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Integrated Computational Materials Engineering for Determining the Set Points of Unit Operations for Production of a Steel Product Mix

Integrated Computational Materials Engineering for Determining the Set Points of Unit Operations for Production of a Steel Product Mix
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Author(s): Rishabh Shukla (TCS Research, India), Ravikiran Anapagaddi (TCS Research, India), Amarendra K. Singh (TCS Research, India), Janet K. Allen (University of Oklahoma, USA), Jitesh H. Panchal (Purdue University, USA)and Farrokh Mistree (University of Oklahoma, USA)
Copyright: 2017
Pages: 30
Source title: Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1798-6.ch027

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Abstract

Manufacturing a steel product mix (bar, rod, sheet) involves a series of unit operations - primary steel making, secondary steel making (ladle refining and tundish operation), continuous casting, reheating, rolling and annealing. The properties of the final product depend significantly on how each unit operation is carried out. Each unit operation must be operated to meet the requirements of the subsequent operations. The requirements imposed on a particular unit operation are often conflicting and compromises must be made. Also, there is high degree of uncertainty in the operating parameters of each unit operation, which may lead to considerable deviations from the anticipated performance. To ensure that the final quality specifications of the product is not sacrificed and the customer requirements are met, it is essential to manage the conflict and uncertainty involved in each unit operation of the manufacturing process. In this chapter, we illustrate the use of compromise Decision Support Problem (cDSP) construct and ternary plots to overcome the challenges involved in one of the unit operations, namely, the tundish. The construct can be instantiated for other unit operations to cover the entire manufacturing cycle. Exploring the effects of system variables for each process step through experiments and plant trials is time consuming and very costly. The proposed method allows for faster design exploration of the process and thereby provides a reduced search space to a process designer. The process designer, with reduced experimentation requirements, can explore the narrowed search space to find the operating set points for a tundish. This, in turn, reduces the time and cost involved in production of a steel product mix with a new grade of steel in industry.

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