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SMS Siemag AG - Alu-web.de

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ALUMINIUM RoLLINg INDUSTRY<br />

können mittels „neuronaler Netze“ Mo<strong>de</strong>lle<br />

gebil<strong>de</strong>t wer<strong>de</strong>n, die selbstlernend die Energiedaten<br />

interpretieren. Mit <strong>de</strong>ren Hilfe lässt<br />

sich <strong>de</strong>r Energieverbrauch abbil<strong>de</strong>n und für<br />

die Zukunft vorhersagen. Eine verlässliche<br />

Vorhersage <strong>de</strong>s Energiebedarfs hilft <strong>de</strong>n Energieversorgern,<br />

auf Bedarfsschwankungen<br />

zu reagieren und dies durch günstigere Tarife<br />

zu honorieren. Alternativ können die gewonnenen<br />

Informationen für eine individuelle<br />

Beschaffungsstrategie genutzt und <strong>de</strong>r Strom<br />

direkt auf <strong>de</strong>m Energiemarkt eingekauft wer<strong>de</strong>n.<br />

Autor<br />

Dr. Jesper Mellenthin ist Projektmanager Energieeffizienz<br />

im Geschäftsbereich Elektrik und Automation<br />

bei <strong>SMS</strong> <strong>Siemag</strong> <strong>AG</strong>, Düsseldorf.<br />

also logs the product type and the quantities<br />

produced. That puts consumption and production<br />

in relation to each other and supplies<br />

key performance indicators. In turn, these indicators<br />

calculated from different measured<br />

values make it possible to compare plants or<br />

situations.<br />

If analysts do not want production data or<br />

conditions shown quantitatively in key performance<br />

indicators, they use curves instead.<br />

A curve takes account of the fact that un<strong>de</strong>r<br />

certain circumstances in the production process<br />

the key performance indicators can have<br />

different values. For example at high capacity<br />

utilisation, lower energy consumption per<br />

product unit can be achieved than during periods<br />

of low production. Combining key performance<br />

indicators with the variables means<br />

similar conditions can be compared and the<br />

various plant situations usefully evaluated.<br />

Furthermore, <strong>SMS</strong> <strong>Siemag</strong> is currently <strong>de</strong>veloping<br />

a prediction tool. Based on already<br />

saved energy data, production data and the<br />

future production plan, the tool uses ‘neuronal<br />

networks’ and self-learning to generate<br />

mo<strong>de</strong>ls that interpret the energy data. It can<br />

be used to map and predict energy consumption.<br />

A reliable prediction of energy <strong>de</strong>mand<br />

helps energy utilities react to fluctuations in<br />

<strong>de</strong>mand and offer cheaper tariffs. Alternatively,<br />

the information gained can be used for an<br />

individual sourcing strategy for direct purchasing<br />

of electricity on the energy market.<br />

Author<br />

Dr. Jesper Mellenthin is project manager Energy<br />

Efficiency in the Electrics and Automation division<br />

of <strong>SMS</strong> <strong>Siemag</strong> <strong>AG</strong> in Düsseldorf, Germany.<br />

Danieli <strong>Alu</strong>minium Technology Forum 2013<br />

Latest breakthrough technology in industrial operation<br />

B. Rieth, Meerbusch<br />

This year’s Technology Forum by Danieli<br />

was very much focused on the processing<br />

of aluminium. In a two-day symposium<br />

held at its headquarters in Buttrio<br />

in northern Italy, around 150 invited<br />

guests from the international aluminium<br />

industry were presented with the company’s<br />

latest <strong>de</strong>velopments in the sectors<br />

of rolling and processing high-gra<strong>de</strong><br />

aluminium strips and plates, extruding<br />

profiles and roll-casting aluminium rod.<br />

Other topics of the presentations were<br />

plant automation and drive technology as<br />

well as know-how support and servicing.<br />

The successful event was roun<strong>de</strong>d off by<br />

a tour of Danieli’s workshops and – as a<br />

particular highlight – a joint flight of the<br />

participants to Belgium to see the cold<br />

rolling mill supplied by Danieli Fröhling<br />

for automobile strips to Aleris in Duffel.<br />

The participants, from 73 companies<br />

in 36 countries, were given interesting<br />

insights during the event into Danieli’s<br />

latest technologies for a broad segment of<br />

the aluminium value chain.<br />

© Danieli<br />

Gianpietro Bene<strong>de</strong>tti, chairman and CEO of<br />

Danieli & C. …<br />

In his welcoming address Danieli chairman<br />

and CEO Gianpietro Bene<strong>de</strong>tti laid stress on<br />

the leading role his company has played for<br />

many years in the <strong>de</strong>velopment of the most<br />

mo<strong>de</strong>rn technologies for the metallurgical<br />

industry, that is the production and processing<br />

of steel and NF metals. The globally active<br />

company foun<strong>de</strong>d by the brothers Danieli in<br />

1914 has meanwhile become the nucleus of a<br />

worldwi<strong>de</strong> network of highly specialised companies<br />

in the sector of plant and machinery<br />

engineering, each with various core interests<br />

and each a market lea<strong>de</strong>r in its own field. With<br />

an annual turnover of some three billion euros<br />

… and Franco Alzetta, COO of Danieli & C.<br />

during their opening addresses<br />

and more than 10,000 employees worldwi<strong>de</strong>,<br />

Danieli is today one of the largest plant engineering<br />

groups in the metallurgical sector.<br />

In past years the core products of the group<br />

and hence also its main expertise and growth<br />

performance were governed almost exclusively<br />

by steel. However, the market downturns<br />

seen by steel in the more recent past,<br />

54 ALUMINIUM · 11/2013

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