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.

Background: “Malaria and malnutrition are closely related in the months of hunger gap when malnutrition is at its peak often coincides with rainy season when the number of malaria cases shoot up. The disease combines in a vicious circle. Children sick with malaria are more likely to become dangerously malnourished”. Severely malnourished children with malaria infection may have no fever, or be hypothermic. Proactive screening for malaria in severely malnourished children is needed even if the child has no symptoms of malaria. The objectives of the study were to estimate prevalence of “malaria and malnutrition” co-existence in under 5 children of tribal dense regions and to determine if any significant difference between this co-existent condition against the disease alone.Methods: Eight villages were selected based on their inaccessibility and demography spread across Bamnipal and Sukinda region. Malaria testing using antigen based RDK and nutritional assessment using MUAC tapes were conducted in of 6 months to <5 yrs children.Results: A total of 224 children of under 5 yrs age group were screened. 50.4% of them were suffering from malaria, 38% of the children were at risk or suffering from severe acute malnutrition. Of the 113 children with malaria, 45% were having malnutrition. Out of 86 malnourished children 59% were diagnosed with malaria. 22.7% of children were found to have malaria and malnutrition together.Conclusions: Malaria and Malnutrition are co-existent and synergistic to each other.