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Automated Procedure for Roll Pass Design.

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Title: Automated Procedure for Roll Pass Design.
Authors: Lambiase, F.1, Langella, A.1 antgella@unina.it
Source: Journal of Materials Engineering & Performance. Jun2009, Vol. 18 Issue 3, p263-272. 10p. 10 Diagrams, 5 Charts, 1 Graph.
Subjects: Computer software development, Expert computer system software, Computer integrated manufacturing systems, Automation, Industrial engineering equipment, Artificial intelligence, Simulation methods & models, Control theory (Engineering)
Abstract: The aim of this work has been to develop an automatic roll pass design method, capable of minimizing the number of roll passes. The adoption of artificial intelligence technologies, particularly expert systems, and a hybrid model for the surface profile evaluation of rolled bars, has allowed us to model the search for the minimal sequence with a tree path search. This approach permitted a geometrical optimization of roll passes while allowing automation of the roll pass design process. Moreover, the heuristic nature of the inferential engine contributes a great deal toward reducing search time, thus allowing such a system to be employed for industrial purposes. Finally, this new approach was compared with other recently developed automatic systems to validate and measure possible improvements among them. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Materials Engineering & Performance is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: <searchLink fieldCode="DE" term="%22Computer+software+development%22">Computer software development</searchLink><br /><searchLink fieldCode="DE" term="%22Expert+computer+system+software%22">Expert computer system software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+integrated+manufacturing+systems%22">Computer integrated manufacturing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+engineering+equipment%22">Industrial engineering equipment</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Control+theory+%28Engineering%29%22">Control theory (Engineering)</searchLink>
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  Data: The aim of this work has been to develop an automatic roll pass design method, capable of minimizing the number of roll passes. The adoption of artificial intelligence technologies, particularly expert systems, and a hybrid model for the surface profile evaluation of rolled bars, has allowed us to model the search for the minimal sequence with a tree path search. This approach permitted a geometrical optimization of roll passes while allowing automation of the roll pass design process. Moreover, the heuristic nature of the inferential engine contributes a great deal toward reducing search time, thus allowing such a system to be employed for industrial purposes. Finally, this new approach was compared with other recently developed automatic systems to validate and measure possible improvements among them. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Materials Engineering & Performance is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11665-008-9289-2
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        Text: English
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      – SubjectFull: Expert computer system software
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      – SubjectFull: Computer integrated manufacturing systems
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      – SubjectFull: Automation
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      – SubjectFull: Industrial engineering equipment
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      – SubjectFull: Simulation methods & models
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      – SubjectFull: Control theory (Engineering)
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              Text: Jun2009
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