AMI Automation offer a complete and fully integrated suite of systems to support operations of the steel making processes, from customer orders to the delivery of products, tracking and controlling material used, plant/process performance, product quality and cost ($/ton), customer requirements, and asset usage.
This Digital OT suite includes:
Production Control Modules
Production Planning
Create Shop Orders from one or more Customer Orders that are optimum for production and determine when they should be produced to maximizes the use of the installed capacity.
Production Scheduling
Generates a Production Schedule for the Meltshop/Caster/Mill by finding the right combination and sequence of Orders given physical capacity of the plant and production rules.
Production Coordination
Determine in real-time how heat should be placed in the melt shop under the current melt shop conditions, to assure arriving on time at the caster with the least use/loss of energy.
Scrap Control Modules
Scrap Buying Optimization
Help the buyer determine the best scrap mix to buy that will contribute to produce liquid steel at the least cost ($/Ton) and meets the requirements of the Production Plan and inventory levels.
Scrap Inventory System
Keeps track of all scrap operations in the yard (reception, consumption, movement, audit/adjustment, etc.) and maintains an accurate and up-to-date inventory of it.
Scrap Recipe Optimization
Determines the best (least cost liquid steel) Scrap Recipe for a Heat considering grade/customer order residual limits, scrap availability, time to melt and volume restrictions.
Bucket Preparation System
Guides the scrap operators to prepare scrap buckets (and trucks) according to the corresponding Scrap Recipe. It tracks in detail all the scrap loaded into the bucket and finally charged in the furnace.
Scrap Characterization (New)
Scrap optimization modules use the characteristics of each type of available scrap (yield, residual content, kwh, density, etc.). This module determines and adjusts those parameters dynamically learning from history to make scrap optimization modules even more accurate.