN tools in RUM. This paper, for the first time in literature, presents an investigation of RUM of stainless steel using CBN tools. Firstly, an introduction of superabrasive materials and RUM principle was provided. After presenting the experiment procedures and workpiece properties, it reports the results on tool wear, cutting force, torque, surface roughness in RUM of stainless. Finally, it discusses and compares the performances of diamond and CBN tools in RUM of stainless steel under certain conditions.

Titanium and its alloys (Ti) have wide applications in industry. However, since Ti is notorious for its poor machinability, their applications have been hindered by the high cost and low efficiency. Ultrasonic-vibration-assisted grinding (UVAG) is a hybrid machining process that combines the material removal mechanisms of diamond grinding and ultrasonic machining, and it is a cost-effective machining process for Ti. The relations between cutting force and input variables have been investigated and reported. But these relations have been studied by changing one variable at time. Therefore, the interactions between cutting force and input variables have not been revealed. In this paper, a two-level five-factor full factorial design is used to study the relations between cutting force and input variables based on a cutting force model for UVAG of Ti. The main effects of these variables, and two-factor interactions and three-factor interactions of these variables are also revealed.

Rotary Ultrasonic Machining (RUM) is a hybrid machining approach that combines two material removal mechanisms, namely diamond grinding and ultrasonic machining. Currently available literature mainly focuses on static parametric relationships. This paper presents preliminary results of an experimental study on some aspects of the RUM process performance, surface integrity, and dynamic process modeling. A stochastic modeling and analysis technique called Data Dependent Systems (DDS) was used to study RUM generated surface profiles and cutting force signals. The DDS wavelength decomposition of the surface profiles suggested that the major characteristic root wavelength had a positive correlation with feed rate, and the wavelength magnitude may be linked to the grain size of the workpiece material. In addition, the difference of the major wavelength between the surface profiles for machined holes and that for machined rods was investigated. The surface variation between the entrance and exit segments of both holes and rods were also studied. Moreover, the DDS modeling approach was applied to cutting force signals collected during RUM and comparisons were made to the surface profiles results.

This paper reviews the literature on dry machining with VT cooling (using vortex-tube generated cold air as coolant). It presents reported experimental results on effects of VT cooling on cutting force, cutting temperature, tool wear, surface roughness, and residual stress. It also points out areas where VT cooling applications have not been reported and potential directions for future research.