Fuzzy neural networks control for hydraulic AGC system of aluminum …

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 …

Multiobjective Optimization of Roll-Forming Procedure

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 …

A study on on-line learning neural network for prediction for …

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 …

(PDF) Application of Artificial Neural Network for Flow …

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

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:

(PDF) Fuzzy-neural control of hot-rolling mill

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 ...

[PDF] Strip Thickness Control of Cold Rolling Mill with Roll

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 …

Fuzzy-Neural Control of Hot-Rolling Mill

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 …

Prefinished Aluminum Sheets & Sheet Metal

Wieland-Wrisco Industries Inc., the prefinished aluminum specialist can benefit your business with more than fifty colors, a wide assortment of gauges and the largest ready-to-ship inventory of prefinished aluminum sheet and coil in the industry! Prefinished Painted Aluminum, Anodized, 70% PVDF, Mill Finish Aluminum, Coil Coated Aluminum …

Evolutionary Optimization of Machining Parameters …

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 ...

FUZZY-NEURAL CONTROL OF COLD-ROLLING MILL

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 ...

Application of artificial neural networks for the prediction of …

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 …

Integrating Fuzzy Logic with Neural Networks: A Python

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…

A novel strategy based on machine learning of selective …

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

Multistep networks for roll force prediction in hot strip rolling mill

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.

Study on PID controller based on fuzzy RBF neural network …

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 …

Detection and Classification of Surface Defects of Cold Rolling Mill

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 ...

Principle of selective cooling control system of work roll

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 …

Design of control system for steel strip-rolling mill using …

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 …

Adaptive convolutional neural network for aluminum …

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 …

Whole process prediction model of silicon steel strip on …

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 …

Illustration of the roll forming machine (a), the working principle …

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 ...

Application of Machine Learning in Rolling Mills: Case …

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

Prediction of shape defects over length of cold rolled sheet …

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. …

Rolling force prediction in cold rolling process based on …

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 ...

A study on on-line learning neural network for prediction for rolling

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.

Prediction of Mechanical Properties of Low Carbon Steel …

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 ...

Aluminum Rolling Mills Explained

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%.

Flatness Defect Detection and Classification in Hot Rolled Steel …

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 …

Using artificial neural networks to model aluminium based sheet …

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 …

What Is Cold Rolled Aluminum | Ashland Aluminum

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. ...

(PDF) Fuzzy-Neural Control of Hot-Rolling Mill

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 ...

Rolling force prediction in cold rolling process based on …

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 …

Shape Performance Improvement of a …

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

Shape Performance Improvement of a Sendzimir Mill …

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

Fuzzy-Neural Control of Hot-Rolling Mill ... (FNNs) in multi-machine system control applied on hot steel rolling. The ... plates, strips, and sheets,

Fuzzy neural networks control for hydraulic AGC system of …

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 …

Aluminum Hot Rolling Mill

ALUMINUM HOT ROLLING MILL — HIGH-QUALITY PRODUCT & MAXIMUM MATERIAL YIELD Primetals Technologies provides a full range of aluminum hot rolling mills for both new and revamp projects. …

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