Tata Steel has been striving to optimize its operations amidst scarce resources and capacity imbalances. To provide decision support, we developed a mathematical model based on mixed-integer linear-programming (MILP) and hierarchical optimization between 1983 and 1986. It considers marketing constraints, capacities, yields, profitability, routes, energy, and oxygen balances. Its use just for optimal distribution of power has provided a benefit of US $73 million in the first year of implementation (1986–1987). Tata Steel has realized other benefits, such as optimal distribution of scarce oxygen and liquid iron, optimal power cogeneration levels, break-even prices and quantities of purchased scrap, and optimal conversion of semifinished steel into finished products by other companies functioning as conversion agents. In the early ’8Os, the model shifted Tata Steel’s emphasis from maximizing tonnage to maximizing contribution to profits.

The energy crisis is one of the deterrents of economic growth in a developing country like India. Rapid industrialization and poor capacity utilization of power plants make the operations of energy consuming industries like integrated steel plants extremely difficult. This case study discusses the development and implementation of a mixed integer linear programming model for optimal distribution of electrical energy in an integrated steel plant. The model considers the balance equations of capacity, material, thermal and electrical energy, oxygen. It also considers the constraints of yields, product routes, net realizations, variable costs, market demands and commitments to decide not only the hierarchy of shutdowns in the event of a power crisis but also the optimal product mix in each level of power availability. The round-the-clock implementation of the model increased the net profit per ton of saleable steel by 58% in 1986. Since then, the model, which is generic in nature, has been successfully integrated into the decision-making process. The cumulative benefit from this work will be at least 73 million US dollars.

The energy crisis is one of the deterrents of economic growth in a developing country like India. Rapid industrialization and poor capacity utilization of power plants make the operations of energy consuming industries like integrated steel plants extremely difficult. This case study discusses the development and implementation of a mixed integer linear programming model for optimal distribution of electrical energy in an integrated steel plant. The model considers the balance equations of capacity, material, thermal and electrical energy, oxygen. It also considers the constraints of yields, product routes, net realizations, variable costs, market demands and commitments to decide not only the hierarchy of shutdowns in the event of a power crisis but also the optimal product mix in each level of power availability. The round-the-clock implementation of the model increased the net profit per ton of saleable steel by 58% in 1986. Since then, the model, which is generic in nature, has been successfully integrated into the decision-making process. The cumulative benefit from this work will be at least 73 million US dollars.