The steel industry is an important sector of the economy which contributes to the development of a nation through its economy. Although it is considered as energy-consuming and an effort taking sector, it still has benefits regarding its contribution to the economy. The steel industry is capable of producing quality products in a specific amount of time. However, it is significant to recognize that the process is energy-consuming. This consumption creates an issue as energy is required in a very large amount. To address this barrier, steel industry must be more efficient to benefit the economy in such a way that extra costs are less. This could be possible with the use of an effective decision support system (DSS) at various stages of manufacturing steel products and making important decisions.

In general, the use of a multi-agent system and expert skills in the manufacturing of steel products is limited. In addition to it, it is the management which is responsible for analyzing and assessing different operations involved in the process of making steel products. Through the use of different methods, information about quality is generated and shared with employees in the production system for classifying products (G. F. Porzio, et al., 2013).

There is a considerable need for decision making in the production of steel products to ensure that raw material is utilized in an optimal manner. A support system for decision making is considered quite important in each and every department of the industry for making rational decisions in the production process. DSS could be used for combining different resources to get maximum outcomes from the production if raw materials are limited in the process of production.  The support system of decision making is also used in different intelligent systems for making rational and sensible decisions. Good decision making can improve the efficiency of the production department.

There are several support systems for making decisions in the steel manufacturing industry which are utilized in different phases of production. For instance, Kosimeus as a support system for making decisions is used in the methodology of the fuzzy system which incorporates different models utilized in a number of processes. This method enables the management to identify issues occurring in a specific process. In addition to it, it also facilitates management in resolving those issues in a timely manner. There is also a use of sequencing and scheduling as a support system for decisions in manufacturing which helps in deciding how to utilize resources in different types of processes and when to utilize them. In the manufacturing of steel, another support system for making decisions is the plant of NKK which is based on computer knowledge and directly relates to the efficiency of the production system (X. Wang, et al., 2013).

References of  System of Decision Support in Steel manufacturing industry  

G. F. Porzio, et al., 2013. Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems–An example of application to the steel industry.. Applied energy,, Volume 112, pp. 818-833.

X. Wang, Wong, T. N. & Fan, Z. P., 2013. Ontology-based supply chain decision support for steel manufacturers in China.. Expert Systems with Applications,, 40(18), pp. 7519-7533..