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.

Optimal process parameter determination for computer‐aided manufacturing

Abstract: Producing high-quality products at low cost is one of the key factors to survival for manufacturing sectors in today's intense global competition environment. One way to gain competitiveness is to integrate product design and process planning into one activity. This study attempts to determine optimal process parameters for a manufacturing process under given design parameters. The process parameters to be determined in this study include process means and process tolerances for particular manufacturing process sequences. The problem is formulated in constrained non-linear optimization, considering both quality- and manufacturing-related costs. The proposed application evaluates alternative product designs and process sequences so that the best associated process parameters can be determined during the early stages of design and planning. This makes the link between CAD and CAM systems more useful and effective. As a result, optimal integration of product design and process planning with minimal production costs and maximal product quality is possible. Copyright © 1999 John Wiley & Sons, Ltd.

Anti-reset windup for controllers in selective control loops

Abstract: A tuning adjustment for a PI controller is disclosed which produces a desired response for a controlled variable in a selective control loop having an external reset feedback signal for anti-reset-windup protection. The desired control effect is evident in the time response of the controlled variables return to set point when a select switches signals and suddenly selects an output limited PI controller to control a process variable, and the selected controller assumes control of the process variable starting with its output at the limiting value. The tuning adjustment is implemented by combining the signal selected for controlling the process variable and a tuning factor for use as the reset feedback signal for the PI controller.

Case study: Level and temperature multivariable control and design via arduino through control loop decoupling

Abstract: In recent years, the use of automatic control has grown exponentially in the world industry, together with the complexity of its plants, which can be explained by the increase in the number of control loops in the same plants. The focus of this work is based on the study and development of temperature and level multivariable control system composed of three tanks, one for mixing and the other two for cold and hot water supply. It is a MIMO (Multiple-Input and Multiple-Output) system with two inputs (hot and cold water) and two outputs (level and temperature process variable), where the system actuators are 12V pumps to control the two input levels. In the second tank, the temperature is controlled independently by a heating resistor. The control actions on the level and temperature variables can be supervised and have their SetPoints changed via a graphical interface. To simplify the controllers tuning, the control loop decoupling technique was used, seeking to decrease the interaction between them. Simulations and tests were performed to choose the best controller configuration, which in turn was embedded in an Arduino MEGA2560 board. The tests carried out showed that the significant interaction between control loops interfere in an incisive way in the controller's performance for large temperature SetPoints. Within a specific range of operation used in this work, the system has proved to be functional.

Nonlinear Model-based Dissolved Oxygen Control in a Biological Wastewater Treatment Process

Abstract: The dissolved oxygen (DO) concentration has been an important process parameter in the biological wastewater treatment process (WWTP). In this paper, we propose a nonlinear control scheme to maintain the dissolved oxygen level of an activated sludge system. Without any linearization or model reduction, it can directly incorporate the nonlinear DO process model with on-line estimation of the respiration rate (R) and the oxygen transfer rate (K La). Simulation results show that it outperforms a control performance of the PID controller. Since it incorporates the process disturbance and nonlinearity in the controller design, the suggested method can efficiently deal with the operating condition changes that occur frequently in the wastewater treatment process.