Steel Plant Model For Solving Logistic Bottlenecks With Advanced Plant Simulation

Associacao Brasileira de Metalurgia,  Materiais e Mineracao
Frank Schrama
Organization:
Associacao Brasileira de Metalurgia, Materiais e Mineracao
Pages:
9
File Size:
2613 KB
Publication Date:
Aug 16, 2017

Abstract

The Steel Plant Model (SPM) is an advanced logistic simulation model for steel plants. With the SPM, bottlenecks can be solved and logistics can be optimized. Both existing plants and greenfield designs can be simulated. All movements and actions simulated, from hot metal to cast products. Not only all major equipment and their relevant components (like a sublance) are simulated, but also ladles, scrap boxes, transfer cars and cranes. The whole plant is simulated in 3D and actual distances and speeds determine transport times. The SPM includes process time deviations and equipment downtimes for maintenance or unexpected breakdowns. This ensures more realistic and reliable results. Logistic optimization is based on comparison of different scenarios. For a new scenario, equipment and practices, etc. can easily be modified, added or removed. At the same time the SPM produces all relevant data for every new scenario, which can be presented conveniently. This makes the SPM the ultimate tool to find bottlenecks or optimize plant logistics. The SPM is validated for several plants world-wide, with different characteristics and layouts. The SPM not only realistically simulates existing plants with all utilizations, crane movements and waiting times, but also to accurately predicts the influence of plant modifications or unexpected events like breakdowns. Given the flexibility of the SPM, any (new) steel plant can be simulated quickly when a layout and the requested data are provided.
Citation

APA: Frank Schrama  (2017)  Steel Plant Model For Solving Logistic Bottlenecks With Advanced Plant Simulation

MLA: Frank Schrama Steel Plant Model For Solving Logistic Bottlenecks With Advanced Plant Simulation. Associacao Brasileira de Metalurgia, Materiais e Mineracao, 2017.

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