Resource Efficiency in the Context of the Energy Transition
Demand-Oriented Control of Peripheral Systems in Production
Production and sustainability - a previously believed contradiction is being addressed with the project for demand-oriented control of peripheral systems in production (BeStPeri) and the integration of data-driven methods in production technology. The demand for resources in production technology often cannot be avoided, but rather their efficient use along the value chain can be improved. However, in addition to the often non-existent, but necessary, transparent data situation, this lacks above all the concretely implemented added value from data for personnel, value creation and the environment. Large and, to date, mostly undiscovered potentials for increasing resource efficiency exist above all when entire process chains are considered. However, when leaving the realm of optimizing individual processes, the complexity increases as well as the amount and variety of data to be handled, since causal effects between process steps and their impact on the resulting quality and overall resource consumption have to be considered simultaneously for a large number of process steps. At this point, the use of digital technologies and machine learning will decisively enable future production technology to significantly increase the resource efficiency of the overall system. Accordingly, the current challenge for manufacturing companies is, on the one hand, to systematically digitize their existing machines, including the supply periphery for data collection, and, on the other hand, to integrate digital services to generate a data benefit along the process chain, both from an ecological and economic perspective.
"The goal of BeStPeri is to enable manufacturing companies to reduce their CO2 emissions in a timely manner through the use of data-driven methods by using necessary resources for production more efficiently. The key to this is to supply processes in line with demand. For this, we need transparency along the entire manufacturing chain and must develop digital software services to control the plants."
Frank Benner, Managing Director of B+T Oberflächentechnik GmbH
Participating in the joint project are: An industrial user, data generator and IT expert from the resourceintensive field of electroplating, the B+T Oberflächentechnik GmbH (B+T), a research institution with many years of experience in the field of IoT data - the Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University - and an operational-technical expert for data acquisition and development of control systems, the DiTEC GmbH. Thus, the project serves the active use of data in the user context with a focus on predictive maintenance, process control and resource feedback along the value chain. The joint project BeStPeri provides a holistic approach to the principle of circular economy with a demand-oriented supply of operating resources and control of peripheral equipment with a high transferability from electroplating technology to production technology.Copyright: © B+T Oberflächentechnik GmbH / B+T Unternehmensgruppe
Work content for achieving objectives
In the project, two electroplating lines of B+T serve as a pilot for a consistent data chain for the industry-oriented identification of resource efficiency potentials. In the project, machine learning methods will be used to combine status data along the entire process chain and, based on this, to forecast ecologically and economically valuable key figures. Finally, the models trained for this purpose will be integrated into production as digital services. The industrial application of the services realizes the required combination of availability and analysis of production data. Starting with exploratory data analysis to identify patterns, needs and waste, machine learning models are trained to reliably detect and predict these anomalies and patterns. The actual data benefit for increasing resource efficiency will come from operational feedback of action instructions and optimized control signals for electrolyte routing, as well as rinsing units, transport carts, compressed air supply, and chemical feed.
The success of the project is evaluated by the increase in resource efficiency by means of dynamic resource flow balancing, CO2 footprint and EcoScore.
Concrete recycling and utilization intentions
The completed data collection in production at B+T creates a data chain with over 100 stations. The project significantly advances the company's strategic direction toward the use of digital technologies and machine learning throughout the production chain. With the data-driven analysis and the anchored feedback into the control systems, a first-time benefit of data acquisition is created and thus a significant contribution to the return on investment. At the same time, this benefit serves the overriding reduction of primary resource consumption of material and energy: final metallization effort, new coatings as well as wastewater or waste are significantly reduced. Furthermore, transparency in production increases plant productivity in terms of availability and robustness. With the establishment of digital services, throughput times are also shortened, thus optimizing plant utilization. Furthermore, the wastewater capacities and rinsing bath quality can be actively controlled in advance through the plant-differentiated consumption depending on the order situation. Based on this, the entire resource procurement is linked to production planning. The consistent recirculation of dragged-out chemicals into the electrolytes before mixing with other substances reduces carryover. According to calculations, 4-6 liter of fresh water can be saved per drum alone. Furthermore, indirect costs are saved through the taxation of CO2 emissions. The main customer benefits from data acquisition and processing are above all the high potentials on the product quality and cost efficiency sides. The possibility of rescheduling energy-intensive production processes to times of high availability of renewable energies results in lower-emission and more cost-effective production. The increased transparency and data situation result in simpler controlling and performance management in the area of sustainability, e.g. for the preparation of evidence for ISO:50001. These and other savings potentials must first be precisely determined and validated.
In addition to proactive action measures, the speed of reaction in ongoing production is considerably increased by the availability of statuses and recommendations up to date with the process. Furthermore, the safeguarding of secondary process status variables, the demand-controlled supply of operating resources, the precise localization of faults in production and the targeted use of predictive maintenance will succeed.
The project will enable DiTEC to go deep into production and process control, including the resource-intensive supply of operating resources. The expansion of services, including documentation of emissions and resource consumption per product or per unit of time based on actual consumption data, can be based on the modular ProGAL control systems installed at more than 800 customers. In turn, these customers can be expected to increase their own resource efficiency by using the services
"A comparable development for controlling resource efficiency for electroplating technology is not yet known on the market. The cooperation with a leading research institution in the field of data-driven methods in production engineering enables us to gain an expanded understanding so that our own products, such as the Service Manager, can be further developed in the direction of digital technologies in a future-proof manner."
Dr.-Ing. Siegfried Kahlich, Managing Director of DiTEC GmbH
The project is funded by the Federal Ministry for Economic Affairs and Climate Action.