Technology & Trends
Using Simulation for the Evaluation of Energy Efficiency Measures in Aluminum Die Casting Plants
Energy efficiency measures in industry are more important than ever due to the energy transition and the global competitive situation. This applies in particular to energy-intensive foundries. Simulation-supported preliminary examinations offer melting and die casting companies the opportunity to assess in advance the effectiveness of possible measures to improve efficiency without influencing production.
In cooperation with the partners pressmetall Gunzenhausen GmbH, ZPF GmbH, Siegelsbach, and the Federal Association of the German Foundry Industry (BDG), a demonstrator for the simulation-based analysis of energy efficiency measures was developed at the University of Ansbach, in which an arbitrarily configurable melting and die casting operation can be visualized. The Competence Center Industrial Energy Efficiency (KIEff) at the University of Ansbach University conducts research in the field of increasing energy efficiency in energy-intensive companies such as the non-ferrous melting and die casting industry. Various projects of the Green Factory Bavaria research association and the Nuremberg Energy Campus (EnCN) are working together with industrial cooperation partners on topics such as simulation, data analysis and automation of melting and die casting operations.
Energy Efficiency in the Foundry Industry
The importance of industrial energy efficiency has increased considerably, especially in Germany. This is due to the progressive transformation of energy systems and increasing competition caused by globalization. Energy-intensive sectors such as the non-ferrous castings industry, in particular, offer great potential for energy and cost savings. According to the Federal Statistical Office, the energy costs can exceed 25 % of the gross value added 1. In the industry, energy consumption per tonne of good cast iron is generally between 2000 and 6000 kWh 2, 3. The melting and holding processes in the furnaces used up to 60 % of the energy and are therefore decisive for operational energy efficiency.
Although the energy losses of a furnace can be reduced by measures such as renewal of the brick lining or improved insulation, corresponding processes are usually associated with high investments and longer-term shutdowns of the plants. Further potential savings, however, can be achieved by optimizing the utilization and operating mode of the melting furnaces and by using the exhaust gas to generate energy.
However, testing of efficiency measures involves far-reaching interventions in the production process and thus endangers planning reliability in the plant.
Simulation-supported preliminary examinations offer melting and die casting companies the opportunity to assess in advance the effectiveness of possible measures to improve efficiency without influencing production. On the basis of the simulation results, a demonstrator was to be developed to show potential savings and improvements of the energy efficiency measures in a company.
Analysis of the Company Structure
In a preliminary examination, the plant structure and processes of the foundries were analyzed. The analysis of the basic structure of different enterprises shows the differences and similarities as well as their effects on the internal material flow. The production process of die casting companies always consists of a combination of continuous (e.g. melting) and discrete (e.g. casting) process steps, which are to be considered in the simulation. The following process steps are relevant for the simulation and are taken into account:
- Delivery of liquid aluminum or block material (ingots)
- Feeding the gas-operated shaft melting furnaces (SO) with ingots, return or scrap material via forklifts
- Heating, melting and overheating or keeping the metal warm
- Distribution of the liquid aluminum to the dosing furnaces of the die casting machines (DGM) by means of DGM forklifts
- Production of castings in die casting machines and quality control
- Transport of full/empty material containers from the die casting foundry or ingot packs from the warehouse to the melting plant
Within the framework of the Green Factory Bavaria project E|Melt, a hybrid simulation model was developed and validated on the basis of real production data, which visualizes the material flow of the entire plant and the energy consumption of the melting furnaces. The software was designed in such a way that any company can be simulated. The operation-specific simulation models are generated via a system configuration which includes the operating structure and the number of producing die casting machines, melting furnaces and forklifts. The basic simulation procedure is shown in Figure 1. The material flow model is used to record the complete material flow within the plant.
The energy flow model records the thermodynamic processes in the aluminum smelting furnaces. Both levels communicate using an interface object that allows the relevant data to be exchanged between the two models. In a control module decoupled from the simulation, orders for the various components are generated based on the plant and process parameters determined and the defined control strategies.
The core element of the simulation is the energy model, which shows the energetic processes in the melting furnace. For validation purposes, the processes were described with complex models, so that the necessary data basis of the models often exceeded the degree of existing data acquisition within the company. A simplified energy model was therefore developed using extensive measurement data, which continues to provide meaningful results on the energy consumption of the plant and reduces the data requirement to three parameters. This eliminates the need for time-consuming metrological tests on the melting furnace. The plant and operating configuration serve as the data basis for the initialization of the simulation. In addition to the number of die casting machines, melting furnaces and transporters, the system configuration also includes the capacities of the individual machines and the travel and loading times of the transporters. The operating configuration includes the control strategies of the forklifts and machines, the production data and the downtimes of the machines.
Validation at Two Different Plants
The validation of the coupled simulation was carried using two real reference plants. For this purpose, the operating data was used across shifts for one calendar week. The material flow model showed a deviation of 1.4 % and 0.9 % in the number of aluminum parts produced and the amount of aluminum consumed, respectively. The results of the energy model were also confirmed on the basis of the recorded data. The molten aluminum mass and gas consumption differ from the actual values by 1.5 % and 0.5 % respectively. Figure 2 shows the course of the aluminum mass in the melting shaft and the flue gas temperature at the shaft outlet over a period of five hours. It has been demonstrated that the simulation can also very well visualize the temporal course of the melting process.
With the help of the simulation developed, efficiency measures in specific companies can be simulatively investigated.
Improved Feeding of the Melting Furnaces
The time optimization of the feeding process, which is possible without additional investment expenditure, aims at increasing the energy efficiency of the melting process. The aim is to ensure a permanently high filling level in the furnace melting shaft in order to achieve optimum heat transfer between flue gas and aluminum. This goal is achieved with an improved feeding strategy. This measure reduces the energy consumption of the melting furnace by about 10 %. A prerequisite for this is precise data acquisition of the melting shaft and furnace trough filling level.
Preheating of the Fed Ingot Packages
The solid aluminum is heated to 300 °C by using the residual heat contained in the furnace exhaust gases. The energy required for heating in the melting furnace is thus significantly reduced in advance, resulting in an increased melting rate. This reduces energy consumption by up to 9 %. In the context of the examination of material preheating, different ingot geometries and stratification strategies were investigated based on flow simulations (see Figure 3). A preheating chamber, which must be integrated into the operational processes, is required for the material preheating.
Improved Feeding of Die Casting Machines
The feeding of die casting machines is currently still carried out in numerous melting and die casting companies on the basis of rigid rules which only rudimentarily take into account the current feeding situation of the die casting machines. Applied strategies are a fixed order of delivery or the signaling of aluminum deficiency by a traffic light display. The recording of the relative filling level of all machines enables a demand-oriented feeding, whereby the duration of the failures caused by aluminum deficiency is significantly reduced or completely avoided. In order to implement this measure, precise level detection of the dosing furnaces on the die casting machines and a clear display of the data for the forklift drivers are required. It was demonstrated simulatively that with the three efficiency measures described the specific energy consumption [kWh/t] of the melting furnaces in the respective plants could be reduced by up to 25 %. This resulted in an increase in OEE (plant efficiency) of up to 3 %.
1) C. Schimansky. Energiepolitik. http://www.bdguss.de/themen/energie/#. WLAU5PJCMQM. Last accessed 17.04.2019.
2) M. Bosse, E. Frost, M. Hazrat, J.-M. Rhiemeier and H. Wolff. Ermittlung von branchenspezifischen Potentialen zum Einsatz von erneuerbaren Energien in besonders energieintensiven Industriesektoren am Beispiel der Gießerei-Industrie. IfG Institut für Gießereitechnik, Ecofys Germany GmbH, Düsseldorf, 2013.
3) C. Herrmann, H. Pries and G. Hartmann. Energie- und ressourceneffiziente Produktion von Aluminium-Druckguss. Springer Vieweg, Berlin, 2013.
This article was first published by GIESSEREI.
This article is protected by copyright. You want to use it for your own purpose? Infos can be found under www.mycontentfactory.de (ID: 46014031)