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.

Optimization of process parameters to maximize ultimate tensile strength of friction stir welded dissimilar aluminum alloys using response surface methodology

Abstract: Aluminium alloys generally present low weldability by traditional fusion welding process. Development of the friction stir welding (FSW) has provided an alternative improved way of producing aluminium joints in a faster and reliable manner. The quality of a weld joint is stalwartly influenced by process parameter used during welding. An approach to develop a mathematical model was studied for predicting and optimizing the process parameters of dissimilar aluminum alloy (AA6351 T6-AA5083 H111) joints by incorporating the FSW process parameters such as tool pin profile, tool rotational speed welding speed and axial force. The effects of the FSW process parameters on the ultimate tensile strength (UTS) of friction welded dissimilar joints were discussed. Optimization was carried out to maximize the UTS using response surface methodology (RSM) and the identified optimum FSW welding parameters were reported.

Mathematical model of the SL/RN direct reduction process

Abstract: A mathematical model has been developed to predict the operating behavior of an SL/RN direct reduction kiln from a knowledge of the main process variables. The model is based on steady state principles and is capable of quantitatively describing the different chemical reactions in the kiln such as reduction, Boudouard reaction, coal devolatilization, combustion in the freeboard together with the mass and heat flows. Results of the model, which are in the form of axial temperature profiles in the freeboard gas, solids bed and wall, and axial concentration profiles in the gas and solids, are in good agreement with measurements made on a 200 ton per day pilot plant at the Steel Company of Canada. The model has been used both to investigate the influence of process variables on the kiln performance and to elucidate operating features of the process. The model has shown that highly reactive coals such as subbituminous and lignite, and highly reducible pellets are most suitable for the SL/RN process. It has also demonstrated that the most important process variable from the standpoint of control is the air profile in the kiln; and consequently that heat transfer is the rate controlling step. The model has also been employed to examine scale-up of the SL/RN process by calculating the operating behavior of a large commercial kiln. It has shown that the large kiln should run cooler than the pilot-size unit so that accretion problems may be significantly reduced.

External grind-hardening forces modelling and experimentation

Abstract: Grind hardening process utilizes the heat generated in the grinding area for the surface heat treatment of the workpiece. The workpiece surface is heated above the austenitizing temperature by using large values of depth of cut and low workpiece feed speeds. However, such process parameter combinations result in high process forces that inhibit the broad application of grind hardening to smaller grinding machines. In the present paper, modelling and predicting of the process forces as a function of the process parameters are presented. The theoretical predictions present good agreement with experimental results. The results of the study can be used for the prediction of the grind hardening process forces and, therefore, optimize the process parameters so as to be used with every size grinding machine.

Adaptive process control using function blocks

Abstract: An adaptive control for a process is disclosed which utilizes a process parameter calculator made up of simple function blocks which generate a plurality of process parameters, and a tuning parameter calculator, also made up of simple function blocks, for calculating tuning parameters from the process parameters. The process parameter calculator is provided with values for various disturbances, a set point, a control output from a process controller and process structure data including process sensitivity and nominal operating data. From these values, the process parameters are determined. The tuning parameter calculator is provided in addition to the process parameters, with performance parameters and design function for generating tuning parameters that are applied to the controller for modifying the control output in response thereto.