Changes in cutting forces during a milling operation can be associated with tool wear and breakage. Accurate monitoring of these cutting forces is an important step towards the automation of the machining process. However, direct force sensors, such as dynamometers, are not practical for industry application due to high costs, unwanted compliance, and workspace limitations. This paper describes a method in which power sensors on the feed and spindle motors are used to generate coefficients for a cutting force model. The resulting model accurately predicts the X and Y cutting forces observed in several simple end-milling tests, and should be capable of estimating both the peak and average force for a given cut geometry. In this work, a dynamometer is used to calibrate the feed drive power sensor and to measure experimental cutting forces for verification of the cutting force model. Measurement of the average x-axis cutting forces is currently presented as an off-line procedure performed on a sacrificial block of material. The potential development of a continuous, real-time force monitoring system is discussed.

In this paper, the effect of kinematic redundancy on chucking, especially, on the positioning accuracy of a cylindrical workpiece was investigated. No previous research on the effect of kinematic redundancy on the positioning accuracy and the repeatability of a workpiece in chucking has been reported, even if kinematic principle has been known for a long time. Starting from the description of the issues, a series of systematic experiments were carried out. It was demonstrated that the non-repeatability and the chucking error proportionally increase as the kinematic redundancy increases. Also, it was shown that kinematic redundancy had a significant effect on the positioning accuracy of chucked workpieces, especially the workpieces with a relatively higher length/diameter ratio. The contact area between the workpiece and the jaws was reduced to the extent which does not hurt the chucking rigidity and safety to reduce kinematic redundancy. It was shown that the concentricity of the workpieces was improved as much as 10 times by just minimizing the kinematic redundancy in the finish hard turning of the rings of a taper roller bearing.

This paper presents the results of a study to assess the feasibility of inferring workpiece material hardness from high-speed video data of chip formation obtained during a turning operation. The motivation for assessing hardness in situ comes from the fabrication of shaped charges, where spatial variation in hardness is known to affect the performance of the shaped charge. While other in-process data could be used for this purpose, video data are analyzed here because of the stand-off, non-contact advantages afforded. This is especially relevant for highly qualified machining processes for small-lot, high value parts where any interference with the process (e.g., introduction of cables near the machine tool) is undesirable. A multistep image processing procedure is presented which is used to extract several features from the video data. These features are then used to develop a classifier which can be used to predict work-piece hardness. Multiple classifier designs (Knn and Ratchet) are considered.

The characteristics of residual stress (RS) profiles and their effects on rolling contact fatigue life for precision turned and ground surfaces with a white layer (WL) are very controversial. The key findings of this study are: (a) The basic RS profiles by a sharp tool can be fundamentally changed by a turned WL but not a ground WL; (b) The hook shaped RS profile of a turned surface may have about 40% more fatigue life than a ground one; (c) The white layer may reduce fatigue life as much as 7–8 times despite the deep compressive RS in the subsurface.

In this paper, a methodology is presented for predicting crack growth rate along three-dimensional crack fronts under mode I dynamic loading conditions. Within the present methodology, for every point along the crack front the stress intensity factor matches the dynamic fracture toughness at the onset of propagation. In order to accurately evaluate the dynamic stress intensity factor the component separation method of the dynamic J integral is used. To overcome the difficulties in three-dimensional dynamic fracture simulations, the three-dimensional dynamic moving finite element method based on three-dimensional moving 20-noded isoparametric elements is used. In the absence of experimental measurements for dynamic fracture toughness, a new methodology to estimate the dynamic fracture toughness is proposed, i.e., a hybrid experimental-numerical approach, which makes use of numerically determined histories of the dynamic stress intensity factor. The values of the dynamic stress intensity factor are converted into dynamic fracture toughness based on the Weibull distribution. The predictive ability of the developed methodology is demonstrated through the prediction of the dynamic crack growth in Double Cantilever Beam (DCB) specimen of PMMA with different thickness.

Diamond coated cutting tools have been pursued as a cost-effective substitute to brazed polycrystalline diamond (PCD) tools in applications such as machining high-strength and lightweight materials. However, coating delamination has been known as the major failure mode of diamond coated tools, which terminates tool life prematurely. Once delamination failure occurs, the tool substrate often subjects to severe abrasive wear leading to catastrophic tool failures that imparts the part quality and interrupts machining operations. Hence, accurate detections and forecasts of coating delamination events can prevent production loss and assist process planning. In this study, the characteristics of acoustic emission (AE) signals when machining a high-strength aluminum alloy and a composite using diamond coated cutting tools were investigated. The AE signals were analyzed in both time and frequency domains at various machining conditions and different cutting times. It was found that AE root-mean-square values decrease considerably once coating delamination occurs. The results also indicate a correlation between the tool condition and fast Fourier transformation (FFT) spectra of AE raw data. In addition, the machining experiments implied that it may be feasible to use AE signals to monitor the condition of diamond coated tools during machining.

Stream of Variance (SoV) modeling of multi-station manufacturing process has been studied for the past 15 years and was used for identification of root causes of manufacturing errors, characterization and optimal allocation of measurements in multi-station manufacturing processes, process-oriented tolerance allocation, and most recently, for optimal in-process adaptations of programmable, flexible tooling (flexible fixtures, CNC machines) for autonomous minimization of errors in dimensional product quality. However, due to the high cost of flexible tooling, it is plausible to strategically position such devices across a manufacturing system in a way that one’s ability to mitigate quality problems is maximized. In this paper, a distributed stochastic feed-forward control method is devised which gives the optimal (in least square sense) reduction of the variance-covariance matrix of errors in dimensional workpiece quality in a multi-station manufacturing process with a limited number of flexible tooling components. Genetic Algorithm is proposed to enable optimal allocation of flexible tooling devices. Theoretical results have been evaluated and demonstrated using the SoV model of a real industrial process.

The two-degree of freedom oscillator is presented to model the dynamics of a machine tool system in the cutting process. The chip dynamics are presented through a discontinuous system with a velocity boundary (frictional force). The closed form solutions are presented for the normalized linear set of ordinary differential equations. The basic mappings are introduced to investigate the stick-slip motion in such a mechanical model. The mapping structures for the periodic motions will be developed. The numerical prediction of the phase trajectory, over a range of the excitation frequency is presented through the discontinuity. The predictions are verified by numerical illustrations of the phase trajectory, velocity and forces time histories. The main contributions are the forces and force product distribution at the switching points for this machine-tool.

Integrating traditionally separate industrial control systems can derive factory-wide benefits by leveraging more information about the ongoing process. This paper shows that connecting a networked safety system and a process control system leads to an extension of the individual benefits provided by each system. A safety system gains the ability to protect not only the machines and workers but also the product that is being built. A diagnostic system can also raise safety alarms when a process variable is outside the expected range of safe operation. This connection is explored to determine the practical impact of different methods of integration on machining and system processes. Three integration methods are possible depending on which portions of the system can be classified as “safe”. A case study integrating a diagnostics system as a non-safe sensor proves that this connection, when it is implemented on an industrial testbed, provides all of the benefits described and does not require significant changes to control software.

In this paper, the application of a pneumatic gantry robot to contour tracking is examined. A hybrid controller is structured to control the contact force and the tangential velocity, simultaneously. A previous study provided controller tuning and model validation results for a fixed gain PI-based force/velocity controller. Performance was limited by system lag and Coulomb friction. New results demonstrate that even with perfect friction compensation, the limiting factor is the system lag. A neural network (NN) compensator was subsequently developed to counter both effects. Results for straight and curved edged workpieces are presented to demonstrate the effectiveness of the NN compensator and the capabilities of a pneumatic gantry robot.

A sensor composed of a composite material formed of a polymer and nano-carbon conductive filler is characterized for measurement of pressure through the relationship to contact resistance. The sensor has the physical attributes of polymer, but is electrically conductive and can therefore be used on a conductive substrate to gauge pressure and subsequently load. Benefits over traditional force sensing include reduced cost, full control of geometry, reduced form factor, resistance to impact and to corrosion. A test circuit was developed to study the behavior of the sensor at different loads and surface conditions, and behavior over time. Prospective applications on manufacturing and automotive fields are proposed.

Surface distortions/deflections are frequently introduced into the Class “A” surfaces during sheet metal stamping processes. However, the origins of the draw die related surface distortion/deflection have not been well understood. This paper presents our design of a stamping test for the investigation of the distortion phenomenon. Five geometric parameters are first identified to represent basic geometry of typical automobile outer panel depression features around the surface distortions. Experimental stamping dies are then designed to reflect various combinations of these five geometric parameters with the assistance of numerical simulations to ensure that the designed dies are able to replicate the surface distortion phenomenon. Also, real-time dynamic measurement techniques are designed to collect historical data of strains and deflection on the stamping panels. Our preliminary tryouts show that the designed stamping test successfully replicates the distortion phenomenon observed in production stamping processes. It provides a platform for the investigation of the root-cause of the draw die related surface distortions.

Wiresaw has become a standard slicing tool especially for large ingots in the wafer preparation industry since late 1990s. To meet the requirements of the surface finish and topology, it is critical to control the process parameters to render good surface finish and to minimize kerf loss. The vibration of moving wire in the wiresaw manufacturing operation affects the wafer surface finish and kerf loss; therefore, the study and analysis of vibration of moving wire become very important and relevant to this manufacturing process. Built on the previous research, the free vibration response of axially moving wire with damping is a combination of infinite sets of response solutions, with trigonometric functions due to end constraints. The apparent damping due to the increase of speed on the first several components of responses will be presented and discussed in this paper. The results also show that the increase in speed will excite components of response except the dominating one. Since the free vibration response is a combination of infinite sets of solutions, it is not possible for the system to be completely critically-damped or over-damped because of the existence of under-damped modes at higher order. Therefore, a damped index is introduced to help in understanding the behavior of such system. When the physical damping is increased (for example, by using a more viscous carrier fluid in slurry), all components are more damped accordingly. However, in addition to the physical damping, the apparent damping caused by the increase of wire speed will also damp out the response. These two parameters, physical damping and apparent damping, control the behavior of an axially moving wire. This is a new finding in vibration analysis of moving wire that, to our best knowledge, has not been reported in the previous literature.

Effective equipment maintenance is essential for a manufacturing plant seeking to produce high quality products. The impact of equipment reliability and quality on throughput have been well established, however, the relationship between maintenance and quality is not always clear or direct. This paper describes a statistical modeling method that makes use of a Kalman filter to identify correlations between independent sets of maintenance and quality data. With such a method, maintenance efforts can be better prioritized to satisfy both production and quality requirements. In addition, this method is used to compare results from the theoretical maintenance-quality model to data from an actual manufacturing system. Results of the analysis indicate the potential for this method to be applied to preventive as well as reactive maintenance decisions since ageing aspects of equipment are also considered in the model.

Newer sheet alloys (such as Al, Mg, and advanced high strength steels) are considered for automotive body panels and structural parts to achieve lightweight construction. However, in addition to issues with their limited formability and high springback, tribological conditions due to increased surface hardness and higher work hardening effect necessitate the use of improved alternative die materials, coatings, lubricants to minimize the wear-related issues in stamping of such lightweight materials. This study aims to investigate and compare the wear performances of seven (7) different die materials (AISI D2, Vanadis 4, Vancron 40, K340 ISODUR, Caldie, Carmo, 0050A) using a newly developed wear testing method and device. We used DP600 sheets in the tests. Our results showed that almost all of the recently developed specially-alloyed die materials demonstrated higher wear resistance performance when compared with the performance of AISI D2 die material.

Present chatter models in turning lack physical insight because they do not model the process in a geometrically rigorous manner. Many of the models are linear and produce unrealistic, unbounded vibration amplitude growth after the onset of chatter. Those that are nonlinear are typically reverse engineered in order to predict bounded vibration. The current approach models the forces in machining due to chip formation, plowing, and interference between the flank of the cutting tool and the machined workpiece surface in a geometrically comprehensive fashion. Additionally the effects of strain, strain rate and temperature on the chip formation process are captured. In doing so, accurate predictions can be made for both the occurrence of chatter and its vibration amplitude growth over time. The proposed model is validated with machining experiments on a compliant workpiece to explore the effect of tool nose radius on chatter.

Condition monitoring (CM) is an effective way to improve the tool life of a cutting tool. However, CM techniques have not been applied to monitor tool wear in an industrial gear shaving application. Therefore, this paper introduces a novel, sensor-based, data-driven, tool wear estimation method for monitoring gear shaver tool condition. The method is applied on an industrial gear shaving machine and used to differentiate between four different tool wear conditions (new, slightly worn, significantly worn, and broken). This research focuses on combining, expanding, and implementing CM techniques in an application where no previous work has been done. In order to realize CM, this paper discusses each aspect of CM, beginning with data collection and pre-processing. Feature extraction (in the time, frequency, and time-frequency domains) is then explained. Furthermore, feature dimension reduction using principal component analysis (PCA) is described. Finally, feature fusion using a multi-layer perceptron (MLP) type of artificial neural network (ANN) is presented.

Machining-induced surface topography has a significant effect on tribological performance of machined components in sliding contact. However, the effect of different surface topography by turning versus grinding on tribological performance has received very little attention. In this study four types of surface topography by turning and grinding AISI 52100 bearing steel (62 HRc) were prepared and characterized to study its effect on friction and wear in sliding contact. Dry and lubricated reciprocating sliding wear tests with an on-line acoustic emission (AE) sensor were carried out using a ball-on-disk tribometer. The experimental results have shown that: (i) the turned surfaces, regardless of the presence of a white layer, yield smaller friction of coefficients in sliding along feed marks than across sliding at both dry and lubricated conditions. However, the opposite hold true for the ground surfaces; (ii) friction of coefficients (0.6∼0.8) at dry conditions is higher for both turned and ground fresh surfaces than their white layer counterparts regardless of sliding direction. At lubricated conditions, Friction of coefficients (0.1∼0.12) are smaller for the both turned and ground fresh surfaces than the white layer surfaces in along sliding, while it is equivalent in across sliding; (iii) the trends of acoustic amplitude amplitude are consistent with those of frictional coefficients for the turned or ground surfaces at dry conditions. Similar trends are also true for the turned surfaces at lubricated conditions, but not for the ground surfaces; and (iv) the wear debris on the track may act as solid lubricants to reduce the sliding frictional coefficient. Machining induced white layers leads to a better wear resistance than the fresh surfaces in either along or across sliding.

Use of Advanced High Strength Steels in automotive applications is increasing. One of these materials is boron steel, which is commercially available in coated and uncoated sheets. Automotive manufacturers are using boron steel in body structure applications to produce light weight parts and to address safety requirements. Boron steel is available in a non heat-treated condition (also referred to as “green state”) which typically has a yield strength around 350 MPa. The yield strength for a fully temperature hardened boron steel increases to above 1000 MPa, depending on heat treatment temperature and quenching methods used. In this report, the static and fatigue properties of uncoated boron steel were evaluated. One objective was to understand whether these properties varied with respect to the material rolling direction (longitudinal, transverse and diagonal). For static strength analysis three different gages (1.0 mm, 1.5 mm and 2.0 mm) were evaluated. For fatigue evaluation, 3.0 mm thickness boron steel was evaluated. Based on the mechanical test data, ultimate tensile strength was not statistically significant in all three directions (longitudinal, transverse and diagonal) among three gages chosen. However, within the same gage, ultimate tensile strength is statistically significant in all three directions. 0.2% offset Yield strength and total elongation are uniform in all gages as well as in all three directions within each gage. However, uniform elongation (at max. load condition) was significant among the gages as well as within the same gages. A comparison of the monotonic and cyclic stress strain curves indicates boron steel is a strain-softening material.

Robotics is a technology that is utilized tremendously in Industrial and Commercial Applications. Different types of robotic arms are used to fulfill the industrial needs. The aim of the work presented in this paper is to give a visual simulation of the robotic arm (Aristo Robot – 6 DOF) which can be used with offline robotic programming thereby introducing the language to the user and creating a training package for the user. This software also reduces the time as programming can be done offline. The pick and place robotic arm comprises of 6 links, which each of them has one degree of freedom (DOF) with a payload capacity of 3 kg is used for visual simulation. The main objective is to design a three dimensional graphic of a robotic arm and its movement animation that imitates the movement of actual robotic arm. The graphic design is then used as a foundation to find its limits of reach in the surrounding. Also the analysis of workspace is done to understand its workspace volume properly.