Multi-criteria Decision Support with SWARA and TOPSIS Methods to the Digital Transformation Process in the Iron and Steel Industry

2021 ◽  
pp. 309-322
Author(s):  
Yıldız Şahin ◽  
Yasemin Bozkurt
2021 ◽  
Vol 13 (5) ◽  
pp. 2832
Author(s):  
Yolandi Schoeman ◽  
Paul Oberholster ◽  
Vernon Somerset

The iron and steel industry is a major global industry that consumes vast quantities of energy and causes environmental degradation through greenhouse gas emissions and industrial waste generation, treatment, and disposal. There is a need to manage complex iron and steel industrial waste in Africa, which requires a system engineering approach to zero waste management as informed by multi-criteria decision-making. The purpose of the current study was to develop a hybrid four-step multi-criteria decision-support model, the i-ZEWATA (Industrial Zero Waste Tiered Analysis). I-ZEWATA acts as a road map to understand, design, assess, and evaluate the iron and steel industrial waste systems with the ultimate objective of moving towards and achieving a zero-waste footprint. The results demonstrate that iron and steel waste can be identified, visualized, prioritized, and managed to promote zero-waste by applying a system-engineered approach. Additionally, relationship patterns to environmental, social, operational, and economic aspects with system behavioral patterns and outcomes were identified. It was clear from the case study in South Africa that, although technology and solution investment is essential, waste management, valorization, and treatment components require a concerted effort to improve industrial waste operational management through effective zero-waste decision-support towards a circular economy.


2012 ◽  
Vol 268-270 ◽  
pp. 1657-1660 ◽  
Author(s):  
Hong Bo Ren ◽  
Yu Wang ◽  
Rong Luo ◽  
Ji Min Yu

As the construction of enterprise informatization in the iron and steel industry has increasingly matured, it leads enterprise to accumulate a large number of business data that can not be used effectively. So the enterprise lack of data information for auxiliary decision-making activities. This paper puts forward a construction of the iron and steel industry sales system based on BI. Combining sales information management with decision analysis for integrated solutions can handle daily business, effectively extract and analyze enterprise historical data into useful information which provides decision support for enterprises.


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