Steel is produced in basic oxygen furnaces (BOF) and in electric arc furnaces (EAF). Steel casting is done through continuous casters and by ingot teeming. Depending on method of casting, profiles, and sizes, semi-products (ingots, blooms, billets) are transported downstream through production supply chain. As could be seen from the scheme the melting and casting are the key stages of production. That is why melt shop and casting scheduling is so important for the company.
The old scheduling process was arranged in the following way. Input data was prepared in manual mode by 5 specialists, who prepared requirements for casting based on planned orders of rolling mills. Based on the requirements, specialists created melt shop and caster schedules. These schedules had sufficient accuracy on the horizon of 4 – 7 days. Beyond this horizon the accuracy significantly deteriorated. Scheduling took much time and efforts. Rolling mills requirements changes or deviations from the schedule in many cases lead to rescheduling. Often because of high laboriousness rescheduling was done after the end of working days or on weekends. Absence of rolling mills requirements beyond 1-2 week horizon significantly reduces efficiency of decision making of planners. Also data quality needed to be improved. Manufacturing execution systems monitored only general volumes of production without accounting for heats, heats sequencing, and without information about allocated orders.
As a result the company had high level of work in process and low due date performance. It was logical that the issue of rearranging of scheduling process and improving its efficiency was open.
General task formulation of melt shop and caster scheduling
Melt shop and caster schedules are normally generated at least once a day—sometimes more often. Thousands of orders must be combined and sequenced for production through iron making, steelmaking, and continuous casting. Each time this occurs, the planner tries to balance multiple business objectives, which exist in a tradeoff relationship.
The first goal of melt shop and caster scheduling is to produce orders on time, that is, to minimize order earliness and order lateness . The desired production time for each order at casting is usually given by some higher level production planning function, which balances order loads across the entire plant. Planners try to respect this requirement by scheduling each order for production on the day that it was requested. If orders are produced too early, unnecessary inventory may result. If orders are produced late, customer delivery performance suffers and unnecessary expediting costs may be incurred.
The second goal of melt shop and caster scheduling is to maximize tundish utilization . For each steelmaking grade, there is some maximum number of heats that can be cast using a single tundish. When the maximum is reached, the tundish must be switched out and relined with new refractory. Maximizing tundish utilization reduces operating cost per ton, minimizes the number of “top” and “bottom” slabs (or blooms, or billets) as a percent of total production, and helps keep liquid steel flowing for as much calendar time as possible. The Czech plant has several casters, and some portion of the order book is often considered to be “swing orders,” able to be produced at alternative casters. Tundish utilization can normally be improved by intelligent allocation of swing orders to casters during the caster scheduling process.
The third goal is to minimize grade and width transitions within the tundish. Minimizing grade transitions improves prime yield, as material from the chemical transition zone may have limited usefulness for customer orders. Reducing the number and severity of slab width transitions is important for flat products producers, as it reduces wear on both casting and hot rolling equipment, reduces breakout risk, and can improve prime yield.
The fourth goal is to minimize the amount of stock within the melt shop and caster schedule, and focus production on current demand. As manufacturing orders are combined into heats, and heats into tundish sequences, stock (or “open order”) material must sometimes be inserted, to fill out a heat or extend tundish length. Production of stock is usually a waste of precious manufacturing time, since it cannot be converted immediately into revenue, but lingers in inventory.
The fifth goal of melt shop and caster scheduling is to minimize over-grading. Each customer order has alloy requirements that must be satisfied. In order to fill out heats, extend tundish length or avoid grade transitions, orders are sometimes “over-graded,” that is, a more expensive chemistry is used to satisfy an order than is actually required by the customer. Thus minimization of over-grading reduces alloy costs.
For integrated steelmaking plants—those with blast furnace operations—there is a sixth goal: control of liquid iron inventory. In every such plant, the fleet of torpedo cars that transport liquid iron from the blast furnace to steelmaking (see Figure 7) is finite: there are only a certain number of cars available at any given time. Ironmaking is the input to this liquid iron inventory, and steelmaking consumes it. Steelmaking production volumes are driven by caster schedules—wide schedules consume more iron, narrow schedules consume less. Since blast furnace production is difficult to modulate rapidly, caster schedules must be continuously adjusted to control the amount of liquid iron “on wheels.” This helps avoid costly or environmentally irresponsible methods of disposing of excess iron.
For those steel plants that are capable of significant amounts of hot charge rolling, two additional goals help define the quality of integrated casting and rolling schedules: material charge temperature into the reheat furnace, and hot mill asset utilization. Retaining as much heat as possible in the semi-finished product reduces fuel costs per ton, and increases throughput for furnace limited mills. Hot mill utilization improves when rolling campaigns are planned at the maximum length for each campaign type, minimizing the number of required roll changes.
All of these goals exist in a complex tradeoff relationship (see Figure 2).