The hydraulic AGC system of aluminum cold rolling mill is directly related to the quality and effectiveness of cold rolling aluminum sheet strips. Traditional PID control becomes difficult to satisfy the necessity of improving the control performance of cold rolling mill. High precision, simple and effective control strategies are very important for the …
In this research, the effective indexes in the cold roll-forming procedure that can affect the energy utilization and required maximum torque of the forming line have been investigated and optimised using NSGA-II and type-2 fuzzy neural networks. The effective parameters were strip thickness, bending angle increment, flange width, inter-distance between the …
Son et al. (2005) designed an online learning ANN to predict the rolling force in a hot-rolling mill for steel strips. A mathematical model based on rolling theory, the …
Machine learning is the core of industry 4.0, the fourth industrial revolution, which is in progress in manufacturing industries. Machine learning tools like linear regression, logistic regression ...
Roofing sheets roll forming machines produce long sections of ribbed metal roofing profiles via continuous bending and gradual shaping from coiled strip stock. ... Roofing sheet roll formers incrementally bend sheet metal into arched ribbed profiles: Process: Continuous bending into progressive die forms by motorized flower rollers:
This paper deals with the application of Fuzzy-Neural Networks (FNNs) in multi-machine system control applied on hot steel rolling. The electrical drives that used in rolling system are a set of ...
PI controller in outer loop for the strip exit thickness while PD controller is used in innerloop for the work roll actuator position and roll eccentricity compensation …
textile, aluminum, and steel productions. T. Matinetz, P. Protzel, and O. Gramckow, in 1994 [2], gave a brief survey of the different control aspects with Neural Network. Alaa …
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mechanical properties (TableA2), and physical properties (TableA3) of the hot rolled low carbon steel (AISI A36). A 4-fluted helical uncoated carbide end mill cutter with diameter (D = 12.7 mm), shown in Figure2a, was used in all tests. All tests were run on a 3-axis Hass minimill CNC vertical milling machine with a maximum spindle speed of ...
This work deals with the application of Fuzzy-Neural Networks in multi-machines system control is considered as cold rolling mill. Drivers of rolling system are a set of DC motors, which have ...
The rolling was performed at 500 °C in a single stand mill with roll diameters of 250 ... Prediction of springback in wipe-bending process of sheet metal using neural …
Fuzzy neural networks represent an innovative blend of fuzzy logic and neural networks, offering a powerful approach to handle complex, non-linear problems that are hard to model with traditional…
exhibits a great practical application potential in steel manufacturing. Keywords Machine learning model ·Cold rolling process ·Selective work roll cooling ·Strip flatness ·Steel manufacturing Introduction Cold rolling and rolling-based processes have been widely used to manufacture various sheet metallic materials (Deng
R. Hwang et al. utilized deep neural networks to predict roll force of the Steckel Mill based on meta-features calculated from physics based equations (Hwang, Jo, Kim, & Hwang, 2020). Roll force for each pass was predicted using pass specific information and information from previous passes.
A kind of PID controller based on fuzzy RBF neural network is proposed to the problem that traditional PID controller is difficult to achieve good control effect because of the …
Supervised learning algorithms mainly include artificial neural networks (ANN) and support vector machines (SVM) in the field of steel surface defect detection [13] [14][15][16]. Unsupervised ...
Precise selective cooling control of work roll can significantly improve the cold rolled strip flatness in steel manufacturing industry. To improve the control accuracy of the coolant output of selective work roll cooling control system, a machine learning (ML) algorithm with differential evolution-gray wolf algorithm optimization support vector machine regression …
A Simulink and mathematical models have been proposed in this study in order to control the thickness in a rolling mill process. The simulation results show that the thickness oscillation can be manipulated with high accuracy by using NARMA-L2, since it can remove the non-linearity of servo system and other disturbances complexities. The …
The aluminum is prone to surface defects of varying degrees during its manufacturing process, which seriously affects the usage performance. At present, the aluminum industry has realized the automation of the production process, but the defect detection of the product surface is the manual visual inspection method in most cases …
The hot rolling and cold rolling control models of silicon steel strip were examined. Shape control of silicon steel strip of hot rolling was a theoretical analysis model, and the shape control of cold rolling was a data-based prediction model. The mathematical model of the hot-rolled silicon steel section, including the crown genetic model, inter …
A finite element model (FEM) roll-forming procedure was utilised to extract the appropriate datasets for this study. type-2 fuzzy neural network (T2FNN) is not employed in cold roll-forming ...
Fuzzy Logic, Genetic Algorithm (GA), and Support Vector Machine (SVM) are being extensively used in different manufacturing industries since last 3 decades. In a review paper published in
A model based on an artificial neural network (ANN) has been developed for prediction of flatness of cold rolled (CR) sheet in a tandem cold rolling mill for white goods applications. Various process parameters including roll bending, roll shifting, tensions between stands etc., which affect flatness of CR sheet are considered in the model. …
In addition, T-S fuzzy neural networks [17], support vector regression [18], extreme learning machines [19], and stacked generative adversarial networks [20] have also been widely applied to ...
In this paper, we propose a machine learning based framework to establish a model that accurately predicts roll forces at each mill stands of the hot strip rolling mill. In contrast to the traditional models, the proposed expert system considers an individual model for each rolling stand and employs rolling history when predicting roll forces.
This work deals with the prediction of mechanical properties of hot rolled steel slab in the hot rolling mill to avoid the manual working of preparing tension test samples in the mechanical ...
2. ALUMINUM SHEETS. Shaping an aluminum sheet begins with the same process as an aluminum plate. Aluminum plates pass through a continuous rolling mill to further reduce plate thickness. The final step for the aluminum sheet is cold rolling, where aluminum sheets compress between two rollers, reducing material thickness up to 50%.
3.2 Data Pre-processing. In surface inspection systems commonly applied in the steel industry, especially on hot products, raw data often need to be prepared and pre-processed before the subsequent elaboration stages, in order to remove unreliable data [] and reduce them in a form suitable to ML systems [].In the present application, raw data …
The proposed ANNs methodology and the respective software system are implemented within the EU H2020 project LoCoMaTech for the aluminium-based sheet forming process HFQ (solution Heat treatment, cold die Forming and Quenching). In this paper, a methodology and a software system will be presented concerning the use of …
Ashland Aluminum has the expertise to produce flat-rolled aluminum coil, precision-rolled aluminum coil, and cold-rolled aluminum strip. (800)688-0140. What Is Cold Rolled Aluminum | Ashland Aluminum. Search for: Serving all of the US, Canada & Mexico ... A rolling mill is impressive, simply due to its sheer size and extreme rolling strength. ...
This paper deals with the application of Fuzzy-Neural Networks (FNNs) in multi-machine system control applied on hot steel rolling. The electrical drives that used in rolling system are a set of ...
This paper selects historical production data from a cold rolling industrial site. The corresponding process parameters of hot rolling are obtained as the basis for model training through an …
This research will be helpful in all industries that use rolling mill machines such as 4-high mill, 6-high mill, and clustering mill in hot and cold rolling. View Show abstract
From roll bending, a complex wave shape appears in the rolled steel plates. In order to solve this problem, an AS-U roll is used to control the vertical rolling load on the plate. A neural-fuzzy control is applied to the shape control system in a ZRM because of the complexity, nonlinearity, and multi-input multi-output (MIMO) characteristics of ...
Fuzzy-Neural Control of Hot-Rolling Mill ... (FNNs) in multi-machine system control applied on hot steel rolling. The ... plates, strips, and sheets,
The hydraulic AGC system of aluminum cold rolling mill is directly related to the quality and effectiveness of cold rolling aluminum sheet strips. Traditional PID control becomes …
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