scholarly journals Predictive Tools for in-Line Isothermal Extrusion of 6xxx Aluminum Alloys

2021 ◽  
Vol 3 (1) ◽  
pp. 24
Author(s):  
Silvia Barella ◽  
Andrea Gruttadauria ◽  
Riccardo Gerosa ◽  
Giacomo Mainetti ◽  
Teodoro Mainetti

During the last fifty years, the metal forming of aluminum alloys advanced significantly, leading to a more competitive market on which production rate and overall quality are kept as high as possible. Within the aluminum industries, extrusion plays an important role, since many industrial products with structural or even aesthetic functions are realized with this technology. Especially in the automotive industry, the use of aluminum alloys is growing very fast, since it permits a considerable weight loss and thus a reduction of the emission. Nevertheless, the stringent quality standards required don’t allow the use of extruded aluminum alloys produced for common building applications. An important parameter that can be used as an index of the quality of the extruded product is the emergent temperature: if the temperature at the exit of the press is kept constant within a certain limit, products with homogeneous properties and high-quality surface are obtained and the so called “isothermal extrusion” is achieved. As extrusion industries are spread all over the world with different levels of automation and control, a universal but simple on-line tool for determining the best process condition to achieve isothermal extrusion is of particular interest. The aim of this work is to implement this model, which allows evaluation of the thermal gradient which has to be imposed on the billet. Several experiments have been carried out on an industrial extrusion press, and the outer temperature was recorded and compared with the simulated one to demonstrate the model consistency.

1993 ◽  
Vol 37 ◽  
pp. 725-728
Author(s):  
Krassimir N. Stoev ◽  
Joseph F. Dlouhy

Nowadays personal computers [PCs) have sufficiently high speed of calculation and large memory and can be used for precise modeling and implementation of the fundamental parameter methods in the x-ray fluorescence (XRF) analysis. Because of its low price the PC is generally a standard component of energy-dispersive and wavelength-dispersive x-ray fluorescence analyzers, and allows not only automation and control of the whole spectrometer during the scientific experiments or routine analysis, but also complete on-line calculation of concentrations {using sophisticated calibration models), QA/QC monitoring, and archivation of the data. Together with the development of faulti-task operation systems for personal computers the efficiency of their use became higher. A few years ago the main requirement for the software was that it be optimized in order to perform many sophisticated calculations in as short time as possible, and less attention was paid to the interface “computer-user”. Now, with much more powerful new generation PCs, one of the main requirements on the software for XRF analysis is to be “user-friendly”, i.e. not to require special education and extended learning period before using it and to ensure high flexibility of application of the programs.


1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.


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