The decision support system in steel manufacturing is used to contribute to the processes from the initial stage to the very last stage. In the initial stage, the production process is being used in the manufacturing process with more economical rate of the price. The ultimate purpose of the production process is to get maximum output with minimum input. In this process, there is a need for support system for making decisions which could be used in making rational decisions to improve different techniques of artificial intelligence, cognitive science and machine language. When a computer system is used as a tool for dealing with issues to increase the efficiency of the production system, it is referred to as the support system for making decisions.

The support system for making decisions is recognized as a knowledge-based system since the information related to information is associated with machine language. The support system for making decisions could be helpful in overcoming obstacles in combining different resources to provide information about machine learning and artificial intelligence (P. Cowling, 2003).

The support system for making decisions is utilized in the industry of steel production for identifying different issues occurring in its operations and effectively resolving them. This support system is quite convenient in resolving issues. In addition to resolving issues, it can also help in making rational and optimal decisions about the utilization of resources. Decision making support system is very important in every department of the industry to make rational decisions in the production process. DSS could be used in combining different resources to get optimum results from the production if raw materials are limited. The support system for making decisions is also utilized in artificial intelligence to make effective decisions. Making effective and rational decisions can serve to improve the efficiency of the production department. Regardless of the industry and organization, the objective of the management is almost similar. This objective is concerned with increasing efficiency and improving performance at low costs. When it comes to the steel industry, there are several examples of organizations using DSS for improving efficiency and reducing costs. These organizations have implemented different support systems for identifying issues and have effectively improved their operational effectiveness. The management has used these methods to determine issues and making better and rational decisions about resolving these issues (C. Gao & Tang, 2008).

References of  support systems in this industry can capitalize on the new technologies such as machine learning, artificial intelligence, big data, and the internet of things etc. to improve the decision-making process.

C. Gao & Tang, L., 2008. A decision support system for color-coating line in steel industry.. In 2008 IEEE International Conference on Automation and Logistic, pp. 1463-1468.

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.

M. KARATAŞ & Gecili, H., 2012. The role of decision support systems in steel industry.. Engineering Science & Technology, an International Journal, 15(1).

P. Cowling, 2003. A flexible decision support system for steel hot rolling mill scheduling.. Computers & Industrial Engineering,, 45(2), pp. 307-321..

P. Cowling, 2003. A flexible decision support system for steel hot rolling mill scheduling. Computers & Industrial. Computers & Industrial Engineering,, 45(2), pp. 307-321.

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..