Introduction

Raw materials form the lifeline of any process industry and a continuous and adequate supply is vital to keep the processes running. Typically, for a steel plant, the main raw materials are iron ore (fines and sized), coal (and coke, if necessary), limestone and other fluxes. Each raw material has a particular point of origin that is quite distant from its final consumption point. Thus, raw materials are transported by different transportation modes (viz. trucks, railway rakes, conveyor belts) from their origin point. The suitability of a particular mode of transport depends on the prevailing local conditions at the point of origin, the infrastructure along the transport route, cost, and maintenance implications. Secondly, the frequency and amount of each raw material that would be required needs to be frozen in advance so that the transportation logic in terms of number of carrier units required can be decided.

The Growth Plan of 2.4 MT of Tata Steel envisages a substantial increase in inbound and outbound plant traffic. Additionally, various in-plant movements, such as that of hot metal, intermediate products, slag, waste and reject materials will also increase considerably. Rail transportation will be the principal mode for incoming raw materials, a large share of product dispatch and hot metal movement. In such a situation, it is imperative to assess the capability of the existing loco fleet to cater to the increased demand with the backdrop of capacity sufficiency of the track hoppers, their evacuation rate, stocking pattern and pattern of arrival of each type of raw material train.

Simulation plays an important role in projecting the possible scenarios that are likely to occur in an actual plant. In an earlier work, design, development and implementation of a generic plant logistic software based on the concept of processing units, carriers and path topologies was reported. The software was augmented for the present study for raw material logistics simulation to provide solutions to the following:

• Find the total rake in-rake out time for each type of raw material rake for a future projected scenario.

• Identify the bottlenecks in the system in terms of delays due to non-availability of transport units (locos), unloading stations (tipplers and track hoppers). Also, evaluate if the transport tracks are sufficient and no rake is rejected due to non-availability of tracks at the Reception Yard.

• Arrive at a sufficient number of locos and their combination (big and medium sized locos).

• Evaluate stock levels and storage spaces for the projected scenario.

HOME