Data mining in heat treatment

Richard D. Sisson, Aparna Varde

Research output: Contribution to journalReview article

Abstract

Various data mining techniques developed by CHTE to enhance the position of the heat treating industry, by applying fundamental research, to solve problems and to advance heat treatment technology are discussed. A technique, called QuenchMiner™ system, provides decision support in heat treating to optimize the processes involved in heat treatment. CHTE has proposed a technique called AutoDomainMine, which is based on data mining guided by the basic knowledge of the domain. AutoDomainMine helps in estimating a set of input conditions that would produce the desired graph for a heat transfer curve in a quenching experiment. The AutoDomainMine estimation can be used to select process parameters for quenching in the industry. AutoDomainMine is also useful for intelligent tutoring systems in heat treating.

Original languageEnglish
Pages (from-to)18-20
Number of pages3
JournalHeat Treating Progress
Volume6
Issue number2
StatePublished - Mar 1 2006

Fingerprint

Data mining
Heat treatment
Quenching
Intelligent systems
Decision support systems
Industry
Heat transfer
Hot Temperature
Experiments

All Science Journal Classification (ASJC) codes

  • Materials Science(all)

Cite this

Sisson, Richard D. ; Varde, Aparna. / Data mining in heat treatment. In: Heat Treating Progress. 2006 ; Vol. 6, No. 2. pp. 18-20.
@article{bb81e51ee3c04bf8bbfb7f92c7dc0a8e,
title = "Data mining in heat treatment",
abstract = "Various data mining techniques developed by CHTE to enhance the position of the heat treating industry, by applying fundamental research, to solve problems and to advance heat treatment technology are discussed. A technique, called QuenchMiner™ system, provides decision support in heat treating to optimize the processes involved in heat treatment. CHTE has proposed a technique called AutoDomainMine, which is based on data mining guided by the basic knowledge of the domain. AutoDomainMine helps in estimating a set of input conditions that would produce the desired graph for a heat transfer curve in a quenching experiment. The AutoDomainMine estimation can be used to select process parameters for quenching in the industry. AutoDomainMine is also useful for intelligent tutoring systems in heat treating.",
author = "Sisson, {Richard D.} and Aparna Varde",
year = "2006",
month = "3",
day = "1",
language = "English",
volume = "6",
pages = "18--20",
journal = "Heat Treating Progress",
issn = "1536-2558",
publisher = "ASM International",
number = "2",

}

Sisson, RD & Varde, A 2006, 'Data mining in heat treatment', Heat Treating Progress, vol. 6, no. 2, pp. 18-20.

Data mining in heat treatment. / Sisson, Richard D.; Varde, Aparna.

In: Heat Treating Progress, Vol. 6, No. 2, 01.03.2006, p. 18-20.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Data mining in heat treatment

AU - Sisson, Richard D.

AU - Varde, Aparna

PY - 2006/3/1

Y1 - 2006/3/1

N2 - Various data mining techniques developed by CHTE to enhance the position of the heat treating industry, by applying fundamental research, to solve problems and to advance heat treatment technology are discussed. A technique, called QuenchMiner™ system, provides decision support in heat treating to optimize the processes involved in heat treatment. CHTE has proposed a technique called AutoDomainMine, which is based on data mining guided by the basic knowledge of the domain. AutoDomainMine helps in estimating a set of input conditions that would produce the desired graph for a heat transfer curve in a quenching experiment. The AutoDomainMine estimation can be used to select process parameters for quenching in the industry. AutoDomainMine is also useful for intelligent tutoring systems in heat treating.

AB - Various data mining techniques developed by CHTE to enhance the position of the heat treating industry, by applying fundamental research, to solve problems and to advance heat treatment technology are discussed. A technique, called QuenchMiner™ system, provides decision support in heat treating to optimize the processes involved in heat treatment. CHTE has proposed a technique called AutoDomainMine, which is based on data mining guided by the basic knowledge of the domain. AutoDomainMine helps in estimating a set of input conditions that would produce the desired graph for a heat transfer curve in a quenching experiment. The AutoDomainMine estimation can be used to select process parameters for quenching in the industry. AutoDomainMine is also useful for intelligent tutoring systems in heat treating.

UR - http://www.scopus.com/inward/record.url?scp=33745954213&partnerID=8YFLogxK

M3 - Review article

VL - 6

SP - 18

EP - 20

JO - Heat Treating Progress

JF - Heat Treating Progress

SN - 1536-2558

IS - 2

ER -