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Technical Brief

Design Exploration for Determining the Set Points of Continuous Casting Operation: An Industrial Application

[+] Author and Article Information
Rishabh Shukla

Tata Consultancy Services,
Pune 411013, India
e-mail: rishabh.shukla1@tcs.com

Sharad Goyal

Tata Consultancy Services,
Pune 411013, India
e-mail: sharad.goyal@ceat.in

Amarendra K. Singh

Tata Consultancy Services,
Pune 411013, India
e-mail: amarendra.singh@tcs.com

Jitesh H. Panchal

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: panchal@purdue.edu

Janet K. Allen

The Systems Realization Laboratory @ OU,
The University of Oklahoma,
Norman, OK 73019
e-mail: janet.allen@ou.edu

Farrokh Mistree

The Systems Realization Laboratory @ OU,
The University of Oklahoma,
Norman, OK 73019
e-mail: farrokh.mistree@ou.edu

1Present address: Research and Development Centre, CEAT Tires, Vadodara, India.

2Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received June 20, 2014; final manuscript received February 6, 2015; published online March 2, 2015. Assoc. Editor: Xiaoping Qian.

J. Manuf. Sci. Eng 137(3), 034503 (Jun 01, 2015) (5 pages) Paper No: MANU-14-1334; doi: 10.1115/1.4029786 History: Received June 20, 2014; Revised February 06, 2015; Online March 02, 2015

To compete with other materials and/or contribute toward light-weighting of vehicles, newer grades of steel are continuously invented and experimented upon. Due to the costs and time involved in such developments, manufacture of new grades of steel at an industrial scale is difficult. We propose a method that is useful for steel manufacturers interested in producing a steel product mix with new grades of steels by predicting the required change in the operating set points of each unit operation in the manufacturing chain of products with the new grade of steel. Here, we demonstrate a method to determine the set points of one unit operation, continuous casting which is measured in terms of conflicting objectives including productivity, quality, and production costs. These parameters are sensitive to the operating set points of casting speed, superheat, mold oscillation frequency, and secondary cooling conditions. To ensure targeted performance and address the challenges of uncertainty and conflicting objectives, an integrated computational method based on surrogate models and the compromise decision support problem (cDSP) is presented. The method is used to explore the design space available for casting operations and determine operating set points to meet requirements imposed on the caster from subsequent downstream processes. This method is of value to the steel industry and enables the rapid and cost effective production of a product mix with a new grade of steel.

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References

Figures

Grahic Jump Location
Fig. 2

Region depicting set of weights for meeting requirement on (a) CLS, (b) productivity, and (c) variance in productivity

Grahic Jump Location
Fig. 3

Superposition of regions depicting sets of weights for each goal

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