Computer numerical control

Parametric interpolation has many advantages over linear interpolation in machining curves. Real time parametric interpolation research so far has addressed achieving a uniform feed rate, confined chord errors and jerk limited trajectory planning. However, simultaneous consideration of confined chord errors that respect the acceleration and deceleration capabilities of the machine has not been attempted. In this paper, the offline detection of feed rate sensitive corners is proposed. The velocity profile in these zones is planned so that chord errors are satisfied while simultaneously accommodating the machine's acceleration and deceleration limits. Outside the zone of the feed rate sensitive corners, the feed rate is planned using the Taylor approximation. Simulation results indicate that the offline detection of feed rate sensitive corners improves parametric interpolation. For real time interpolation, the parametric curve information can be augmented with the detected feed rate sensitive corners that are stored in 2 £ 2 matrices. q

Virtual reality-based training systems (VRTSs) are advanced computer-assisted training systems using Virtual Reality (VR) technology. To have better structure and easier implementation, a virtual training system can be modeled as an integrated system consisting of a training task-planning module, an instruction module, a simulation module, a performance evaluation module, and an interface module. Presented in this paper are an architecture of VR-based training systems and a practical knowledge modeling approach to modeling the training scenarios of the systems by using Petri nets formalism. A Computer Numerical Control (CNC) milling operations virtual training prototype system was developed to illustrate the feasibility and eectiveness of this approach.

that there exists a prime p of the form p = cn +1 which is representable with s = @(log n) bits. Then 2Tp, the field of integers modulo p , contains a primitive root of unity w of order n and supports an O(n1ogn)-step fast Fourier transform on n points. Without loss of generality, we may assume that F consists of m characters of (s-1) bits each (each character being an element of Z p) , since the same process is applicable to each of the m (s-1)-bit blocks into which the original file can be segmented. We shall encode F into n elements of 2Tp in the following manner. Let V be the n X n Fourier matrix corresponding to primitive root w , i.e., (V) ,

In this work we present how Augmented Reality (AR) can be used to create an intimate integration of process data with the workspace of an industrial CNC (computer numerical control) machine. AR allows us to combine interactive computer graphics with real objects in a physical environment -in this case, the workspace of an industrial lathe. ASTOR is an autostereoscopic optical see-through spatial AR system, which provides real-time 3D visual feedback without the need for user-worn equipment, such as head-mounted displays or sensors for tracking. The use of a transparent holographic optical element, overlaid onto the safety glass, allows the system to simultaneously provide bright imagery and clear visibility of the tool and workpiece. The system makes it possible to enhance visibility of occluded tools as well as to visualize real-time data from the process in the 3D space. The graphics are geometrically registered with the workspace and provide an intuitive representation of the process, amplifying the user's understanding and simplifying machine operation.

Glass is an excellent material for use as a microfluidic chip substrate because it has great chemical and thermal stability. This work describes a flexible platform for the rapid prototyping of microfluidic chips fabricated from glass. A debris-free laser direct-writing technology that requires no photomask generation is developed. A 266 nm laser with a high repetition rate is employed in laser-induced backside wet etching (LIBWE) for glass machining. A microfluidic pattern is designed using computer drawing software and then automatically translated into computer numerical control motion so that the microtrench is directly fabricated on the glass chip. The overall machining speed can be increased by increasing the repetition rate to ∼6 kHz. Without a clean room facility or the highly corrosive acid, HF, the overall development time is within hours. Trenches with complex structures that are hard to fabricate by photolithography were easily produced by laser direct-writing. An integrated microreactor/concentrator is demonstrated. The crack-free and debris-free surface was characterized by SEM and a surface profiler. Various effective etching chemicals for the LIBWE process were investigated to understand the etching mechanism. The minimal laser power used for glass etching was approximately 20 mW for a 6 µm wide microtrench. Several new compounds have been demonstrated to be effective in ablation. The etch threshold is minimum and does not decrease further as the unit length absorbance increases above 8000 in acetone solution.

The purpose of this research is to investigate the relative importance of spindle speed, system dynamics, and cutting conditions on the accuracy of surface location in computer numerical-control (CNC) finish machining operations. The relationship between the spindle speed, the most flexible modes of the machine/cutting tool system and the final part dimensions is rather complex. The underlying theory, based on the situation of forced vibrations, is outlined. It is shown that the critical factor is the ratio of the tooth passing frequency to the system most flexible mode and corresponding natural frequency. Simple analytical calculations are carried out to illustrate the overcut/undercut surface error phenomenon. A simple simulation for end milling operations is also described which calculates the force on the cutter, the resulting cutter deflection, and the final error of surface. A comparison between the simulated and experimental results is presented. From experimental data, it shown that a change in surface location (and part dimension) of up to 50 m is seen for a set of given conditions (i.e., cutter, material, chip load) simply by changing spindle speeds. Furthermore, it is seen that certain spindle speeds produce surfaces with no error introduced by the machining process.

This study presents a new suction-type, pneumatically driven microfluidic device for liquid delivery and mixing. The three major components, including two symmetrical, normally closed micro-valves and a sample transport/mixing unit, are integrated in this device. Liquid samples can be transported by the suction-type sample transport/mixing unit, which comprised a circular air chamber and a fluidic reservoir. Experimental results show that volume flow rates ranging from 50 to 300 μl/min can be precisely controlled during the sample transportation processes. Moreover, the transport/mixing unit can also be used as a micro-mixer to generate efficient mixing between two reaction chambers by regulating the time-phased deformation of the polydimethylsiloxane (PDMS) membranes. A mixing efficiency as high as 98.4% can be achieved within 5 s utilizing this prototype pneumatic microfluidic device. Consequently, the development of this new suction-type, pneumatic microfluidic device can be a promising tool for further biological applications and for chemical analysis when integrated into a micro-total analysis system (μ-TAS) device.

Nickel-based alloy is difficult-to-machine because of its low thermal diffusive property and high strength at higher temperature. The machinability of nickel- based Hastelloy C-276 in turning operations has been carried out using different types of inserts under dry conditions on a computer numerical control (CNC) turning machine at different stages of cutting speed. The effects of cutting speed on surface roughness have been investigated. This study explores the types of wear caused by the effect of cutting speed on coated and uncoated carbide inserts. In addition, the effect of burr formation is investigated. The chip burr is found to have different shapes at lower speeds. Triangles and squares have been noticed for both coated and uncoated tips as well. The conclusion from this study is that the transition from thick continuous chip to wider discontinuous chip is caused by different types of inserts. The chip burr has a significant effect on tool damage starting in the line of depth-of-cut. For the coated insert tips, the burr disappears when the speed increases to above 150 m/min with the improvement of surface roughness; increasing the speed above the same limit for uncoated insert tips increases the chip burr size. The results of this study showed that the surface finish of nickel-based alloy is highly affected by the insert type with respect to cutting speed changes and its effect on chip burr formation and tool failure.

The application of '41 technologies using modem computers and controllers is seen as a way forward to produce higher quality components more efficiently with smaller batch sizes and more frequent changeovers. Users continue to demand better accuracy, surface integrity, and shorter cycle times with reduced operator intervention and increased flexibility. This paper reviews research into the use of intelligent control and optimisation techniques in grinding and propose the incorporation of intelligent techniques into computer numerical controls (CNCs). Two main trends are evidenced in the development of AI technologies in grinding: desktop systems to assist tool and parameter selection and self-optimising systems integrated within the machine controller. It is predicted that future developments will favour increasing incorporation of intelligence into CNC. The development of modular systems which are sufficiently robust to plan. supervise and control abrasive processes requires ongoing research and development. Ke.ywords: Grinding; Artificial intelligence: CNC 0166-3615/96/$15.00 Copyright 0 1996 Elsevier Science B.V. All rights reserved. PII SOl66-3615(96)00036-X 46 W.B. Rowe et al. / Computers in Industry 31 (1996) 45-60 creasingly CNC is presented as an intelligent con-Grinder Grinding Dressing Wheels Diagnosis Control Year Billatos [ 1.21 Brown [3] Chen [4] Dornfeld [5] Du l61 Inasaki [7,8] Inoue [9] Junkar [lO,ll] Koenig [12,13] Liao [14] Malkin [15-171 Midha [18-211 Mori [22-241 Nagasaka [25] Nakajima [26] Paul [27] Roberts [28] Rowe [29-361 Sathyanarayanan [37] Tanaka [38] Tonshoff [39-421 Trtnal [43] Ueda [44] Venk [45-471 Walter [48] Wobker [49] Yoneda [50,5 l] Zhao I52,53] Screw FL

A vacuum tube oscillator fabricated by the deep etch X-ray lithography: lithographie, galvanoformung, abformung (LIGA) process was successfully developed for the first time. For the proof-of-concept experiment involving a delayed feedback oscillator, a folding-waveguide traveling-wave tube (FWTWT) was fabricated by computer numerical control milling in advance. With a 12.4-kV and 150-mA electron beam, a Ka-band FWTWT amplifier shows a linear gain of 25 dB and a bandwidth of 10%. Applying a delayed feedback scheme, the threshold feedback strengths for the onset of oscillation and for self-modulation were measured to be 30 dB and 16 dB, respectively. The optimum value of the feedback strength for the single-frequency oscillation at 32.5 GHz was about 18 dB with a net electronic efficiency of 6%. The LIGA-fabricated FWTWT circuit was constructed by a lithographic process using the synchrotron X-ray source at the Pohang Light Source. The resulting accuracy and average surface roughness were less than 10 and 1 m, respectively. The LIGA-fabricated Ka-band amplifier shows a linear gain of 15 dB and bandwidth of 1.7% with a 12.4-kV, 47-mA electron beam. The threshold for the onset of oscillation was about 11 dB and the optimum value of feedback strength for a single frequency oscillation at 35 GHz with a net electronic efficiency of 3.5% was about 8 dB. Index Terms-Deep etch X-ray lithography, delayed feedback oscillator, folding-waveguide traveling-wave tube (FWTWT), lithographie, galvanoformung, abformung (LIGA). I. INTRODUCTION R ECENT developments in microfabrication technologies have encouraged researchers in the vacuum electronics community to investigate the production of oscillators with the operation frequency range up to terahertz, where applications, such as high data rate communication, radar, radio astronomy, plasma diagnostics, remote sensing, and medical imaging could be attractive [1]. As the desired operating frequency becomes higher, the dimensions of the interaction circuit should become smaller. In the frequency range above the W-band, traditional machining is not feasible for circuit fabrication and microfabrication techniques should be adopted.

In order to compete favorably in the world markets, it is essential for a company to have an efficient and flexible manufacturing system, capable of producing quality products with low costs and reacting quickly to the changes in consumer demand. Factory automation (FA) (a very popular term in Japan and virtually synonymous with computer integrated manufacturing (CIM)) has been recognized as a promising approach for companies to become more competitive. Currently, the United States may still lead the world in developing automation technologies; however, Japan has been more successful in implementing them. If factory automation holds the key to the revival of American industrial competitiveness, why has there been a lack of actual implementation? To answer this question, it is beneficial to explore the approaches that Japanese companies have employed to implement factory automation. The main objective of this paper is to report the findings of a research study that investigates the practical experience that Japanese industries have accumulated concerning the implementation of factory automation.

This paper introduces an adaptive fuzzy logic controller (AFLC) for precision contour machining which adjusts both input and output membership functions simultaneously. The parameters of the proposed controller are self-tuned in real-time according to a continuous measurement of the performance of the controller itself and estimated disturbance values. The adjustment of the membership functions are restricted within a stable range derived from a stability analysis. The proposed controller as well as a conventional fuzzy logic controller and a PID controller were simulated and implemented on a 3-axis milling machine in contour milling. Both the simulations and experiments show that the AFLC can provide superior performance in terms of contour tracking accuracy compared with the other two controllers particularly in machine tool systems where friction is a serious problem in the feed drives.

This paper presents an effective patient-specific approach for prediction of failure initiation and growth in human vertebra using the general framework of the quantitative computed tomography (QCT)-based finite element method (FEM). The studies were carried out on 13 vertebrae (lumbar and thoracic), excised from 3 cadavers with the average age of 42 years old. Initially, 4 samples were QCT scanned and the images were directly converted into voxel-based 3D finite element models for linear and nonlinear analyses. The equivalent plastic strains obtained from the nonlinear analyses were used to predict the occurrence of local failures and development of the failure patterns. In the linear analyses, the strain energy density measure was used to identify the critical elements and predict the failure patterns. Subsequently, the samples were destructively tested in uniaxial compression and the experimental load-displacement diagrams were obtained. The plain radiographic images of the tested samples were also examined for observation of the failure patterns. In continuation, the presence of osteolytic defects in vertebrae was simulated by creation of artificial cavities within 9 remaining samples using a computer numerical control (CNC) milling machine. The same protocol was followed for scanning, modeling, and destructive testing of these samples. A strong correlation was found between the predicted and measured strengths. Finally, a typical vertebroplasty treatment was simulated by injection of low-viscosity bone cement within 3 compressed samples. The failure patterns and the associated load levels for these samples were also predicted using the QCT voxel-based FEM.

CNC feature-based programming with STEP-NC standard extends the collaborative model of manufacturing data exchange all along the numerical data chain. This paper considers the mutations related to this approach from the manufacturing system level to the industrial enterprise as a whole. The eXtended Manufacturing Integrated System concept is introduced to fill in the gap of the current manufacturing data exchange bottleneck. It is composed of eXtended CAD and eXtended CNC systems to link the CAD model to the real machined part through the Manufacturing Information Pipeline. The contributions associated with these concepts are demonstrated through a validation platform implemented on industrial CNC manufacturing equipments.

A number of unique challenges arise in fabricating and assembling complex mechanisms at the meso-scale (hundreds of microns to centimetres). In general, for a complex multi-part mechanism at this length scale, no single machining technique can produce all the necessary parts-or often even a single individual part. Towards developing a comprehensive set of 'best practices' for combining multiple precision micromachining operations at the meso-scale, we present a case study on fabricating and assembling an endoscopic capsule robot. Existing passive imaging capsules have proven exceptionally useful in the diagnosis of the gastrointestinal tract, and robotic capsules promise to enhance their diagnostic capabilities and enable non-invasive treatment delivery. In this case study, we describe the fabrication of a robotic capsule (2.6 cm 3 in volume) containing a complex mechanism consisting of 72 components, each of which requires a variety of meso-or even micro-scale features. We describe the manufacturing processes used to produce these components and features (combinations of high precision, multiply refixtured computer numerical control processes, sink and wire electro discharge machining , laser cutting, etc). These results contribute to the emerging framework of best practices in meso-scale design and manufacture, illustrating ways to effectively combine several processes to produce a complex meso-scale device. Figure 4. The two faces of one of the caps. The two cylindrical protrusions, that are the reference surfaces, are 3.85 mm in diameter and the inter-axis spacing is 6.8 mm.

Each year, billions of dollars are spent by U.S. manufacturers to acquire hard and soft manufacturing technologies. Hard technologies are bundle of equipment, computer hardware and software such as computer numerical control, computer-aided manufacturing, robots, etc. In contrast, soft technologies are manufacturing techniques and know-how such as just-in-time, total quality management, statistical quality control, etc.-hardware is not essential to their successful use but can enhance their scope and effectiveness.

Early detection of pathogens is crucial for the effective surveillance of diseases. Many efforts have been made to explore methods which can detect these pathogens within a short period of time without requiring a tedious protocol. However, these developed methods have disadvantages such as they are relatively time-consuming or require specialized laboratory facilities. In this work, we have developed an integrated microfluidic system for rapid and automatic detection of viruses by direct analysis from fresh Phalaenopsis orchid leaves. The entire protocol, including ribonucleic acid (RNA) purification, reverse transcription loop-mediated-isothermal-amplification (RT-LAMP) and optical detection by measuring changes in turbidity was performed on a single chip. This is the first time that an integrated microfluidic system for the detection of viruses infecting the Phalaenopsis orchid has been demonstrated. The sensitivity of the developed system was also explored in this study to validate its performance.

Although efforts in this field are significant around the world, real prognostics systems are still scarce in industry. Indeed, it is hard to provide efficient approaches that are able to handle with the inherent uncertainty of prognostics and nobody is able to a priori ensure that an accurate prognostic model can be built. As for an example of remaining problems, consider datadriven prognostics approaches: how to ensure that a model will be able to face with inputs variation with respect to those ones that have been learned, how to ensure that a learned-model will face with unknown data, how to ensure convergence of algorithms, etc. In other words, robustness, reliability and applicability of a prognostic approach are still open areas. Following that, the aim of this paper is to address these challenges by proposing a new neural network (structure and algorithm) that enhances reliability of RUL estimates while improving applicability of the approach. Robustness, reliability and applicability aspects are first discussed and defined according to literature. On this basis, a new connexionist system is proposed for prognostics: the Improved-Extreme Learning machine (Imp-ELM). This neural network, based on complex activation functions, enables to reduce the influence of human choices and initial parameterization, while improving accuracy of estimates and speeding the learning phase. The whole proposition is illustrated by performing tests on a real industrial case of cutting tools from a Computer Numerical Control (CNC) machine. This is achieved by predicting tool condition (wear) in terms of remaining cuts successfully made. Thorough comparisons with adaptive neuro fuzzy inference system (ANFIS) and existing ELM algorithm are also given. Results show improved robustness, reliability and applicability performances.

We study a Petri net model of a system composed of two processes sharing a resource. Conflicts may occur over the usage of the shared resource, thus making the system nondeterministic. Therefore, in the context of minimax algebra, it cannot be formulated as a linear system in order to compute its performance measures. However, if the sequence by which the resource is allocated to the two processes is known, we can transform the system into a decision-free net. For this system with an imposed constraint on the resource allocation frequencies, we show that the optimal allocation sequence is the most regular integer sequence satisfying that constraint. We also discuss the periodic behavior of this system under no constraints on the resource allocation frequencies

The industry of machine tools keeps a constant progress that responds to the most demanding market requirements, such as production-time decreasing and zero-defect manufacturing. As part of this progress, sensors and monitoring instruments have been integrated on machine tools, improving computer numerical control (CNC) and monitoring during the manufacturing process. The vibrations are one of the most significant variables to be monitored on machine tools since they directly affect the end piece finishing, tool life expectancy, general machine-tool condition, current consumption, etc. Time domain, fast Fourier transform (FFT), and discrete wavelet transform (DWT) are techniques often used for vibration analysis, because they are computationally efficient for online implementation; unfortunately, it is difficult to find an instrument for vibration analysis that allows individually applying the time, FFT, and DWT techniques, and their fusion. Moreover, the lack of instruments with characteristics such as open architecture, low cost, parallel processing, and continuous online monitoring is remarkable. The contribution of this work consists of developing a vibration-analysis instrument based on the time, FFT, DWT, and DWT-FFT fusion techniques. The instrument is implemented into a low-cost field-programmable gate array with proprietary hardware signal-processing cores in parallel for achieving real-time and continuous online analysis. Experimentation is done to show the proposed methodology efficiency and the developed-instrument versatility, focusing on industrial control applications for CNC machine tools.

In this paper, an integral sliding mode controller (ISMC), based on input-output models, is proposed as a refinement from a two-degree-of-freedom controller with independent objectives for tracking and regulation. Thus, the knowledge of pole placement can be utilized in ISMC. The robustness is improved by a disturbance estimation, which results in an equivalent control. To eliminate the problem of chattering, two measures adopted are an appropriate choice of the sliding surface and an integral control action. It was found that the choice of a slower natural frequency of the sliding surface dynamics than that of the open loop can ease the problem of chattering. The choice of k i , the integral control coefficient, is based on the two-degree-of-freedom controller. Root locus is used in assisting in choosing an appropriate value of k i to ensure the closed-loop stability. The proposed ISMC was implemented and experimentally tested in a mini-CNC machine. The contouring accuracy of the mini-CNC machine was greatly improved by the proposed ISMC. Furthermore, no chattering was observed, which is beneficial to machine actuators.

Multiple Source Cooperation (MSC) techniques, including conventional Code Division Multiplexing (CDM) and Classic Network Coding (CNC) are investigated. We adopt a soft sum-product decoding algorithm for the CNC technique for efficiently processing a large number of information streams and propose a flexible Variable-rate Network Coding (VNC) technique, which is capable of attaining a near-optimum performance. Quantitatively, the proposed VNC method is capable of operating within 1dB from the outage capacity of the quasi-static Rayleigh fading channel. The iterative decoding convergence of the multiple source computation methods is analysed with the aid of EXtrinsic Information Transfer (EXIT) charts.

This paper investigates the maximum throughput for a rechargeable secondary user (SU) sharing the spectrum with a primary user (PU) plugged to a reliable power supply. The SU maintains a finite energy queue and harvests energy from natural resources and primary radio frequency (RF) transmissions. We propose a power allocation policy at the PU and analyze its effect on the throughput of both the PU and SU. Furthermore, we study the impact of the bursty arrivals at the PU on the energy harvested by the SU from RF transmissions. Moreover, we investigate the impact of the rate of energy harvesting from natural resources on the SU throughput. We assume fading channels and compute exact closed-form expressions for the energy harvested by the SU under fading. Results reveal that the proposed power allocation policy along with the implemented RF energy harvesting at the SU enhance the throughput of both primary and secondary links.

A slotted packet broadcast channel with an infinite user population is considered. A limited feedback sensing algorithm is proposed and analyzed for collision versus noncollision binary feedback. The algorithm has maximum throughput equal to 0.42 (packets / slot), has uniformly good delay characteristics within its stability region, and is robust in the presence of feedback errors. A variation of the algorithm, for ternary feedback, attains maximum throughput 0.425 and has uniformly good delay characteristics withfn its stability region. In contrast, the highest tbroughput limited feedback sensing algorithm existing for ternary feedback attains maximum throughput 0.456, but induces relatively high delays for Poisson intensities below 0.3.

Monitoring and control of machining systems has been shown to dramatically improve operation productivity and part quality; however, very little attention has been given to the coordination of multiple complex machining modules. The current practice is to design the module coordination and to debug the resulting computer code in an ad hoc manner. In this paper, the concept of supervisory machining control, in the context of machining module regulation, is presented. The structure of, and elements contained in, a supervisory controller are detailed, and a systematic design procedure for constructing these controllers is presented. The design procedure is utilized to construct a supervisory machining controller which is experimentally implemented in a face milling operation.

We assembled a single carbon nanocoil (CNC) on the tip apex of an atomic force microscope probe by utilizing dielectrophoresis in isopropyl alcohol (IPA). The total assembly process can be achieved within several seconds at room temperature by using a simple apparatus. Three-dimensional finite element simulations have been conducted to investigate the orientation and position of this assembly. Our experiment agrees well with the simulation. The results indicate that it is essential to filter the CNC/IPA suspension and manipulate the capillary meniscus for a single CNC to be vertically assembled on the tip apex. An inclined-edge electrode has, therefore, been suggested and found effectively confining the CNC/IPA suspension around the probe tip.

We consider an Adaptive Random Convolutional Network Coding (ARCNC) algorithm to address the issue of field size in random network coding for multicast, and study its memory and decoding delay performances through both analysis and numerical simulations. ARCNC operates as a convolutional code, with the coefficients of local encoding kernels chosen randomly over a small finite field. The cardinality of local encoding kernels increases with time until the global encoding kernel matrices at the related sink nodes have full rank. ARCNC adapts to unknown network topologies without prior knowledge, by locally incrementing the dimensionality of the convolutional code. Because convolutional codes of different constraint lengths can coexist in different portions of the network, reductions in decoding delay and memory overheads can be achieved. We show that this method performs no worse than block linear network codes in terms of decodability, and can provide significant gains in terms of average decoding delay or memory in combination, shuttle and random geometric networks.

Servomotors are widely used in computerized numerically controlled (CNC) machines, hence motion control is a major topic covered in undergraduate/graduate engineering courses. Despite the fact that several syllabi include the motion dynamics topic in their courses, there are neither suitable tools available for designing and simulating multi-axis motion control nor an efficient link between theory and practice. This paper proposes an educational, open-source tool for teaching motion dynamics in multi-axis servomotor control. The tool allows students to generate multi-axis motion and export these movements for their application to a CNC machine. A simulation module is embedded for evaluating the controller performance. The proposed educational tool allows the use of the inductive pedagogic method to support student learning. Eleven lab practicals are described to show how the proposed tool can be utilized for the systematic teaching of motion dynamics.

In order to enable robotic surgery without human assistance, a means must be developed to change tools. As part of the larger Trauma Pod Project, we developed the Tool Rack Subsystem-an automated tool rack capable of holding, accepting, and dispensing up to 14 tools for the da Vinci T M surgical robot. Borrowing some techniques from industrial automation, we developed a robust system capable of presenting any stored tool in 700ms or less. Tools are positively retained in a sterilizable carousel in a compliant manner designed to accomodate misalignment during tool exchange. RFID equipment is integrated into the system and the tools so that tools can be inventoried and presented by function or serial number instead of rack position. The resulting device has completed testing and integration into the Trauma Pod system and met all its design requirements.

Micro-milling requires both high speed and high accuracy in order to economically produce parts with features on the scale of 1 micron. Because micro-mills are small, they are more flexible than traditional large scale machines and therefore vibration is a problem. Since they also require high positioning precision, even small vibrations of the cutting tool are also an issue. This paper presents a nonlinear command shaping technique to reduce the vibrations of a micro-mill which can be implemented with a standard CNC controller. The robustness of this technique to modelling errors and disturbances is investigated. Theoretical proofs and experimental demonstrations of the command shaping technique are presented. The improved performance from the command shaping technique enables higher throughput and improved accuracy of the machine.

We investigate in this paper a numerical method to control the temperature of an induction heating process through electric current parameters such as frequency and current voltage imposed to the terminals of the inductor. We seek a sinusoidal voltage function whose amplitude varies in time. For this, we use a two-dimensional induction heating model that involves a phase transition in which the magnetic field has only one nonvanishing component. The procedure can be extended to more sophisticated models without major modification of the optimal control problem. We present a numerical control algorithm and discuss numerical experiments that prove the efficiency of the procedure.

The majority of state-of-the-art speech recognition systems make use of system combination. The combination approaches adopted have traditionally been tuned to minimising Word Error Rates (WERs). In recent years there has been growing interest in taking the output from speech recognition systems in one language and translating it into another. This paper investigates the use of cross-site combination approaches in terms of both WER and impact on translation performance. In addition the stages involved in modifying the output from a Speech-to-Text (STT) system to be suitable for translation are described. Two source languages, Mandarin and Arabic, are recognised and then translated using a phrase-based statistical machine translation system into English. Performance of individual systems and cross-site combination using cross-adaptation and ROVER are given. Results show that the best STT combination scheme in terms of WER is not necessarily the most appropriate when translating speech.

In this paper, we consider a cognitive setting under the context of cooperative communications, where the cognitive radio (CR) user is assumed to be a self-organized relay for the network. The CR user and the primary user (PU) are assumed to be energy harvesters. The CR user cooperatively relays some of the undelivered packets of the PU. Specifically, the CR user stores a fraction of the undelivered primary packets in a relaying queue (buffer). It manages the flow of the undelivered primary packets to its relaying queue using the appropriate actions over time slots. Moreover, it has the decision of choosing the used queue for channel accessing at idle time slots (slots where the PU's queue is empty). It is assumed that one data packet transmission dissipates one energy packet. The optimal policy changes according to the primary and CR users arrival rates to the data and energy queues as well as the channels connectivity. The CR user saves energy for the PU by taking the responsibility of relaying the undelivered primary packets. It optimally organizes its own energy packets to maximize its payoff as time progresses.

This paper addresses the analysis of diversitymultiplexing tradeoff (DMT) for a cooperative system using network coding, called the cooperative network coding (CNC) system, which combines a decode-and-forward (DF) relay with the information mixing and broadcast techniques. The outage probability in the high signal-to-noise ratio (SNR) regime is also provided in the closed-form. Our scheme has two users' nodes and one relay node. All nodes are half duplex, i.e., they cannot transmit and receive data at the same time. The two users can communicate to each other directly as well as via the relay node indirectly. Our results show that network coding can help the relay nodes provide cooperative multiplexing gain as well as diversity gain. Compared with the pure DF protocol of which maximal diversity and multiplexing gain are 1 and 1/2, respectively, the maximal diversity and multiplexing gain of the CNC protocol are 2 and 2/3, respectively. The CNC protocol has even better DMT performance than an improved version of DF, selection decode-and-forward (SDF), of which maximal diversity and multiplexing gain are 2 and 1/2, respectively. The impact of wireless lossy channel on performance gains of the network coding is analyzed and can be quantitatively evaluated in the presented DMT curve, which gives us more insight than the capacity analysis does. This is because the capacity analysis only tells us about the maximal error-free transmission rate, while the DMT curve gives us the optimal tradeoff between the error rate and data rate. Index Terms-Cooperative communications, decode-andforward, diversity-multiplexing tradeoff, network coding, outage probability. I. INTRODUCTION Cooperative communications attract a great deal of interests recently. Relay terminals in a cooperative communication system can help the transmitter send information to the receiver. This is similar to a virtual multiple-input multipleoutput (MIMO) system because the terminals in a cooperative network form a virtual antenna array. Clearly, cooperative communication systems can provide diversity gain, which is called cooperative diversity and similar to the space diversity provided by MIMO antenna techniques. Many cooperative communication protocols were proposed to improve diversity gain, which fall into three main categories. The first one is based on the amplify-and-forward (AF), such as orthogonal amplify-and-forward (OAF) [1] and nonorthogonal amplifyand-forward (NAF) [2]. The second one is based on the space-time coding (STC), such as [3]-[5]. The third one is

We report on the fabrication, preliminary metrology, and X-ray transmission results of variable-focus cylindrical beryllium lenses. Each lens consists of a number of 1-mm-diameter lenslets made by precision computer numerical control (CNC) drilling into a beryllium substrate. The substrate is then cut into five parts, each having a different number of lenslets, ranging from 10 to 50. Each lens is then cut diagonally, using an electron discharge machine, to provide it with focusing ability. Unlike the traditional lenses having a fixed focal distance for a given energy, the present lenses provide for a wide range of photon energies and focal distances. Additionally, X-ray transmission through the lens is enhanced by reducing lenslet wall thickness to about 50 mm, the thinnest reported to date. Published by Elsevier B.V.

Multimedia is a cutting-edge approach for channeling information of product to customer. The success of this approach can generally be seen especially to promote, advertise and market product effectively besides staying competitive in global environment. The dramatic reduction in the cost of computer hardware is put forward as the major reason for the increasing importance of computer-aided learning (CAL). Computer-aided learning or CAL usually delivers more realistic views of product to customer. Due to its distinctive characteristics of interactive, user-friendly as well as attractive, people are keen to keep explore and hardly get bored. Compared with the old-fashioned way, CAL applications assist customers to avoid from overlooking necessary information. On the company side, this helps to achieve paperless situation by replacing or reducing the usage of paper. Certainly, this saves a lot of cost in terms of printing manuals, pamphlets and fliers. The case study presented is computer numerical control (CNC) milling machine at CNC Lab, Faculty of Engineering, Universiti Industri Selangor named VMC-1000 produced by GATE company. The multimedia authoring software applied to succeed this study are Macromedia Director, Adobe Illustrator, Adobe Premiere Pro and Gold Wave. This CAL application mainly facilitates in supplying the step-by-step tutorials and machine specification details.

In discrete manufacturing, smooth running of a factory is a goal that is often not attained. Smooth running depends on the ways with which every day problems are tackled on the floor. The efforts of factory floor personnel in this regard are challenged when new technologies are introduced, as is the case with the computer-based manufacturing technologies (CBMT) in the automotive industry. The tactical flexibility of a work station, its ability to deal with the deviations from norm, is argued to be reduced as the CBMT replaces other technologies. This change is accompanied by changes in many factory floor activities. This perspective permits us not only to identify the problems affecting the work stations in modem plants but also the plant-specific solutions to these problems. The data, collected from four Canadian automotive plants through a questionnaire, generally support the framework and are used to draw conclusions relevant for production managers and technological strategists. Shoukry D. Salah received the B.A. Degree from Cairo University, Cairo, Egypt, and the Ph.D. degree in industrial and organizational psychology from Case Western Reserve University, Cleveland, OH. He was formerly the Director of Personnel Research for the Ontario government and is a past Chair of the Department of Management Sciences, University of Waterloo, Waterloo, Ontario, where he has been a Professor since 1969. His work experience includes consulting for industries in North America and overseas. His current research interests include the effects of technology on organizations and the study of the factor which affects technological innovation. Prof. Saleh is a member of the Academy of Management and the Canadian and American Psychological Associations. He is also an affiliate member of the IEEE Engineering Management Society.

An application of field programmable gate arrays (FPGA) to accelerate calculations of the inverse kinematics problem solution for a parallel robot is presented in the paper. The robot is designed for milling by moving a milling cutter along a desired trajectory generated in the Cartesian space. For a position controller of the robot, each point of the trajectory must be transformed into the joint space by the solution of the inverse kinematics problem, thus must be calculated on-line at high frequency. The paper shows how to decrease the calculation time, preserving required accuracy, by augmenting the arithmeticlogic unit (ALU) of a microprocessor with custom instructions. The hardware implementation of the accelerator is described and results of calculations performed in an Altera FPGA chip are analyzed. Index Terms-FPGAs in industrial control systems, controller hardware/software, industrial robots.

This article examines the measurement uncertainty in terms of the incident angle, the object colour and the measurement distance for a Computer Numerical Control (CNC) laser-scanning process. It describes a new method for predicting the measurement uncertainty that simultaneously considers all three parameters. A set of measurements with different values for these parameters was made in order to describe the measurement uncertainty for the whole measuring range of the laser-scanning device. The final result of this research is an equation model that allows an accurate prediction of the measurement uncertainty within the investigated measurement field while the results of the extrapolated measurement field give an accuracy of the prediction that is better than 15%. In general, the model can also be useful as a measuring guideline for any other laser-triangulation measuring device, although the values would need to be adapted to each particular device. The, thus, obtained equation model could then be implemented into automatic inspection/control lines or used for self-adaptive measuring CNC paths to perform measurements in the optimal measuring range for a particular surface.

There has recently been a great demand for the artificial teeth prostheses that are made of materials sintered at 1500 8C, such as zirconia ceramic. It is, however, very difficult for dental technicians to manually fabricate the prostheses with such materials since their degree of strength is very high. For that reason, the prostheses of strong materials have been fabricated by using computer numerical control (CNC) machines. In the CNC fabrication, the most important subject is how accurately the prostheses can be modeled in three-dimensional (3D) space according to dentists' requirements. In this paper, we propose effective methods for modeling single cores such as single caps and Conus cores, which are the principal ones of the artificial teeth prostheses. Our approach employs the two-dimensional Minkowski sum, a developed ZMap algorithm, and other geometric techniques such as the tiling of contours. We also present and analyze the 3D visual examples of the single cores modeled by the proposed methods.

presents a novel approach to recognizing shape features on geometric models composed of both simple and complex ruled surfaces. The algorithm described uses a network of adjacent 2D-laminae (i.e., bounded surfaces) derived from a component's CAD model to both locate and create generic protrusion and depression feature volumes. The approach also enables the automatic generation of alternative feature descriptions and requires no predefined feature libraries.

This paper evaluates proton exchange membrane (PEM) fuel cell microchannel width and depths ranging from 20 μm to 1000 μm. A DRIE process is employed to create the serpentine microflow field patterns from silicon wafers for channel width and depths ranging from 20 μm to 200 μm. To compare the smaller microchannel dimensions with conventional dimensions, computer numerical control (CNC) machining was used to create the 500 μm and 1000 μm flow field channel dimensions in delrin. All of the plates were coated with gold to prevent corrosion and to improve conductivity.Two air-breathing 2.54 cm × 2.54 cm × 1.47 cm fuel cell stacks were designed and assembled for this research. The same membrane electrode assembly (MEA) with an active area of 1 cm2 was tested with all of the silicon flow field plates with microchannels. The fuel cell performed well with the 20-μm width and depth flow channels (maximum power density of 65 W cm−2 or a maximum of 170 mA cm−2 at 0.2 V), although all of the I–V tests yielded good results for room temperature, air-breathing fuel cells. Microchannels with widths and depths from 100 μm to 20 μm look promising for new high-current density microelectro mechanical (MEMS) fuel cell designs.