Details
| Original language | English |
|---|---|
| Pages (from-to) | 679-689 |
| Number of pages | 11 |
| Journal | Production Engineering |
| Volume | 12 |
| Issue number | 5 |
| Publication status | Published - 8 May 2018 |
Abstract
Constantly increasing quality requirements and ever-stricter conditions pose difficult challenges for the foundry industry. They must produce the high-quality components demanded by the market at a reasonable cost. Modern technologies and innovative methods help to master this challenge. Until recently, production, from the design of the aluminum melting furnace to daily process, relied largely on traditional methods and experience. However, important data and information about the melting process—for example, the temperatures and the shape of the aluminum block in the furnace—can hardly be obtained with conventional experimental methods, as the temperatures exceed 700 °C. Therefore, this research project investigates the method of monitoring a melting process by means of optical sensors for the first time. The purpose of this paper is to predict the surface shape of the block during the melting process, as it is not possible to maintain a constant monitoring due to the heat and energy loss during measurement Behrens (Einsatz einer Lichtfeldkamera im Hochtemperaturbereich beim Schmelzvorgang von Aluminium, wt Werkstattstechnik online, 2016). To generate the necessary data, a 3D light-field camera is installed on top of an aluminum melting furnace in order to monitor the process. The basic idea is to find a general method for curve modeling from scattered range data on the aluminum surface in 3D space. By means of the (x, y, z) data from the 3D camera, the aluminum surface is modeled as a polynomial function with coefficient derived using various interpolation and approximation methods. This study presents an attempt to find the optimal polynomial function model that describes the aluminum surface during the melting process by interpolation or approximation methods. The best method for curve fitting will be extended and implemented for surface modeling. Based on this method, the melting process can be better controlled while the furnace operates continuously under stable conditions and the efficiency can therefore be increased. The proposed model can be modified for a wide variety of melting furnaces.
Keywords
- Aluminum surface model, Approximation, Interpolation, Light-field camera, Melting process, Polynomial function
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Production Engineering, Vol. 12, No. 5, 08.05.2018, p. 679-689.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Modeling of an aluminum melting process using constructive polynomial functions
AU - Mohammadifard, Sara
AU - Stonis, Malte
AU - Langner, Jan
AU - Sauke, Sven Olaf
AU - Khosravianarab, Farzaneh
AU - Larki Harchegani, Hossein
AU - Behrens, Bernd Arno
N1 - Funding Information: Sponsored by the German Federal Ministry of Economics and Energy on the basis of a decision of the German Federal Parliament (Project name: Edusal II, sponsor number: 03ET1056B). The responsibility for the contents of this publication lies with the author. Publisher Copyright: © 2018, German Academic Society for Production Engineering (WGP). Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/5/8
Y1 - 2018/5/8
N2 - Constantly increasing quality requirements and ever-stricter conditions pose difficult challenges for the foundry industry. They must produce the high-quality components demanded by the market at a reasonable cost. Modern technologies and innovative methods help to master this challenge. Until recently, production, from the design of the aluminum melting furnace to daily process, relied largely on traditional methods and experience. However, important data and information about the melting process—for example, the temperatures and the shape of the aluminum block in the furnace—can hardly be obtained with conventional experimental methods, as the temperatures exceed 700 °C. Therefore, this research project investigates the method of monitoring a melting process by means of optical sensors for the first time. The purpose of this paper is to predict the surface shape of the block during the melting process, as it is not possible to maintain a constant monitoring due to the heat and energy loss during measurement Behrens (Einsatz einer Lichtfeldkamera im Hochtemperaturbereich beim Schmelzvorgang von Aluminium, wt Werkstattstechnik online, 2016). To generate the necessary data, a 3D light-field camera is installed on top of an aluminum melting furnace in order to monitor the process. The basic idea is to find a general method for curve modeling from scattered range data on the aluminum surface in 3D space. By means of the (x, y, z) data from the 3D camera, the aluminum surface is modeled as a polynomial function with coefficient derived using various interpolation and approximation methods. This study presents an attempt to find the optimal polynomial function model that describes the aluminum surface during the melting process by interpolation or approximation methods. The best method for curve fitting will be extended and implemented for surface modeling. Based on this method, the melting process can be better controlled while the furnace operates continuously under stable conditions and the efficiency can therefore be increased. The proposed model can be modified for a wide variety of melting furnaces.
AB - Constantly increasing quality requirements and ever-stricter conditions pose difficult challenges for the foundry industry. They must produce the high-quality components demanded by the market at a reasonable cost. Modern technologies and innovative methods help to master this challenge. Until recently, production, from the design of the aluminum melting furnace to daily process, relied largely on traditional methods and experience. However, important data and information about the melting process—for example, the temperatures and the shape of the aluminum block in the furnace—can hardly be obtained with conventional experimental methods, as the temperatures exceed 700 °C. Therefore, this research project investigates the method of monitoring a melting process by means of optical sensors for the first time. The purpose of this paper is to predict the surface shape of the block during the melting process, as it is not possible to maintain a constant monitoring due to the heat and energy loss during measurement Behrens (Einsatz einer Lichtfeldkamera im Hochtemperaturbereich beim Schmelzvorgang von Aluminium, wt Werkstattstechnik online, 2016). To generate the necessary data, a 3D light-field camera is installed on top of an aluminum melting furnace in order to monitor the process. The basic idea is to find a general method for curve modeling from scattered range data on the aluminum surface in 3D space. By means of the (x, y, z) data from the 3D camera, the aluminum surface is modeled as a polynomial function with coefficient derived using various interpolation and approximation methods. This study presents an attempt to find the optimal polynomial function model that describes the aluminum surface during the melting process by interpolation or approximation methods. The best method for curve fitting will be extended and implemented for surface modeling. Based on this method, the melting process can be better controlled while the furnace operates continuously under stable conditions and the efficiency can therefore be increased. The proposed model can be modified for a wide variety of melting furnaces.
KW - Aluminum surface model
KW - Approximation
KW - Interpolation
KW - Light-field camera
KW - Melting process
KW - Polynomial function
UR - http://www.scopus.com/inward/record.url?scp=85046668235&partnerID=8YFLogxK
U2 - 10.1007/s11740-018-0831-2
DO - 10.1007/s11740-018-0831-2
M3 - Article
AN - SCOPUS:85046668235
VL - 12
SP - 679
EP - 689
JO - Production Engineering
JF - Production Engineering
SN - 0944-6524
IS - 5
ER -