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.

Model predictive controller

Abstract: A model predictive controller for a process control system which includes a real-time executive sequencer and an interactive modeler The interactive modeler includes both a process model and an independent disturbance model The process model represents the dynamic behavior of the physical process, while the disturbance model represents current and future deviations from the process model The interactive modeler estimates current process states from the process model and input data received from the executive sequencer The executive sequencer then projects a set of future process parameter values, which are sought to be controlled, over a predetermined control horizon The interactive modeler then solves a set of equations as to how the physical process will react to control changes in order to determine an optimized set of control changes As a result, the process control system will be able to accurately track a predetermined set-point profile in the most effective and cost efficient manner

Parametric process optimization to improve the accuracy of rapid prototyped stereolithography parts

Abstract: The functional requirements of a rapid prototyping system are speed and accuracy, and they are both functions of vendor defaulted and user selected manufacturing parameters. Accuracy is evaluated by dimensional errors, form errors and surface roughness of manufactured parts. A specially designed specimen with 20 dimensional, geometrical, and surface roughness features has been used in the inspection of RP manufacturing processes. In terms of Taguchi experimental design techniques, an orthogonal array of experiments has been developed which has the least number of experimental runs and desired process parameter settings. Using a 3-D coordinate measuring machine and surface profilometer, a series of measurements in evaluating the SLA parts quality has been conducted to find the functional relationships between the output part quality and input manufacturing process parameters. Two analysis tools, response surface methodology and Analysis of Variance (ANOVA), have been used to evaluate the SLA RP process and to perform the product optimization. The optimal setups of SLA manufacturing parameters for both individual features and a general part with various features have been concluded from this study.

Method for setting and adjusting process parameters to maintain acceptable critical dimensions across each die of mass-produced semiconductor wafers

Abstract: A method and system are disclosed for: (a) matching a machine-implemented process simulator with an actual fabrication line, (b) using the matched model to simulate the statistical results of mass production by the modeled production line, (c) using the model to predict cross-reticle variance from collected data for in-scribe features, (d) using the model to decompose the variance contributions of each process parameter and identify the more prominent contributors, and (e) using the model to identify the process parameter adjustments which would provide best leverage when taken one at a time.

Model predictive control apparatus and method

Abstract: A model predictive control apparatus and method for controlling the operation of a process (34) having a process input signal (Xk) and a process output signal (Yk), which includes determining a predicted process output signal (Yk+n+m+2) at a future steady state condition according to a process model, determing a steady state error signal according to the difference between the predicted process output signal and a desired set point signal (Ysp), and determining a set of future process input change signals (x) requires to correct for the estimated steady state error (e) by providing at least one step response in the process output at a future time. The next net process input change is then applied according to the sum of the currently determined first element of the set of future process input change singals (x) summed with any future process input change signals that were previously calculated for the next process input change signal that is calculated according to this method. The model is expressed in velocity form. Process tuning parameters are available to dampen the net process input change as well as the currently determined first element of the process input change with respect to a process input change signal that is calculated according to the steady state error divided by the steady state process gain.

Method and apparatus for automated pre-treatment and processing of biological samples

Abstract: The present invention concerns a method and apparatus for automatic processing a biological sample on a carrier, perhaps robotically, by applying predetermined amounts of reagents in a predetermined sequence according to a processing protocol, the processing including pre-treatment steps, under the control of an adaptive processing control system using a sample process parameter input that may be independent and an independent process parameter memory that does not interrupt process operation when being used, such that samples may be added or removed without interrupting the processing of other samples. Also included is an image capture function for sample and reagent identification and process monitoring, as well as temperature regulation and environmental control functions.