Megabytes for metals: development of computer applications in the iron and steel industry (original) (raw)
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IEEE Annals of the History of Computing, 2000
This article focuses on the growth of production planning in the Dutch Hoogovens Steel Company. In response to market changes in the 1950s, production facilities and capacity were enormously expanded, and a decentralized just-in-time system of production planning was developed. Punchedcard machines were introduced to process the necessary data. In spite of these efforts a control crisis emerged in the companx resulting in large order backlogs and long delivery times. In response, production planning was centralized and digital computers introduced. This article will demonstrate that the choice of computing technologies was intimately related to the organization of production planning. Although the introduction of just-in-time systems is normally considered a consequence of the evolution of computing technologH in this case such a system appears to have contributed to the demand for digital computers. The question that will be posed is, to what extent do these views corroborate those expressed in James Beniger's book The Control Revolution ?
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The Copper Mining and Smelting Complex Bor (RTB Bor) in the Republic of Serbia has a long history of computer control and computer-aided data processing. Working within the confines of the Cold War era, RTB implemented and developed four generations of computers, becoming a major influence in the IT sector and the primary computer training resource in the region.
Digitalization in Hot and Cold Rolling Mills
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The demands made by the market on the steel industry will again become significantly greater in the near future.Examples of this are the expansion of the product mix, the production of smaller batch sizes, higher quality requirements, and lower prices. The paper presents possible responses of the equipment builder to these challenges. Digitalisation concepts should in particular support production engineering (hot/cold rolling) to the effect that new, mostly high-strength materials can be produced in an economically efficient way to hence allow their speedy introduction on the market.
Expert Systems Controlling the Iron Making Process in Closed Loop Operation
Expert Systems, 2010
An alternative to the production route described above is the COREX® process. It produces liquid hot metal, just like a blast furnace, but can be charged with coal instead of coke, thus eliminating the need for a coke plant. Sinter is not required either, because lump ore or pellets are used as iron carrier feed material. 1.2 Automation systems After starting of the automation age, blast furnaces were soon equipped with so called basic automation systems, in order to automatically control more and more parts of the furnace operation (sequence logic). However, the operational setpoints were determined by experienced engineers. Soon, the need was felt to take away the "magic" of determining setpoints and replace it with science. So, one of the first such applications were charge models, which calculate-under the assumption that all input and output streams are known-based on material balance calculations, which materials have to be charged by which amount, to get the desired results, which are hot metal and slag with a certain chemical composition. Following this example more and more process models were developed, initially used only offline in some computer centres, and then with the advent of cheaper and more powerful personal computers more and more online. However, there was still a lot of art in controlling the blast furnaces, because it was not possible to find proper algorithms for the problems at hand, and so the experience of the operators and the engineers still had a major impact on the performance of a blast furnace. In the 1970's and 80's artificial intelligence techniques were slowly finding their way from universities and research centres into the "real world". Rule based expert systems and later fuzzy logic based systems were the leaders of this development. Neural networks and other data based techniques soon followed. Steel producers were not shy to experiment with these technologies and investigated whether they can benefit from them (Gottlob & Nejdl, 1990).