User interface for end users and engineering
Ultimately only the login decides what role you will assume. During project development, many advantages are associated with having a screen available like the one the operator has in live operation. The option of making adjustments later directly at the control station without the need for a specific engineering environment or license accelerates all types of projects.

• Smart client technology—available without elaborate Installation
• Redundancy support (user actions are followed up)
• Dynamic image generation from geospatial information
• Multi-screen support per client station
• Map integration—use of inventory maps
• Intelligent display building (zoom, decluttering, layer, picture in picture)
• Direct link—emergency mode if a service connection is unavailable, direct communication with devices
• ISA 101 HMI Standard
• Playback Manager to reproduce historical conditions (incidents, accidents, etc.)
• Multilingual
• Single Sign-on support
• Active Directory-support
• Floating user license model

Our IEC 61131 SoftSPS solution provides the usual standard along with unmatchable flexibility. Real-time behavior is possible in combination with our Linux real-time operating system.

• IEC 61131 Soft PLC for gateway and controller solutions
• Data buffer mechanism (unlimited)
• Real-time Linux support
• Number of communication protocols > 50
• Deterministic protocol redundancies (PROFIBUS and PROFINET—also for participants without redundancy support!)
• Optimized resource management for maximum project volume
• Diagnosis of web interface
• Standardized PLC open support
• Real-time data acquisition
• Independent of hardware (Siemens, Wago, Beckhoff, Advantech, Kontron, B&R Syslogic, etc.)
• Force/simulation/debugging support
• Uninterrupted online engineering

Homogeneous integration into any IT network is possible with the aXcontroller. The controller variant with Linux and a real-time kernel is an alternative to traditional PLC solutions. Maximum program storage thanks to available system resources provides space for comprehensive PLC projects. The solution for the Windows controller variant is an all-in-one package: SCADA, HMI and PLC. With such characteristics, the aXcontroller is perfect for decentralized (cell-oriented) solutions for industry and infrastructure.

The aXlink100 connects Ethernet and PROFIBUS using Xlink, the real-time Ethernet protocol developed by AutomationX. The aXlink100 has two Ethernet interfaces, an 8P8C (RJ45) or a FIC, and a PROFIBUS DP Master Interface—ideal hardware for your PROFIBUS decentralized periphery.
A number of system and network configurations are possible with these interfaces. With this device, an electric ring can be set up via CAT5 cables or a network redundancy and/or a server redundancy can be set up in a star-shaped network with switches. With the Ethernet interface, up to 16 PROFIBUS Master (aXlink100) can be linked to automationX by up to 124 PROFIBUS-DP Slaves each.

Customer-specific firmware support distinguishes aXconverter from traditional converters. Targeted data preprocessing on the converter allows quick and simple integration of hardware that does not have the required interfaces.
The aXconverter has an internal bus data logger that can be used as a protocol debugger. All serial data traffic can be logged via an Ethernet connection. A firmware module allows quick downloading or replacement of a variety of different software components. All required configurations and addressing employ a rotary switch or a DIP switch.

In the UMBERTO research project, a digital planning and control method based on digital twins is being developed for cross-company optimisation of energy flexibility and thus CO2 emission reduction in material goods production.
The energy transformation to an electricity-based system is the most significant GHG reduction measure, and the conversion of the manufacturing industry, polluter of more than 40% of GHG emissions, must make a major contribution to this. This poses enormous challenges:

a) The increasing volatility in the power grid with the transformation must be countered by increasing energy flexibility in production, by making maximum use of and expanding the degrees of freedom, above all also achieved through cross-company coordination of energy use.

b) Better synchronisation of energy use and energy availability must be achieved in order to minimise GHG emissions in the energy set. Cross-company optimisation of energy use in production is a key to this, also by enabling energy generation and storage facilities to be operated more economically.

UMBERTO therefore aims to develop a planning method for the cross-company optimisation of production and energy use that contributes to grid stability and thus prevents negative effects due to forced shutdowns in energy control, while at the same time maximising the share of renewable energy in material goods production through increased energy flexibility, reducing energy costs and GHG and improving the utilisation options of energy generation and storage for companies. The specific objectives are:

- Reduction of energy consumption peaks as well as avoidance of energy use at unfavourable times (low e-availability from renewable sources) in the range of 15-30%, thereby avoiding coercive measures of energy control, resulting in higher grid security and thus lower grid costs, in turn resulting in location and competitive position security for energy-intensive production companies.

- CO2 reduction in industrial energy use by 5-10% and energy cost reduction in the range of 5-20%, through cross-company synchronised energy use in manufacturing, achieved through avoided energy use at times of poor e-availability as well as better use of local e-generation (e.g. large shared solar plants) and storage options.

The result is a digital planning method based on digital twins of the companies' production and energy systems, as well as cross-company automatically optimising planning of energy use in production between the companies, based on optimisation of networked systems (adapting AI methods such as reinforcement learning), confidentiality-preserving technology, and data rooms. In a unique use case with the three energy-intensive companies at the Judenburg electricity distribution node, their energy supplier and the grid operator, the interdisciplinary research consortium will develop the application-oriented method, evaluate the use-benefit and thus create a direct implementation perspective. UMBERTO will thus make a significant contribution to climate-neutral, energy-saving material goods production and to securing the location of energy-intensive production companies in particular.

The LEOPOLD research project is developing a digital method for making energy systems more flexible through optimized planning and control of complete industrial systems, based on flexible and efficient modelling and optimization.

The socially and politically recognized need to operate industry in a more sustainable and energy-efficient manner is contrasted by the lack of powerful, application-ready digital tools for the optimized design and planning of complex energy and production systems for industry. And although the basic possibility and potential benefits of synchronizing industrial energy demand with the fluctuating energy supply (increasingly, due to the increasing share of renewable energy sources in the supply mix) are recognized, digital tools are also lacking for this purpose, as well as concepts for flexible energy supply for industrial consumers. Thus, ecological and economic optimization potential in a high-tech environment remains unused.

LEOPOLD addresses these potential fields: Complex energy systems in industrial plants are designed (structure) and controlled (process) in an optimized way using a digital method, and are optimally coordinated with the process of the industrial core process (production) and synchronized with the fluctuating energy supply. The method to be developed therefore offers the possibility of modelling and optimizing the industrial systems in variable energetic detail as required: For the overall system, a predominantly discrete simulation is used, for energetically relevant parts of the factory, physical energy consumption behavior is mapped in a hybrid discrete-continuous simulation, and for complex energy systems and their elements (e.g. storage/controllable units), mathematical and data-based modelling (machine learning/AI method application at component level) plus a gradient-based local optimization is carried out. The local energy system optimization is coordinated with the global overall system optimization, which is metaheuristics-based and uses the simulation of the overall system as evaluation function; a hybrid optimization is created. The approach will be developed into an integrated digital method that creates a perspective for feasible practical application. At the same time, a concept for the flexible coordination of energy suppliers and industrial energy consumers for optimized synchronized energy procurement will be developed and integrated into the digital method with the involvement of energy suppliers.

LEOPOLD aims to increase energy efficiency and reduce CO2 emissions by up to 20% in the overall production process and a further reduction of more than 10% at the level of complex energy supply systems. At the same time, the synchronization of energy demand and supply will create a cost advantage for the companies, as well as an efficiency advantage - and thus ecological benefit - for the entire system of energy production and industrial energy consumers.

The project and its method development is accompanied by a comprehensive industrial use case, with two energy-intensive companies in the field of steel products in one value chain, which ensures the practical relevance of the approach from concept to method development to implementation and estimates the potential benefits quantitatively in a demonstrator. The integration of an energy supplier also ensures the direct application perspective of the concept of flexible and synchronized energy procurement or coordination between energy supplier and consumer. The interdisciplinary consortium provides the necessary know-how and preliminary work to successfully implement the ambitious project.

In principle, the vision of meeting 100% of electrical energy demand and even producing a surplus can be realized by using renewable but fluctuating sources (e.g., photovoltaics) to produce energy. Existing urban electrical energy systems may restrict growth due to technical limits such as grid bottlenecks from peaks in production or increases in voltage. Optimized control strategies have been developed that permit proactive responses. Model-based predictive control (MPC) has already proven successful in industrial applications (for example power plant technology). Thanks to the predictive nature of the controller, the optimal response can be found to changes in the future.

Project partners:

In this project, innovative control concepts were developed using model-based, nonlinear methods of control in combination with intelligent sensors. The focus was on implementing control and regulation algorithms for heating, ventilation and air conditioning (HVAC) systems and building loads that are supported by the model and adapted to the physical properties of the building. Intelligent sensors along with real-time data acquisition and processing provide support for secondary model-based control and regulation algorithms, thereby contributing to a general improvement in control accuracy. Through multi-objective tracking of different control targets (optimal energy use, optimal costs, optimal time) and real-time optimization during building operation, the ARIS project significantly optimizes energy consumption and energy savings at a low cost. The ARIS approach focuses on office buildings and public buildings, which have the greatest potential for optimization.

Project partners:

The sector of the economy devoted to manufacturing is responsible for roughly 30% of total energy expenditure in Austria. Along with private households and transportation, it is one of the largest consumers of energy. While the other two sectors have worked for years to develop solutions that increase energy efficiency and energy savings, developments in the manufacturing industry are more recent. As a result of economic and social circumstances, however, more and more companies are striving to plan and operate their production sites sustainably. To date, one obstacle to decisions to make more efficient use of resources in production has been the difficulty in estimating the impact on the entrepreneurial success of the company and the cost of investment in infrastructure. In times of rising energy costs and more conscious consumer decisions, energy efficient production is a key competitive advantage.
Balanced Manufacturing provides a simulation-based method for monitoring, predicting and optimizing the energy and resource requirements of the manufacturing company while taking into account the economic success factors time, cost and quality. AutomationX is responsible for developing the BaMa toolchain.
http://bama.ift.tuwien.ac.at/cube

Project partners:

VUT – Institute for Energy Systems and Thermodynamics (IET)
VUT – Institute for Computer Aided Automation (ASG)
VUT – Institute for interdisciplinary Building Process Management (IBPM)
VUT – Institute for Management Science (IMW)
researchTUb GmbH (rTUb)
Siemens AG Österreich (SIE)
ATP sustain GmbH (ATP)
Daubner Consulting GmbH (DC)
dwh GmbH – Simulation Services & Technical Solutions (DWH)
Wien Energie GmbH (WE)
GW St. Pölten Integrative GmbH (GW)
Berndorf Band GmbH (BB)
Infineon Technologies Austria AG (INF)
Franz Haas Waffel- und Keksanlagen-Industrie GmbH (FHW)
Metall- und Kunststoffwaren Erzeugungsgesellschaft m.b.H. (MKE)
MPREIS Warenvertriebs GmbH (MPR)

The ASPeCT project is developing a method for integrated short-term and long-term production planning that optimizes all essential production resources to include synergy effects and give the company support in decision-making in a complex planning task. Along with the integration of the time horizon for planning, the quality of planning is improved by accepting energy and resource efficiency into the planning target system and facilitating overall optimization of planning with a complex target system. This is achieved with an innovative system that combines short-term and long-term planning based on simulation-supported optimization of multicriteria planning. The method is developed with company partners from different sectors and implemented in the form of demonstrators. The result is a reference setup for an efficient integrated planning system as well as the detailed estimation of the potential impact of the newly developed method when it is used in the company.

Project partners:

DIGIBatch shows how the components knowledge base, functional mockup units (FMU) and a cloud platform can provide small and medium sized companies with a simple and affordable tool for quality assurance and production assurance that preserves core knowledge of the production process. With FMU, physical models from existing simulation environments are combined with empirical knowledge from the knowledge base and with real-time data from the current process. As the digital twin of the core process, the models are then centrally linked to an optimization cycle in a cloud platform at the company level. Recipes can be improved and enhanced by recalibration after each batch and ongoing control parameter adjustment. To increase quality assurance and production assurance, criteria from the process can be monitored automatically and recipes can be developed based on nearly real-time simulation models at all sites without a great need for experimentation.

Project partners:

Renewable and secure energy supply is of great importance for industry, which can only be achieved through the optimal use of all available resources, not least due to the international climate targets. Even in Austria, renewable electricity can only cover part of the energy demand because of a lack of resources. Therefore, the industrial process heat demand in the low and medium temperature range (<400 °C) should be covered by technologies that are efficient in terms of exergy: waste heat utilization, solar process heat and heat pumps in combination with storage tanks, photovoltaics and PVT collectors.

Project Partners: