Cutting force and hole quality analysis in micro-drilling of CFRP

Micro-drilling in carbon fiber reinforced plastic (CFRP) composite material is challenging because this material machining is difficult due to anisotropic, abrasive and non-homogeneous properties and also downscaling of cutting process parameters affect the cutting forces and micro-drilled hole quality extensively. In this work, experimental results based statistical analysis is applied to investigate feed and cutting speed effect on cutting force components and hole quality. Analysis of variance based regression equation is used to predict cutting forces and hole quality and their trend are described by response surface methodology. Results show that roundness error and delamination factor have similar trends to those of radial forces and thrust force, respectively. Non-linear trends of cutting forces and hole quality errors are observed during downscaling of the micro-drill feed value. Optimization results show that cutting forces and hole quality errors are minimum at a feed value which is almost equal to the tool edge radius rather than at the lowest feed value. Therefore, the presented results clearly show the influences of size effects on cutting forces and hole quality parameters in micro-drilling of CFRP composite material.     

Life cycle energy and carbon footprint analysis of photovoltaic battery microgrid system in India

Electricity supply in India is from a centralized grid. Many parts of the country experience grid interruptions. Life cycle energy and environmental analysis has been done for a 27 kWp photovoltaic system which acts as grid backup for 3 h outage in an Indian urban residential scenario. This paper discusses energy requirements and carbon emission for a PV storage system for five different battery technologies in Indian context. This can be used as a metric for comparative analysis for new batteries, with an undeveloped market. The energy requirements for the components are quantified and are compared in terms of energy payback time (EPBT) and Net Energy Ratio (NER). All the calculations are done for Indian context. EPBT is found to be in the range of 2–4.5 years for all the systems, while NER is in the range of 6.6–2.52. NaS has the highest emission factor of 0.67 kgCO₂/kWh and the least for NiCd (0.091 kgCO₂/kWh). These factors can be used to select a PV battery option and to target selection of materials and systems based on the reported values.     

Detection and quantification of valve stiction by the method of unknown input estimation

Valve stiction is one of the most common causes of oscillations in industrial process control loops. Such oscillations can degrade the overall performance of the loop and eventually the final product quality. The detection and quantification of valve stiction in industrial process control loops is thus important. From previous studies in the literature, a sticky valve has been shown to have a distinct signature of the stiction phenomena in its valve positioner data. However, the position of the modulating control valves is seldom available. We consider the problem of estimating the valve position as an unknown input estimation problem. In this work, we propose a novel application of the unknown input estimator in order to estimate the valve position given the process model and the data of the process variable and controller output. Using the estimated valve position, we can detect and also quantify the amount of stiction. We demonstrate the efficacy of the method through simulation examples where a sticky valve is deliberately introduced in the closed loop using a two-parameter stiction model available in the literature. Application of the proposed methodology to a laboratory scale flow control loop is presented. An industrial case study is also presented in which the algorithm accurately detects and quantifies stiction in the level control loop of a power plant.     

FMS scheduling with knowledge based genetic algorithm approach

In this paper a complex scheduling problem in flexible manufacturing system (FMS) has been addressed with a novel approach called knowledge based genetic algorithm (KBGA). The literature review indicates that meta-heuristics may be used for combinatorial decision-making problem in FMS and simple genetic algorithm (SGA) is one of the meta-heuristics that has attracted many researchers. This novel approach combines KB (which uses the power of tacit and implicit expert knowledge) and inherent quality of SGA for searching the optima simultaneously. In this novel approach, the knowledge has been used on four different stages of SGA: initialization, selection, crossover, and mutation. Two objective functions known as throughput and mean flow time, have been taken to measure the performance of the FMS. The usefulness of the algorithm has been measured on the basis of number of generations used for achieving better results than SGA. To show the efficacy of the proposed algorithm, a numerical example of scheduling data set has been tested. The KBGA was also tested on 10 different moderate size of data set to show its robustness for large sized problems involving flexibility (that offers multiple options) in FMS.     

A virtual RV-M1 robot system

Exploring a virtual model under simulated environments is the best way to learn about a real system. This is particularly true in robotics where it is quite expensive to provide the system to each individual. The interdisciplinary area of robotics is being studied commonly in various fields like electrical, computer, mechanical engineering, nanotechnology, etc. A virtual robot system can help one fully understand the controls and working of a robot. The system may also be helpful to design the path and plan the trajectory of a robot in an industrial environment or other robotics application. Virtual model of RV-M1 robot has been developed in the MATLAB environment. The virtual system performs forward kinematics and inverse kinematics in addition to providing a simulation of the robot teachbox.     

Influence of pH on particle size and sensing response of chemically synthesized chromium oxide nanoparticles to alcohols

Nanoparticles of chromium oxide have been synthesized by following a co-precipitation route at various pH values of the precursor solution. Structural and morphological analysis were carried out by using XRD and TEM techniques which revealed that the size of nanoparticles synthesized at pH 9 was smaller as compared to those synthesized at other pH values. The thick films of synthesized samples were deposited on alumina substrate and their sensing response to methanol, ethanol and isopropanol was investigated at different operating temperatures. It was observed that all the sensors gave optimum response at 250 °C. It has been observed that sample prepared at pH 9, being a collection of smallest particles as compared to other samples, exhibited high sensing response to alcohol vapour. Sensor response of all the samples tested was significantly higher towards isopropanol vapour than towards methanol or ethanol.In the present study the effect of particle size on intergranular activation energy has been studied as well. It was found that smaller particles possess high activation energy and exhibit higher sensing response as compared to that of larger particles. This type of study may help in the selection of particle suitable for gas sensing.     

Automated process planning method to machine A B-Spline free-form feature on a mill–turn center

In this paper, we present a methodology for automating the process planning and NC code generation for a widely encountered class of free-form features that can be machined on a 3-axis mill–turn center. The free-form feature family that is considered is that of extruded protrusions whose cross-section is a closed, periodic B-Spline curve. In this methodology, for machining a part with B-Spline protrusion located at the free end, the part is first rough turned to the maximum profile diameter of the B-Spline, followed by rough profile cutting and finish profiling with axially mounted end mill tools. The identification and sequencing of machining volumes is completely automated, as is the generation of actual NC code. The approach supports both convex and non-convex profiles. In the case of non-convex profiles, the process planning algorithm ensures that there is no gouging of the work piece by the tool. The algorithm also identifies when sections of the tool path lie outside the work piece and utilizes rapid traverses in these regions to reduce cutting time. This methodology presents an integrated turn–mill process planning where by making the process fully automated from design with no user intervention making the overall process planning efficient. The algorithm was tested on several examples and test parts using the unmodified NC code obtained from the implementation were run on a Moriseiki mill–turn center. The parts that were produced met the dimensional specifications of the desired part.     

First-principles study of ground-state properties and phase stability of vanadium nitrides

Using a series of density functional electronic structure total energy calculations, we have systematically studied the ground-state properties and phase stability of vanadium nitrides. Comparison of enthalpy of formation shows that V ₂N is equally stable (polymorphic) in , and Fe₂C phases within a few meV. Formation enthalpy of the various phases considered for perfect stoichiometric V N_1.0 shows that it has enhanced stability in hexagonal WC and NiAs structures in relation to NaCl-type δ-phase. The TiAs phase of VN has nearly same energy as NaCl structure. Comparison of energetics of -type , for x=0 and 0.3333 and of , for x=0, 0.0625, 0.125 and 0.25 shows that vacancies on the nitrogen sublattice lowers the formation enthalpy in relation to respective stoichiometric phases which is in agreement with experiments, as bulk vanadium nitrides are known to be generally non-stoichiometric. The calculated dilute heat of solution for the interstitial nitrogen is found to be in good agreement with experimental values and shows that nitrogen prefers to occupy the octahedral sites in bcc vanadium. The α^′-FeN and martensite structures, considered for the metastable phases of vanadium nitrides, have higher formation enthalpy in relation to equilibrium phases. Analysis of electronic density of states of V ₂N shows that the low energy , and Fe₂C phases are characterized by broad V 3d-N 2p and V 3d bonding bands. Density of states of VN shows that in the low energy WC and NiAs phases some of the antibonding states are made empty, leading to a minimum near the Fermi level. For and , density of states shows that vacancies on the nitrogen sublattice introduce additional filled states in the 3d band below Fermi level enabling enhanced bonding. Comparison between bulk moduli and atomic volumes for the various phases of vanadium nitrides shows that higher bulk moduli are dominated by increased V–N bonds combined with low atomic volumes.