University of Twente Student Theses


A Methodology for Evaluating Decision Support Systems in the realm of Steel Ladle Logistics

Keshetti, Akhil Raja (2024) A Methodology for Evaluating Decision Support Systems in the realm of Steel Ladle Logistics.

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Abstract:The research to make the manufacturing processes energy efficient and sustainable is imperative. Given the significant production demand and energy consumption, the iron and steel industry plays a predominant role in this endeavor. The adoption of Industry 4.0 by the steel industry is essential for enhancing manufacturing processes' energy efficiency and environmental sustainability. Advanced Analytics emerged as the core pillar of Industry 4.0 owing to its capabilities of digitizing collection, storing, and various methods of analyzing data, offering invaluable insights for fulfilling sustainability goals. The steel-making industry can implement such analytics to make the production process energy efficient, given the availability of necessary historical data. In the steel-making process, steel ladle logistics is a prominent operation, that can be made energy-efficient using Advanced Analytics. Steel Ladle Logistics refers to the management, monitoring and transportation of ladles used in steel-making process. The scientific landscape has State-of-the-Art decision support systems built using mathematical models to generate optimal ladle logistics schedules. But the practical applicability of these solution methods remained uncertain, due to the absence of robust methodologies in literature that can be adopted to validate the usability in real-time. As a result, the primary motivation of the study is to fill the gap in literature by proposing an validation methodology by adopting simulation techniques. By integrating a simulation model (that replicates the real world dynamics of steel ladle logistics) along side the optimization model, feasibility to respect the system constraints and comparative analysis on the system performance was evaluated. It was aimed to analyse the feasibility of carrying out model generated decisions without conflicts and respecting minimum tapping temperature constraint in real time. The methodology suggests to identify a set of sustainability indicators that can be adopted to realize the effect of optimization model results on system performance. In this research study, $CO_2$ emissions and steel temperature losses are chosen and analysed as sustainability indicators of steel ladle logistics.
Item Type:Essay (Master)
Tata Steel IJmuiden, IJmuiden, The Netherlands
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:51 materials science, 54 computer science, 83 economics
Programme:Business Information Technology MSc (60025)
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