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Automated Procedure for Roll Pass Design

  • F. Lambiase
  • A. Langella
Article

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.

Keywords

automated process design expert system roll pass design process simulation 

Nomenclature

A

Cross-sectional area

Ah

Parameter of Shinokura’s model

As

Parameter of Shinokura’s model

Available list

List that stores the nodes that are not still inspected

D(x)

Difference function

Dep

Depth level in the search tree. Number of passes which precede the current one

H

Height

Hi

Maximum function (choice the highest value)

ID

Identification of a node during path search

INPUT

Defined as an input of sequence search

Lo

Minimum function (choice the lowest value)

MPN

Most promising node

N

Number of sequence passes

NAID

Next available ID

NotAvailable list

List that stores the nodes already inspected

R

Rolls radius

Ratio

Ratio of horizontal to vertical cross-section dimensions of rolled shape

S

Shape

W

Width

f

Evaluation function

ε

Convergence parameter used for the evaluation of W gropt

γ

Shinokura’s model costant

λ

Elongation ratio

\( \uplambda _{N}^{k} \)

Elongation ratio of the kth pass of a sequence composed of N passes

Subscripts

c

Current

circ

Circumscribed groove shape

dad

Parent node

gr

Rolls groove

gropt

Optimized groove

inc

Entering Bar

ins

Inscribed groove shape

max

Upper limit of groove dimension

mid

Average value of lower and upper limits of groove dimension

min

Lower limit of groove dimension

out

Rolled bar

tot

Entire sequence

Superscripts

e

Equivalent rectangle

i

Optimal groove dimension iteration

References

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Copyright information

© ASM International 2008

Authors and Affiliations

  1. 1.Department of Materials and Production EngineeringUniversity of Naples Federico IINaplesItaly

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