Process variable

About: Process variable is a research topic. Over the lifetime, 3983 publications have been published within this topic receiving 43130 citations. The topic is also known as: process parameter.

Computational Study and Experimental Comparison of the In-Flight Particle Behavior for an External Injection Plasma Spray Process

Abstract: A three-dimensional computational fluid dynamic (CFD) analysis using Fluent V5.4 was conducted on the in-flight particle behavior during the plasma spraying process with external injection. The spray process was modeled as a steady jet issuing from the torch nozzle via the heating of the are gas by an electric are within the nozzle. The stochastic discrete model was used for the particle distribution. The particle temperature, velocity, and size inside the plasma plume at a specified standoff distance have been investigated. The results show that carrier gas flow rate variation from 2 standard liters per minute (slm) to 4.0 slm can increase the centerline particle mean temperature and mean velocity by 10% and 16%, respectively, at the specified standoff distance. A further increase of the carrier gas flow rate to 6 slm did not change the particle temperature, but the particle velocity was decreased by 20%. It was also found that an increase in the total arc gas flow rate from 52 slm to 61 slm, with all other process parameters unchanged, resulted in a 17% higher particle velocity, but 6% lower particle temperature. Some of these computational findings were experimentally confirmed by Kucuk et al. For a given process parameter setting, the kinetic and thermal energy extracted by the particles reached a maximum for carrier gas flow rate of about 3.5–4.0 slm.

Evaluation of Optimal Parameters for machining with Wire cut EDM Using Grey-Taguchi Method

Abstract: The main objective of this work is to demonstrate the optimization of Wire Electrical Discharge Machining process parameters for the machining of H13 HOT DIE STEEL, with multiple responses Material Removal Rate (MRR), surface roughness (Ra) based on the Grey-Taguchi Method. taguchi'sL27(2 1 x3 8 ) Orthogonal Array was used to conduct experiments, which correspond to randomly chosen different combinations of process parameter setting, with eight process parameters: TON, TOFF, IP, SV WF, WT, SF, WP each to be varied in three different levels. Data related to the each response viz. material removal rate (MRR), surface roughness (Ra) have been measured for each experimental run; With Grey Relational Analysis Optimal levels of process parameters were identified. The relatively significant parameters were determined by Analysis of Variance. The variation of output responses with process parameters were mathematically modeled by using non-linear regression analysis. The models were checked for their adequacy. Result of confirmation experiments showed that the established mathematical models can predict the output responses with reasonable accuracy.

Rare earth-doped integrated glass components: modeling and optimization

Abstract: For the integrated optic erbium-doped phosphate silica-amplifier, a comprehensive model is presented which includes high-concentration dissipative ion-ion interactions. Based on actual waveguide parameters, the model is seen to reproduce measured gains closely. A rigorous design optimization is performed, and the influence of variations in the launched pump power, the core cross section, the waveguide length, the erbium concentration, and the background losses are evaluated. Optimal design proposals are given, and the process reproducibility of the proposed optimal design is examined. Requirements for process parameter control in the wafer fabrication are set up. >

Filling of a complex-shaped mold with a viscoelastic polymer. Part I: The mathematical model

Abstract: A model for the filling stage of injection molding of viscoelastic thermoplastics in cavities of complex shape is presented. The model considers two-dimensional melt flow, with converging and diverging flow patterns induced by complex boundary shape and by the presence of an obstacle. The model is non-isothermal (with the melt loosing heat to the mold walls as it travels into the cavity) and handles a viscoelastic (following the White-Metzner model) material with properties that vary with temperature, shear rate, and pressure. The numerical method is based on finite differences, with boundary fitted curvilinear coordinates used in the mapping of the flow field (which has an arbitrary shape that evolves with time) into a time invariant rectangle. The numerical results reveal geometry-induced asymmetries in the flow and thermal fields as well as the effect of various process parameters on the pressure and temperature profiles in the cavity. The model admits variable cavity thickness, thus allowing for a treatment of the cavity thickness as a process parameter in the simulations.

Process control apparatus with process dependent switching between process control modes

Abstract: The process control apparatus according to the present invention is adapted to control the process automatically in compliance with the state of the process characteristics. In the process control apparatus, when the process characteristics are found to be in a steady state, the control is performed by a first process control operational means suited for sample controlling the process according to the control constants for the first process control operational means as determined during the control of a second process control operational means, while, when the process characteristics vary frequently, the control is performed by the second process control operational means which is suited from sample controlling the process.