ue to numerous influencing factors and partly contradictory optimisation criteria, optimisation tasks for production processes can become increasingly complex in a short time. Hence celano uses a three-stage optimisation model.
This can be universally adapted to a wide variety of optimisation requirements and production situations.
Based on our experience and simulation results (e.g. flow simulation by solving the Navier-Stokes equations), an exact modelling of the process is carried out in advance.
This modelling is used for the parallel calculation of the observer as a basis for the calculation of the current process status.
The prediction then defines possible process states that may happen in the future. These are then used by the optimisation process to determine the setpoints that lead to the desired optimal process. Depending on the requirement, this is done by linear or non-linear algorithms.
Fig.: The three-stage model for optimising the setpoint
values for the furnace temperature (example)
celFCS - sim
The furnace simulator celFCS – sim can be used for different applications: For the downstream analysis of completed heat treatments, already archived process data is used and the annealing process is repeated (“What was going on?”). By specifying theoretical data, the furnace simulator can support the development of new furnaces (“What if?”).
Fig.: The furnace management system celFCS - rhf –
Schematic temperature profile in a reheating furnace
celFCS - tef (tempering furnace) for tempering furnaces, the setpoint values for the furnace chamber temperatures and the set speeds for the individual roller tables are specified cyclically.
The required velocity of the material as well as gaps are calculated prior to the material entering the furnace, whilst at the same time geometrical, thermodynamic and quality-relevant specifications and permissible tolerances are considered.
Disruptions in the production process (e.g. cycling, cold drawing) are compensated directly by speed adjustments. By using the optimisation, the quality of the tempered material can be improved by better adherence of permissible tolerances.
The production capacity is increased by the use of celFCS – tef, for example, by reducing waiting times by a timely change of the furnace chamber target temperatures and the utilisation of the furnace by optimising the specification of material entry times.
celFCS - rhf (reheating furnace) for reheating furnaces calculates both, the temperatures of the material in the furnace (depending on geometries and alloy contents) as well as the furnace chamber temperatures by a multi-dimensional consideration.
Based on this, the setpoint temperatures are determined to achieve the discharging temperature profiles for the furnace. Optimisation minimises energy consumption and scaling alike.
celFCS - bas (batch annealing shop) for bell annealing furnaces is used to pre-calculate a setpoint for a given stack (holding time, duration of the cooling with heating bell, start of the quick-cooling, packing temperature).
This avoids secondary anneals and allows a wider range of coil combinations (different dimensions, different alloys, different target qualities). If a cooling time with a heating bell is specified, the model calculates the resulting cure times and thereby simultaneously reduces the risk of sticking.
Fig.: Temperature Profiling with a data logger of a rotary hearth furnace – Comparison between measured and calculated core temperature
celFCS - cal (continuous annealing line) for continuous belt annealing lines controls the gas quantities or furnace chamber temperatures continuously. Here, not only heating but also cooling (jet cooling) is considered. By specifying the furnace chamber temperatures, defined temperature profiles of the material are achieved. celFCS – cal leads to an improvement of the product quality because it responds quickly to a reduction in speed.
The number of coils to be discounted due to overheating and the variance of temperature variations are minimised. In addition, there is a standardisation of the furnace management.
The increasing flexibility of production, reflected by a rich product mix and small batches, and the increasing demands regarding product quality put a high pressure on the planning and optimisation of production processes. Another challenge are the complex production paths and their correlations.
Fig.: Optimisation example
For this purpose, celano has developed the production planning tool celSSR, which use achieves optimum utilisation of resources and thus increases production output.
The built-in graphical editor makes it easy to capture the set of rules that results from production requirements.
The result of the optimisation, for example, the determined production order, can be displayed both as a spreadsheet or as a Gantt chart.
With celSSR, production orders are optimally distributed to the existing aggregates and production plants. Efficiency can be increased by parallelly using the celFCS furnace control system. Because the furnace can optimise the internal changing processes much more effective, when the material is known in advance.
