Research about the Vibration Parameters for a Cold Rolling Mill Machine

By using the equipments of vibration measurement we can fight against the damages (strip undulation and thickness variation on the length) who is show in while of mill work. The amplitude of vibration parameters determine the apparition of patterns on laminated strip. The researches about the vibration parameters are essential for a product quality. To directly introduce by a milling program, the roll force and the other parameters, these must be in correlation with amplitude acceleration, frequency and velocity vibration

Vibration Diagnosis Systems for a Cold Rolling Mill Machine

In this work is shown the importance to use a monitoring by vibration system for a cold rolling mill machine. The using of this monitoring vibration system reduce maintenance costs, minimize the impact on operation because is monitoring the rolls, the backup rolls, the coupling shaft, the gears from power system. Another advantage is to preventing damage occurring by detecting signs of abnormalities. The accurate prediction of works parameters is essential for a product quality. Currently, a mathematical model is used. It is important to directly predict the roll force and the other parameters, to compute a corrective coefficient Using a mathematical model, we grove up the possibility to obtain a new quality for laminates strip

On the Prediction of the Strip Shape in a Cold Rolling Mill (1700 mm)

In this paper is shown a new way for predicting the precision of laminated strip in a cold rolling mill (1700 mm). The increasing demands on the quality of rolled strip; need new technology for monitoring the strip shape, by using complex system control for technological parameter of the rolling mill process. It is very important to reduce the dynamic load, to choose the optimal functionary parameters and modern systems to control the stress, tensions, lamination force and speed in cold rolling mill machine

Optimisation of the heat treatment of steel using neural networks.

Heat treatments are used to develop the required mechanical properties in a range of alloy steels. The typical process involves a hardening stage (including a quench) and a tempering stage. The variation in mechanical properties achieved is influenced by a large number of parameters including tempering temperature, alloying elements added to the cast, quench media and product geometry, along with measurement and process errors. The project aim was to predict the mechanical properties, such as Ultimate Tensile Strength, Proof Stress, Impact Energy, Reduction of Area and Elongation, that would be obtained from the treatment for a wide range of steel types. The project initially investigated a number of data modelling techniques, however, the neural network technique was found to provide the best modelling accuracy, particularly when the data set of heat treatment examples was expanded to include an increased variety of examples. The total data collected through the project comprised over 6000 heat treatment examples, drawn from 6 sites. Having defined a target modelling accuracy, a variety of modelling and data decomposition techniques were employed to try and cope with an uneven data distribution between variables, which encompassed nonlinearity and complex interactions. Having not reached the target accuracy required the quality of the data set was brought into question and a structured procedure for improving data quality was developed using a combination of existing and novel techniques. IV The stability of model predictions was then further improved through the use of an ensemble approach, where multiple networks contribute to each predicted data point. This technique also had the advantage of enabling the reliability of a given prediction to be indicated. Methods of extracting information from the model were then investigated, and a graphical user interface was developed to enable industrial evaluation of the modelling technique. This led to further improvements enabling a user to be provided with an indication of prediction reliability, which is particularly important in an industrial situation. Application areas of the models developed were then demonstrated together with a genetic algorithm optimisation technique, which demonstrates that automatic alloy design under optimal constraints can now be performed

Analysis, optimization, FE simulation of micro-cutting processes and integration between Machining and Additive Manufacturing.

La seguente Tesi di Dottorato riguarda i processi di Micro-Machining (MM) applicati su materiali ottenuti per fabbricazione additiva. I processi MM sono un insieme di tecnologie di produzione utilizzate per fabbricare componenti o realizzare features di piccole dimensioni. In generale, i processi di taglio sono caratterizzati da un'interazione meccanica tra un pezzo e un utensile che avviene lungo una determinata traiettoria. Il contatto determina una rottura del materiale lungo un percorso definito, ottenendo diverse forme del pezzo. Più precisamente, la denominazione di microlavorazione indica solo le lavorazioni di taglio eseguite utilizzando un utensile di diametro inferiore a 1 mm. La riduzione della scala dimensionale del processo introduce alcune criticità non presenti negli analoghi processi su scala convenzionale, come l'effetto dimensionale, la formazione di bave, la rapida usura dell'utensile, le forze di taglio superiori alle attese e l'eccentricità del moto dell'utensile. Negli ultimi decenni, diversi ricercatori hanno affrontato problemi relativi alla microlavorazione, ma pochi di loro si sono concentrati sulla lavorabilità dei materiali prodotti per Additive Manufacturing (AM). L’AM è un insieme di processi di fabbricazione strato per strato che possono essere impiegati con successo utilizzando polimeri, ceramica e metalli. L'AM dei metalli si sta rapidamente diffondendo nella produzione industriale trovando applicazioni in diversi rami, come l'industria aerospaziale e biomedica. D’altro canto, la qualità del prodotto finale non è comparabile con gli standard ottenibili mediante i metodi convenzionali di rimozione del materiale. Lo svantaggio principale dei componenti realizzati mediante AM è la bassa qualità della finitura superficiale e l'elevata rugosità; pertanto, sono solitamente necessari ulteriori trattamenti superficiali post-processo per adeguare le superfici del prodotto ai requisiti di integrità superficiale. L'integrazione tra le due tecnologie manifatturiere offre opportunità rilevanti, ma la necessità di ulteriori studi e indagini è evidenziata dalla mancanza di pubblicazioni su questo argomento. Questa ricerca mira ad esplorare diversi problemi connessi alla microlavorazione di leghe metalliche prodotte mediante AM. Le prove sperimentali sono state eseguite utilizzando il centro di lavoro ultrapreciso a 5 assi “KERN Pyramid Nano”, mentre i campioni AM sono stati forniti da aziende e gruppi di ricerca. L'attrezzatura sperimentale è stata predisposta per eseguire la micro-fresatura e per monitorare il processo in linea misurando la forza di taglio. Il comportamento di rimozione del materiale è stato studiato e descritto per mezzo di modelli analitici e simulazioni FEM. I metodi FE sono stati utilizzati anche per eseguire un confronto tra le forze di taglio previste e i carichi sperimentali, con lo scopo finale di affinare la legge di flusso dei materiali lavorati. La ricerca futura sarà focalizzata sulla simulazione FE dell'usura dell'utensile e dell'integrità della superficie del pezzo.This thesis is focused on Micro-Machining (MM) processes applied on Additively Manufactured parts. MM processes are a class of manufacturing technology designed to produce small size components. In general, cutting processes are characterized by a mechanical interaction between a workpiece and a tool. The contact determines a material breakage along a defined path, obtaining different workpiece shapes. More specifically, the micro-machining designation indicates only the cutting processes performed by using a tool with a diameter lower than 1 mm. The reduction of the process scale introduces some critical issues, such as size effect, burr formation, rapid tool wear, higher than expected cutting forces and tool run-out. In the last decades, several researchers have tackled micro-machining related issues, but few of them focused on workability of Additive Manufactured materials. Additive Manufacturing (AM) is a collection of layer-by-layer building processes which can be successfully employed using polymers, ceramics and metals. AM of metals is rapidly spreading throughout the industrial manufacturing finding applications in several branches, such as aerospace and biomedical industries. Moreover, the final product quality is not comparable with the standards achievable through the conventional subtractive material removal methods. The main drawback of additively manufactured components in metals is the low quality of the surface finish and the high surface roughness, therefore further post-process surface treatments are usually required to finish and to refine the surfaces of the build product. The embedding between the two technologies offers relevant opportunities, but the necessity of further studies and investigation is highlighted by the lack of publication about this topic. This research aimed to explore several micro-machining issues with regards to Additive Manufactured metals. Experimental tests were performed by using the ultraprecision 5-axes machining center “KERN Pyramid Nano”, while the AM samples were provided by companies and research groups. The experimental equipment was set-up to perform micro-milling and to monitor the process online by measuring the cutting force. The material removal behavior was investigated and described by means of analytical models and FEM simulations. FE methods were employed also to perform a comparison between the predicted cutting forces and the experimental loads, with the final purpose of refining the flow stress law of the machined materials. The future research will be focused on the FE simulation of the tool wear and the workpiece surface integrity by means of specific subroutines

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201

Numerical Modelling and Simulation of Metal Processing

This book deals with metal processing and its numerical modelling and simulation. In total, 21 papers from different distinguished authors have been compiled in this area. Various processes are addressed, including solidification, TIG welding, additive manufacturing, hot and cold rolling, deep drawing, pipe deformation, and galvanizing. Material models are developed at different length scales from atomistic simulation to finite element analysis in order to describe the evolution and behavior of materials during thermal and thermomechanical treatment. Materials under consideration are carbon, Q&T, DP, and stainless steels; ductile iron; and aluminum, nickel-based, and titanium alloys. The developed models and simulations shall help to predict structure evolution, damage, and service behavior of advanced materials

Proceedings of the 7th Sound and Music Computing Conference

Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010