Augmenting an inbound raw material handling system of a steel plant by uncovering hidden logistics capacity

This paper presents an approach for inbound logistics capacity design by uncovering the hidden capacities of a raw material handling system of an integrated steel plant. The traditional analytical approach to capacity augmentation overlooked the possibility of capacity extraction from the existing system which resulted in sub optimal capacity design affecting capital investments and operational expenditures. Using discrete event simulation, we designed a capacity augmentation mechanism which would seek to maximize the utilization of unloading equipments, address system wide congestion and bottlenecks, and better the route layout resulting in released capacity while promoting seamless material flow. Our recommendation included changes in operational procedures, rearrangement of rake scheduling mechanisms, redesigned route network and equipment layout coupled with modest addition of unloading capacity. Our simulation model also showed significant reduction in operations cost through congestion management in the railway networks which resulted in superior ROIs when compared to the traditional approach.