Multi-Zone Proportional Hazard Model for a Multi-Stage Degradation Process

Conditional-based maintenance (CBM) decision-making is of high interests in recent years due to its better performance on cost efficiency compared to other traditional policies. One of the most respected methods based on condition-monitoring data for maintenance decision-making is Proportional Hazards Model (PHM). It utilizes condition-monitoring data as covariates and identifies their effects on the lifetime of a component. Conventional modeling process of PHM only treats the degradation process as a whole lifecycle. In this paper, the PHM is advanced to describe a multi-zone degradation system considering the fact that the lifecycle of a machine can be divided into several different degradation stages. The methods to estimate reliability and performance prognostics are developed based on the proposed multi-zone PHM to predict the remaining time that the machine stays at the current stage before transferring into the next stage and the remaining useful life (RUL). The results illustrate that the multi-zone PHM effectively monitors the equipment status change and leads to a more accurate RUL prediction compared with traditional PHM.

Study of the Effect of Anode/Cathode Geometry on the Yield Rate and Quality of the MWCNTs Synthesized by Submerged Arc Discharging

The main objective of the present paper is to clarify the effect of anode/cathode geometry combinations on the yield rate and quality of the Multiwalled Carbon Nanotubes (MWCNTs) produced by submerged arc discharge technique. The effects of current intensity and the discharging medium (solvent) are also investigated. The morphology and crystalline perfection of the produced MWCNTs are confirmed by transmission electron microscopy (TEM) and Electron diffraction. Thermogravimetric analysis (TGA) is conducted to check the quality of the MWCNTs in a quantitative manner. The flat ended anode/cathode combination of diameters 4 and 12 mm respectively exhibited the highest yield at 70 A using deionized water as solvent. Through careful selection of the process parameters, the yield rate of MWCNTs obtained is found to be higher than most of the reported values in literature. However, the best quality of MWCNTs with purity as high as 95%, average thermal stability of 745°C as well as good batch homogeneity, is obtained with KCl solution and tapered male/female anode combination. The best quality MWCNTs is used successfully as reinforcement for A356 aluminum silicon composite.

Combined Temperature and Force Control for Robotic Friction Stir Welding

The objective of this research is to develop a closed-loop control system for robotic friction stir welding (FSW) that simultaneously controls force and temperature in order to maintain weld quality under various process disturbances. FSW is a solid-state joining process enabling welds with excellent metallurgical and mechanical properties, as well as significant energy consumption and cost savings compared to traditional fusion welding processes. During FSW, several process parameter and condition variations (thermal constraints, material properties, geometry, etc.) are present. The FSW process can be sensitive to these variations, which are commonly present in a production environment; hence, there is a significant need to control the process to assure high weld quality. Reliable FSW for a wide range of applications will require closed-loop control of certain process parameters. A linear multi-input-multi-output process model has been developed that captures the dynamic relations between two process inputs (commanded spindle speed and commanded vertical tool position) and two process outputs (interface temperature and axial force). A closed-loop controller was implemented that combines temperature and force control on an industrial robotic FSW system. The performance of the combined control system was demonstrated with successful command tracking and disturbance rejection. Within a certain range, desired axial forces and interface temperatures are achieved by automatically adjusting the spindle speed and the vertical tool position at the same time. The axial force and interface temperature is maintained during both thermal and geometric disturbances and thus weld quality can be maintained for a variety of conditions in which each control strategy applied independently could fail.

Virtualize Manufacturing Capabilities in the Cloud: Requirements and Architecture

In recent years, Cloud Manufacturing concept has been proposed by taking advantage of Cloud Computing to improve the performance of manufacturing industry. Cloud Manufacturing attempts can be summarized as two sectors, i.e. manufacturing version of Computing Cloud, and a distributed environment that is networked around Manufacturing Cloud. In this paper, manufacturing resource, ability and relevant essentials are discussed in the service-oriented perspective. The functional requirements of a Cloud Manufacturing environment are discussed, along with an interoperable manufacturing system framework. Cloud resource integration models are developed that are compliant with existing international standards. It is possible to achieve a collaborative, intelligent, and distributed environment via Cloud Manufacturing technologies.

Fabrication and Characterization of Photonic Crystals by Two-Photon Polymerization Using a Femtosecond Laser

Two-photon polymerization is a powerful technique in fabricating three dimensional sub-diffraction-limited structures. Recently, new sol-gel material, SZ2080, was introduced into two-photon polymerization and was proved to be better than the conventional materials for its negligible shrinkage. In this paper, two-photon polymerization was applied to generate woodpile structures, one kind of photonic crystal, using SZ2080. First, the relationship between scanning speed, laser power and resolution was determined through fabricating free-hanging lines. Based on this relationship, woodpile structures with different period distances were fabricated with high uniformity as shown by SEM images. Then optical properties of woodpile structures were investigated using Fourier Transform Infrared Spectroscopy (FTIR) and a quantitative relationship between band gap and period distance was established.

Analytical Modeling and Experimental Validation of Force Ripple and Friction Force for General Direct Drive Systems

In this paper, we present a systematic modeling method of direct drive systems. Experiments are designed to decouple and model friction and force ripple separately, which are two major sources of tracking error. Three different optimization methods, least square method, nonlinear least square method and particle swarm optimization are used for parameter optimization. The analytical form of the model makes it easy to use in engineering practices. All results are obtained and verified experimentally. The method presented in this paper can also be used to model other mechanical systems.

Effect of Inter-Particle Interaction on Particle Deposition in a Cross-Flow Microfilter

Recent studies show that inter-particle interaction can affect particle trajectories and particle deposition causing fouling in the microfilters used for metal working fluids (MWFs). Inter-particle interaction depends on various factors: particle geometry and surface properties, membrane pore geometry and surface properties, MWF’s properties and system operating conditions, etc. A mathematical model with a Langevin equation for particle trajectory and a hard sphere model for particle deposition has been used to study the effect of particle’s size, particle’s surface zeta potential, inter-particle distance, and shape of membrane pore wall surface on particle trajectory and its deposition on membrane pore wall. The study reveals that bigger particles have a lesser tendency to be deposited on membrane pore walls than smaller particles. The shape of the membrane pore wall surface can also affect the particle deposition behavior.

Model Learning in a Multistage Machining Process: Online Identification of Force Coefficients and Model Use in the Manufacturing Enterprise

This work presents a systems approach in machining process control. Traditional force-based machining process control has been focused on single machine-single operation. The force or power sensor is used to measure the instantaneous force/power, and control action is taken by changing the feedrate in real time to follow a given force setpoint. The application of such control has successfully been implemented to prevent chatter and to elongate tool life by minimizing tool wear. This research seeks to extend the application of control algorithms to learn about the machining system (comprised in this context of a workpiece being operated on in progressive machining), and how knowledge generated by the process can be passed on to the next process for optimization. To demonstrate this, turning of a partially hardened bar is explored. A nonlinear mechanistic force model-based control framework attempts to control the cutting force at a designated setpoint, with material properties changing over the cut. The force coefficients for the material are calculated offline using experimental data and Bayesian inference methods. Since the hardened part of the bar will shift the force coefficient values, an online estimation strategy (Bayesian Recursive Least Square estimator) is used to learn the new coefficients as well as satisfying the control objective. With the newly learned coefficients passed downstream, the subsequent operation experiences no compromise of control objective as well reduces the maximum values of force encountered. Numerical analyses presented show the adaptation and control scheme performance.

Characterization of Fluid Film Produced by an Atomization–Based Cutting Fluid (ACF) Spray System During Machining

The atomization–based cutting fluid (ACF) spray system has recently been proposed as a cooling and lubrication solution for machining hard to machine materials (e.g. titanium alloys). On the tool rake face, the ACF spray system forms a thin film from cutting fluid that penetrates into the tool–chip interface to improve tool life. The objective of this work is to characterize this thin fluid film in terms of thickness and velocity for sets of ACF spray parameters. ACF spray experiments are performed by varying impingement angle in order to observe the nature of the spreading film, and to determine the film thickness at different locations after impingement of the droplets. It is observed that the film spreads radially outward producing three fluid film development zones (i.e. impingement, steady, unsteady). The steady zone is found to be between 3 and 7 mm from the focus (impingement point) of the ACF spray for the set of parameters investigated. An analytical 3D thin fluid film model for the ACF spray system has also been developed based on the equations for continuity of mass and momentum. The model requires a unique treatment of the cross–film velocity profile, droplet impingement and pressure distributions, as well as a strong gas–liquid shear interaction. The thickness profiles predicted by the analytical film model have been validated. Moreover, the model predictions of film velocity and chip flow characteristics during a titanium turning experiment reveal that the fluid film can easily penetrate into the entire tool–chip interface with the use of the ACF spray system.

Dilute Acid Pretreatment of Wheat Straw: A Predictive Model for Energy Consumption Using Response Surface Methodology

Response surface methodology was used to study the effects of parameters namely, time, temperature, and solid content and to optimize the process conditions for the minimum energy consumption in dilute acid pretreatment. Box-Behnken design using response surface methodology was employed. Effects of time and temperature are significant at the significant level of α = 0.05. Longer time and higher temperature result in higher power energy consumption. The best optimal values of the process conditions are time 14–21 min and temperature 129–139 °C.