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AxIoM Gamified AI Assistance System for Support of Manual Assembly Processes In this research project, a novel assistance system for manual assembly stations based on artificial intelligence will be developed. On the one hand, the system monitors the assembly process and verifies the quality of the completed product, and, on the other hand, it considers and individually supports the employee when working at the manual workstation. The system will analyse the sensory information collected at the assembly station using image processing and machine learning methods with regard to the ergonomic and production-related work situation of the employee. This enables the newly developed assistance system to adapt to the individual needs of the employee in order to improve his work situation through specific support as well as motivation and training strategies. Furthermore, by monitoring both progress and assembly components, the system will increase the efficiency and quality of the manual assembly process. Contact persons: C. Petzoldt   (Project manager)T. Beinke Funded by: EFRE: Europäischer Fonds für regionale Entwicklung Duration: 01.06.2019 - 30.11.2020 See project's publications See project's page (http://www.efre-bremen.de) |
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OffshorePlan Complementary application of mathematical and discrete-event models to solve complex planning and control problems in offshore construction logistics Offshore construction logistics pose an exceptionally challenging problem in terms of planning and control. Generally, one can differentiate two approaches: event-discrete simulations as well as mathematical or stochastic optimizations. By themselves, both methods provide their own advantages and disadvantages in terms of computational time, level of detail und optimality. This project aims to investigate new ways for the complementary utilization of both types of methods in the context of offshore construction logistics. Under the basic assumption that despite formal differences, both types of models describe the same elements of the real world system, this project aims to develop a method to convert in between or to generate each kind of model with its own level of aggregation/abstraction based on a more basic description of the real world system. Consequently, the advantage of both types of models can be used complementary within computer aided planning and control methods. Contact persons: M. Lütjen (Project manager)D. Rippel Funded by: DFG Duration: 01.04.2019 - 30.09.2021 See project's publications See project's page |
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IPM Individual Predictive Maintenance Ziel des Projektes ist die Entwicklung einer Toolbox zur Überwachung von Sensordaten für eine individuelle prädiktive Instandhaltung von Dieselmotoren für Schienenfahrzeuge. Motivation: Derzeit werden Instandhaltungsmaßnahmen reaktiv oder in periodischen Intervallen präventiv durchgeführt. Dieses Vorgehen ist jedoch mit hohen Kosten verbunden, da im Schadensfall meist Folgeschäden auftreten. Zudem führen die ausgefallenen Züge nicht nur zu Verspätungen der darin transportierten Personen und Güter, sondern blockieren auch die Bahnstrecke für weitere Transporte und die damit zusammenhängende Logistikkette. Allerdings ergeben sich durch das vorsorgliche Austauschen der Komponenten relativ hohe Instandhaltungskosten, da diese noch für einen längeren Zeitraum hätten genutzt werden können. Methodik: Durch eine Instandhaltung im Bedarfsfall (kurz vor Störereignis) können die Instandhaltungskosten minimiert werden, ohne das Risiko eines Zugausfalls signifikant zu erhöhen. Unter Anwendung künstlicher Intelligenz sollen frühzeitig auszutauschende Motorkomponenten identifiziert und damit eine ressourceneffiziente Instandhaltungsplanung ermöglicht werden. Contact persons: H. Engbers (Project manager)Funded by: BAB Bremer Aufbau-Bank GmbH Duration: 01.02.2019 - 31.07.2020 See project's publications See project's page |
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EILa Examining the influence of „Industry 4.0“ on Factory Layout Planning In the context of ongoing industrial digitization, new technologies are introduced to make production processes more efficient. However, the digital data, which are created and processed by cyber-physical systems, promise improvements as well for adjacent areas, e.g. the restructuring of factories. Thus, the trend towards "Industry 4.0" influences factory planning and requires adapted methods for this task. In this project, the prospects of digitized factory planning are identified and examined, based on a literature study as well as an empirical investigation . The results will provide a methodical guideline for state-of-the-art factory layout planning and identify further research areas for adaptable digital factories. Contact persons: M. Teucke (Project manager)H. Engbers L. Steinbacher Funded by: Bremer Landesprogramm Duration: 20.11.2018 - 31.10.2019 See project's publications See project's page |
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OBELiSK Smart Outdoor Lighting Concept in a Port Environment The aim of the research project "OBELiSK - Intelligent Outdoor Lighting Concept in a Port Environment" is to derive motion patterns or motion prognoses from operational data and DGPS coordinates of the port handling equipment or via smartphones using algorithms and thus enable intelligent lighting of a terminal by dimming LEDs. In addition, it must be possible to illuminate certain areas for special events via a central control system. The consortium estimates that lighting can save around 20% of current energy consumption. Contact persons: M. Trapp (Project manager)L. Steinbacher Funded by: BMVI Duration: 01.09.2018 - 31.08.2021 See project's publications See project's page |
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VirtuOS Multi-Criteria Optimization of Position and Configuration of 3D Sensors through Virtual Reality for Flexible Automation Solutions in Logistics The design of flexible handling robots and autonomous vehicles for logistic processes is a great challenge due to heterogeneous objects, variable environmental conditions and complex properties of the 3D sensor technology. In the VirtuOS project, a freely available online tool is being developed with which application scenarios in virtual space can be freely configured and 3D sensor data realistically simulated. The objective of the project is the development and integration of a multicriteria optimization, which delivers application-specific optimal sensor configurations depending on different optimization criteria. SMEs such as automation companies, system integrators and suppliers of sensors and image processing solutions can thus be supported in the selection and configuration of sensors for new working stations or robots. Contact persons: A. Börold Funded by: AiF Duration: 01.06.2018 - 31.05.2020 See project's publications See project's page |
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ReaLCoE Next Generation 12+MW Rated, Robust, Reliable and Large Offshore Wind Energy Converters for Clean, Low Cost and Competitive Electricity Offshore wind energy is a key technology for generating renewable energies. Due to its complex processes regarding installation, operation and service, and therefore relatively high costs, offshore wind energy converters still cannot compete with today’s energy market prices. To create a competitive offshore WEC with a Levelised Cost of Electricity (LCoE) target of €35/MWh ReaLCoE takes a holistic approach and scrutinises costs in each link of the value chain. As a key element of ReaLCoE, BIBA focusses on the digitisation of future offshore WECs and their adhered value chain. Besides the integration of sensors and the implementation of a condition-based monitoring system, the digital representation of the WECs through a digital twin (“product avatar”) takes a major part in BIBAs contribution to ReaLCoE. Building on this, a concept for predictive maintenance will be developed and realized. Furthermore, BIBA will develop optimised logistic and installation concepts and will conduct various performance simulations for a further reduction of supply chain and installation costs. To validate the concept, a technology platform for a first prototype of a digitised 12+MW turbine as well as a pre-series array of 4-6 WEC will be installed, demonstrated and tested. Contact persons: J. Uhlenkamp A. Ait Alla M. Kreutz S. Oelker A. Sander M. Stietencron Funded by: H2020 Duration: 01.05.2018 - 31.10.2021 See project's publications See project's page (realcoe.eu) |
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RETROFIT Recyclable insulated shipping containers for food Direct selling offers many small and medium-sized companies a good opportunity to deliver high-quality food products directly to the customer by means of refrigerated mailing. Thereby, the use of EPS packaging such as e.g. Styrofoam© has a strong negative impact on the life cycle assessment of the individual products, leaving a lot of waste for the customer. The aim of this feasibility study is the development of an insulated container made of renewable raw materials, which is recyclable and thus represents a new product for the bio-economy. Contact persons: M. Lütjen (Project manager)Funded by: BMBF Duration: 01.04.2018 - 31.03.2020 See project's publications See project's page |
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CooPick Collaborative robot-robot-human interaction for fruit laying Depending on flexibility and capacity requirements, placing fruit on conveyors is either completely manual or fully automated in large plants. Affiliated to the process is a quality control and a final packaging. Against this background, large rationalization potentials for medium flexibility and capacity requirements can be identified by partial automation. The aim of the project is the development of a collaborative fruit lay-up system, which is freely scalable in terms of both employee and robot use and can support automated handling, quality control and packaging. The system should be universally applicable and can be adapted quickly to different types of fruit depending on the season. An essential feature is an intuitive work organization between human and robot. Contact persons: J. Arango Castellanos (Project manager)M. Lütjen A. Rohde Funded by: BMWi Duration: 01.01.2018 - 31.12.2019 See project's publications See project's page |
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InspectionCopter Development of a drone with an attached device for the inspection of wind turbines Rotor blade inspection of wind turbines with hub heights of up to 160 m and blade lengths of up to 88 m is a challenge for service technicians. To support them in the future, the project is developing a drone for automatic inspection of the rotor blade surface. The rotor blade to be inspected is automatically flown off and examined for surface defects by means of optical measuring methods and machine learning. An attachment device also allows the drone to make contact with the rotor blade to test the lightning protection device. Contact persons: D. Denhof (Project manager)B. Staar Funded by: BMWi Duration: 01.01.2018 - 31.12.2019 See project's publications See project's page |
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PiB Predictive and intelligent technical operation to reduce the risk of icing of wind turbines - Data Mining and Data Analytics Structural loads do not only stress wind turbines and rotor blades, they are also affected by extreme environmental influences. Depending on the location of the wind turbine, there is a risk of icing at the leading edge of the rotor blades, in particular at low temperatures and high atmospheric humidity. Within the PiB project, a predictive and intelligent technical operation to reduce the risk of icing of wind turbines will be investigated. Therefore, a new, comprehensive approach based on data mining and data analysis is adopted. In this concept, historical data, meteorological data, and lifecycle data in addition to the current SCADA data is considered. In addition, the innovative system is not limited to one wind turbine or one wind farm. Furthermore, it is planned to enable networking with other wind parks. As result, it is intended to provide a comprehensive picture of the individual risk of icing for each wind turbine. Contact persons: J. Ohlendorf (Project manager)A. Ait Alla M. Kreutz K. Varasteh Funded by: BMWi Duration: 01.12.2017 - 01.11.2020 See project's publications See project's page |
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LoRaLight Development of a highly flexible picking system Picking is a core process of intralogistics tasks and pursues the goal of compiling deliveries according to customer order; the deliveries are thus subsets of the entire product range. The installation of complex and wired infrastructure systems that supports efficient picking procedures is expensive and also poorly adaptable to a changing warehouse infrastructure. An additional problem in the area of ??quality assurance of the picking process is the monitoring of the correct picking processes (picks). This is especially true when picking from non-sorted subjects has to be executed as well as the simultaneous processing of multiple orders, in which an item that has been picked takes place in order-specific containers on a picking trolley. In the project, this gap is to be closed by developing a picking system that can be easily and inexpensively integrated into an existing warehouse infrastructure, maintaining a high degree of flexibility of adaptation and ensuring high quality standards. The maintenance effort should also be significantly lower than with conventional wireless systems. The system to be developed represents a deliberate departure from the development trend of continuous automation of warehouses and picking processes. Contact persons: M. Trapp (Project manager)M. Lütjen A. Rohde Funded by: BMWi Duration: 01.11.2017 - 31.10.2019 See project's publications See project's page |
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KlimAR Augmented Reality-based assistance system for the maintenance of complex heating, air conditioning and cooling technology In the course of the stable development of the German construction industry, the heating, ventilation and air conditioning industry is experiencing steady growth in employment. In addition to a growing shortage of skilled workers, the increasing networking of the working world creates new challenges for technical staff. As a result, all employees involved in a work process have to be provided with all the information in real time that is needed to complete a work task. The aim of the KlimAR assistance system is to support the service technicians in the workflow during the maintenance of complex heating, ventilation and air conditioning systems. Through the use of data glasses, the preparation and provision of technical documentation in the work process, orientation and work support with the help of virtual additional information as well as an adaptation of the used documents by means of interaction with the displayed content will be made possible. This is intended primarily to reduce search efforts in the maintenance process and to support documentation tasks. Contact persons: T. Beinke (Project manager)M. Quandt Funded by: BMWi Duration: 01.10.2017 - 30.09.2019 See project's publications See project's page (http://www.klimar.biba.uni-bremen.de/) |
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F.I.T. Gaerautomat Development of a fully automatic fermenter with automatic determination of the fermentation state In industrial bakery production, a lot of time is spent on determining the optimum fermentation state by baking experts. Achieving the optimal fermentation state purely on the fermentation time and ensuring compliance with the machine-side fermentation and cooling parameters is thus impossible in both branch operation and in industrial operation according to current state of development. The project develops a novel fermentation system (fully automatic proofer) with integrated measuring technology and a special software solution, that detects the current maturity automatically and reproducibly without having to interrupt the fermentation process. The system should be cost-effective, adaptable (large product range) and easy to use. Additionally, the system should be able to specify process leveling. Contact persons: M. Lütjen A. Rohde Funded by: BMWi Duration: 01.10.2017 - 30.09.2019 See project's publications See project's page |
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IRiS Interactive robotic system for unloading of sea containers The unloading of containers is one of the last non-automated activities in a highly-engineered transport chain. A significant proportion of imported and exported containers are emptied or loaded in seaports. Existing automatic and semi-automatic systems do not meet the requirements of port operators due to high investment costs, high commissioning times and adaptations to the infrastructure and have a very low degree of dissemination. The objective of the IRiS project is the development of a new, mobile robot for improving the efficiency of transhipment processes at seaports. The robot should be able to be deployed in a very short time without any major adjustments to the existing operational infrastructure. In order to be able to meet disturbing situations as quickly and effortlessly as possible, an intuitive human-robot interaction interface is developed. Contact persons: T. Beinke (Project manager)N. Hoppe C. Petzoldt L. Rolfs H. Thamer J. Wilhelm Funded by: BMVI Duration: 01.09.2017 - 30.08.2020 See project's publications See project's page (http://www.iris-projekt.de) |
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Isabella Automobile logistics in sea- and inland ports: interactive and simulation-based operation planning, dynamic and context-based control of device- and load movements The project Isabella aims at the development of an interactive planning and control system for adaptive logistics processes on sea and inland ports. After development, the planning and control system will be implemented for pilot testing on the vehicle port of the BLG in Bremerhaven. A simulation-based planning tool will be developed to enable short-term planning adjustments due to occurring change demands and to validate possible planning alternatives. The planning tool is supposed to work on a visual and thus most intuitive basis. A multi-touch table will be used for the visualization of the current planning situation and the definition of planning alternatives. The evaluation of these alternatives is supposed to happen simulation-based. The simulation will evaluate all alternatives based on a multi-criteria target system. A control algorithm will be developed for the management of vehicle movements on the vehicle port. The control system should assign tasks based on the current order situation and the location of the vehicles. By doing so, not only a given order sequence and thus due date reliability can be pursued, but also route optimization and elimination or minimization of empty runs. For the realization of adaptive logistics processes, a tracking and tracing system needs to be designed that generates real time data of the location of the vehicles. A special requirement is the urgent need for a high spatial accuracy that can locate objects within an area of adequate size, preferably on parking lot exactness. Therefore, it will be investigated, if different tracking and tracing methods such as differential-GPS (DGPS) and WLAN-Fingerprinting are adequate for usage in vehicle compound applications. The envisioned planning and control system will be developed in cooperation with the project partners BLG and 28Apps. The project is funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of the program for innovative port technologies (IHATEC). Contact persons: S. Schukraft (Project manager)M. Hoff-Hoffmeyer-Zlotnik N. Jathe M. Lütjen S. Oelker Funded by: BMVI Duration: 01.07.2017 - 30.06.2020 See project's publications See project's page |
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safeguARd Augmented Reality-based assistance system for commercial vehicles to raise the safety level The goal of the safeguARd project is the development of an assistance system for commercial vehicles, which recognizes the occurrence of hazardous situations at an early stage, draws the operator's attention to the dangerous situations and, in the last resort, actively transmits control commands to the machine operator, for example, to initiate an emergency stop. In the context of the project, the safeguARd system is initially developed and evaluated on the example of mobile cranes. This is due to a modular and flexible design so that the transmission of the system to other construction machines as well as other commercial vehicle groups is possible without major adjustments. The project partners apply the "Design for all" concept as part of the development efforts. Thus, the system enables all users to an efficient and safe use of commercial vehicles. Particularly older employees can compensate sensomotoric restrictions and thus the safeguARd system represents an approach to adapt machine operator workplaces to the requirements of the demographic change. Contact persons: M. Quandt (Project manager)T. Beinke B. Staar L. Steinbacher Funded by: BMBF Duration: 01.06.2017 - 31.05.2020 See project's publications See project's page (http://www.safeguard.biba.uni-bremen.de/) |
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ALSO 4.0 Increasing the efficiency of an aluminium furnace by the use of intelligent control modules, extended sensors and innovative solution methodology in the combustion technology The production of molten aluminium is an energy intensive process. To increase energy and material efficiency, machine learning can be used to learn models from sensor data used to control processes. The aim is to develop an adaptive partial control system to determine the optimum process parameters so that the performance can be adapted to melting material. This increases the degree of automation of the entire furnace. Contact persons: A. Decker D. Schweers Funded by: BMWi Duration: 01.06.2017 - 30.11.2019 See project's publications See project's page |
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STRADegy STRADegy – Automated Container handling by Using Straddle Carriers The overall objective of the project STRADegy, which is conducted by EUROGATE and BIBA, is to increase the productivity and flexibility in container handling as well as to reduce the environmental impact and to increase the security of German seaports. Within the project, automated straddle carriers are evaluated in a field test in Europe for the first time. A straddle carrier is a highly flexible freight-carrying vehicle used for stacking and moving standard containers in container terminals. To achieve the research objectives, different concepts are evaluated to ensure a high productivity of the automated system. The developed concepts should also be applicable to a broad range of container terminals. For this purpose, standard interfaces have to be developed to link IT systems from different manufacturers, such as terminal operating systems (TOS), which control the handling processes in terminals. It is also important to ensure that straddle carriers from different providers can be integrated. In this context, BIBA contributes to the design of the pilot experiments and ensures that innovative research approaches are considered throughout all phases of the project. Furthermore, guidelines are prepared that will help to automate mega container terminals in the future. The flagship project STRADegy receives funding from the Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of the program for innovative harbor technologies (IHATEC). Contact persons: S. Oelker (Project manager)S. Eberlein B. Knoke J. Schumacher Funded by: BMVI Duration: 01.03.2017 - 29.02.2020 See project's publications See project's page (http://www.biba.uni-bremen.de/forschung/projekte/laufende-projekte.html) |
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SaSCh Digital Services for Shaping Agile Supply Chains The main objective of SaSCh is a continuous cross-company end-to-end logistic quality monitoring of components and products during their life cycle, especially the supply chains. The project is focusing on selected supply chain processes. Using stationary and mobile sensors or cameras for collection and digitization of quality-relevant environmental data and geolocation. Generated data is stored decentral at each company and provided to relevant partners. Data is exchanged based on the EPCIS standard, being developed further on to realize an exchange of sensor and quality data. Different digital services could use the provided data to improve product and process quality in supply chains. For the automotive industry, new digital services can be implemented to extend the geographical limits of JIT- and JIS-concepts and to prevent special transports, rework, production stops or recalls. Additionally, more transparency enable a better bottleneck management and the entire system will include the developed opportunities. The German Federal Ministry for Economic Affairs and Energy (BMWi) is funding this work as part of the technology programme “PAiCE” (Platforms, Additive Manufacturing, Imaging, Communication, Engineering). Contact persons: M. Teucke (Project manager)A. Börold M. Veigt Funded by: BMWi Duration: 01.11.2016 - 31.10.2019 See project's publications See project's page (http://www.sasch-projekt.de) |
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Geregelt Integrated control for the energy self-sufficient operation of large-scale infrastructure based on environmental data The project Geregelt aims at developing a novel integrated control system for energy and building technology of large-scale infrastructures. By the energetic optimization of the entire energy system under consideration of environmental data and energy storage technology, a significant reduction of total energy consumption can be reached. The linkage and control of internal energy sources, storages and loads can contribute to the smoothing of energy consumption and therefore increase energy self-sufficiency of large-scale infrastructures. Contact persons: A. Rohde (Project manager)J. Arango Castellanos Funded by: BMBF Duration: 01.06.2016 - 31.12.2019 See project's publications See project's page (http://www.geregelt.biba.uni-bremen.de/) |
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AdaptiveSBO An adaptive simulation-based optimisation approach for the scheduling and control of dynamic manufacturing systems **Motivation** The planning and control of production processes has a significant influence on the performance of a job shop manufacturing system. The job shop production is subject to dynamic influences (e.g. faults caused by machine failures or rush orders), which have to be considered for the production planning and control. Common methods are therefore normally divided into modules for calculating plans and modules for operational control. In general, optimisation only takes place at the strategic planning level, while detailed planning is carried out on the basis of simple, static dispatching rules. This allows the generation of schedules in short computation times, but generally no optimal schedules based on the current state of the production system are generated. **Results of the 1st phase** In the first phase of the Brazilian-German cooperation project, a simulation-based optimisation method for controlling dynamic job shop production has been developed. The classical approach of simulation-based optimisation was extended in such a way that the dynamics of job shop manufacturing are taken into account and the optimisation of planning decisions and control rules is always based on the current system state. The developed method was evaluated considering the job shop production of a Brazilian producer of mechanical parts. **Objectives of the 2nd phase** In the second project phase, a method for the integrated control of inventory, production and maintenance processes has to be developed in order to map the current status of a production system in more detail. This means that maintenance orders can be scheduled for the machines in addition to the existing method and the inventory stocks can be taken into account for planning and control. **Approach** Initially, methods for planning maintenance jobs (Germany) and methods for inventory control (Brazil) using up-to-date system data will be developed in parallel. Subsequently, both approaches will be combined to an integrated inventory, production and maintenance control method, which will then be evaluated in a real scenario using data from the industry partner Rudolph Usinados as well as by scenarios from the literature. Contact persons: E. Broda (Project manager)Funded by: DFG Duration: 01.04.2016 - 31.03.2020 See project's publications See project's page (http://www.bragecrim.rwth-aachen.de/#projects) |
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KIPro AI supported platform for the assistance of production control for improving energy efficiency Current energy management systems are only able to capture the energy data and determine key indicators. Methods of artificial intelligence offer the potential to analyze this enhanced knowledge to support the decision-making process for the selection of process parameters for an energy-efficient production. This approach could increase the transparency of the use of energy by giving automated suggestions which allow to lower the primary energy demand.The KIPro research project examines the possibilities of improving energy efficiency in industrial plants with strongly varying properties of the input materials. The aim is to reduce energy demand through the use of methods of artificial intelligence, such as artificial neural networks in combination with deep learning, architectures, semantic mediators and expert systems, without compromising product quality. These systems analyses large amounts of data and identify specific patterns and rules, training and improving their own knowledge base in order to offer specific proposals for an energy-optimized process. Contact persons: A. Decker (Project manager)A. Benggolo K. Burow M. Franke Z. Ghrairi K. Klein H. Thamer Funded by: BMWi Duration: 01.09.2015 - 31.08.2019 See project's publications See project's page (http://www.kipro-projekt.de/) |
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SKILLS Development and demonstration of a rapid and cost-effective installation concept for offshore wind turbines The objective of the project is to develop an innovative and safe installation and logistics concept. Therefore, new transport and lifting concepts for wind turbine components of 6-MW turbines at the North Sea will be developed in order to face conditions of a significant wave height of 2.0 m. The results will be demonstrated on a real offshore site. The research objectives within these project include a significant improvement of the present logistics concepts as well as the development of basics and technologies for the future use of feeder vessel concepts. Contact persons: J. Ohlendorf (Project manager)A. Ait Alla N. Hoppe R. Mortensen Ernits S. Oelker Funded by: BMWi Duration: 01.09.2015 - 31.12.2019 See project's publications See project's page |
