Research and Development Projects
Current Research Projects
In RISE4PM new methods for the use of wireless RFID sensor systems in the Industrial Internet of Things are investigated in the subproject "Software systems and test environment for the RFID sensor tag platform".
Digital assistance systems in manufacturing
Conception and implementation of a demonstrator for managing a robot via voice-controlled assistants as well as the preparation of a research project for the use of digital, voice-controlled assistance systems in manufacturing.
The project for system integration of miniaturized components for wireless sensor technology in mechanical engineering is part of the Transfer Center Function Integration for Micro-/Nanoelectronics project
Digitization Pilot for small & medium-sized companies
In the project, the digitisation process is to be actively motivated and promoted, by developing concrete proposals and recommendation courses of action for small & medium-sized companies from a stocktaking in the company.
Construction of a generic data model
Doctoral project with the title "Construction of a generic data model for production machines to uncover optimization potential under consideration of throughput" based on the production technology formula for capacity determination.
KoSeBOT - Context-Sensitive Robotics
With the KoSeBOT project, a demonstrator for interactive human-robot collaboration will be created. This shows how the implementation of cobotics in production plants can be designed, planned and cost-effectively implemented in the future.
The project for system integration of miniaturized components for wireless sensor technology in mechanical engineering is part of the Transfer Center Function Integration for Micro-/Nanoelectronics Project.
A software Framework, that supports the production control of a Smart Factory by means of combined centralized - decentralized planning and enables the secure connection of production capacities, is to be developed.
KoMaA - Complete wheel automatic assembly machine
The aim of the project "KomaA - Complete Wheel Mounting Machine" is to ensure continuously high quality through smart automation of the tire mounting process so that customer satisfaction will increase.
Creative, interesting, playful Sensitization for MINT (Mathematics, Sciences, Informatics and Engineering) in cooperation with Dresden schools, the HTW Dresden is developing new experiments for everyday school life with the Calliope Mini.
Saxony5 Co-Creation Lab "Factory of the Future"
The Co-Creation Lab "Factory of the Future" in the Saxony5 transfer network aims to facilitate networking and knowledge transfer between universities, companies and society on the topics of a smart factory.
Industrial Internet of Things Test Bed
The project has created a central laboratory and research infrastructure that can be used for interdisciplinary research and development of industrial IoT concepts and solutions in teaching and practice.
Starting your own project?
Please feel free to contact us if you are interested and have exciting ideas for joint projects! We would be pleased to help you find more precise ideas and validate your product innovation.
Completed research projects
Camouflage - Contactless tracking at a manual workplace
A general established quality management is the basic prerequisite for ensuring sustainable competitiveness in a manufacturing industry. In times of optimized production, customers require transparency in regard to traceability of individual production steps and used materials and in general the sustainability of manufactured products. Especially for small and medium-sized enterprises (SME), the organizational and technical effort of collecting and processing information presents considerable challenges. High-tech companies, such as the semiconductor and automotive industry rely on direct and automated data acquisition from the machine to the manufacturing execution system (MES). However, SMEs are usually collected data by the operator using a control terminal or paper. The disadvantages of this method are range from partial and complete lack of data, temporal deviations from real processing times to the increase of the risk of data-entry errors by the worker. Order-related and event-driven feedback is often not possible, because the actual production process is thereby interrupted. A consequently and efficient production is impossible.
The prototype camouflage addresses this challenge with an innovative work design according to the vision of the industrial internet. The camouflage workplace was developed in cooperation with the company CamLine Dresden GmbH. With the help of a software for the real-time analysis of three-dimensional depth data and the connection to an MES, the flow of material can be touchless recorded and monitored at the workplace.
- automated monitoring of material collection and accounting in the IT system of the company
- a partially automated classification of the material by placing the workpiece in defined areas of the assembly area
- the system provides support for the worker in questions relating to the set-up and changeover of the workplace. Acknowledges, what materials in which quantities have been used by the operator. It documents the start, the end and if necessary the break of a work process. Upon request, the system provides an assembly instruction or serial, interactive, real-time help for the operator
- application without constantmedia operation and process interruptions
- contactless and distortion-free recordiing of all necessary information for a complete tracking, a direct check of the current process statur as well as the prompt feedback of prodution orders at the workstation
- continous work flow as well as producer and customer transparency regarding the prodution processes
One-third of the global energy is used for the manufacturing of goods. For this very reason, industrial manufacturing is in the focus for efforts to more energy-efficient solutions. The limited available resources and the problems of global warming are challenges which should not be underestimated. Additionally, the increasing energy prices exert pressure on the industrial sector. Today, the energy prices are the second largest cost factor even before labour costs. This is recognized by management worldwide and the majority agreed that the efficiency of all energy sources will be a crucial factor for their company in the next twenty years. Germany attempts to take the leading role here, by encouraging measures to reduce the energy consumption. This strategy is defined within the recommendations for the future project Industry 4.0. Germany is still at the beginning of its efforts. Until now the German industry consumes about 46% of the total energy. Only 10% to 15% of that is used for the actual working steps on the producing machines. Therefore, a great potential still exists.
The goal of the joint project between University of Applied Sciences Dresden and ccc software gmbh is to analyse and pre-process among others energy consumption, process and sensory measured data with the aid of modern methods and to deduce proposals for action for process engineers, people responsible for the plant plus manager of SMEs. Thus, the managing directors are able to act independently, recognize “energy sinner”, to optimize production sequences or for example to shift the main consumption into time intervals with a low energy tariff. Based on historical data, models will be developed, which will support customers with the planning of an energy-efficient manufacturing. For this, the data have to be pre-processed for further processing, by filtering and adding additional data or transforming them into an evaluable form. Based on this information and with different procedures it is possible to improve the production output at equal or smaller expenditure of energy. A modern manufacturing provides a lot of starting points: For example, the decreased rejects and rectification of them might influence the overall consumption of the company positively. Furthermore, savings potential can be attained by optimizing the process parameter and consequently the expenditure of energy. Because the approaches are independent of the concrete use case, they are applicable to different producing companies. The attempt of this research project is to decrease the energy consumption of SMEs, which already use the software of ccc gmbh, by having a low time exposure and resource effort, which normally need optimizing. Thus, this project contributes to the German goal of energy savings.
Sensors for supervising and securing production processes are becoming increasingly important in the field of factory automation. Currently, available solutions on the market are focusing on external supervision of the manufacturing line. As opposed to this approach, intelligent sensors can localize products, assets and collect environmental information from the production process in order to optimize a path through the manufacturing line. To minimize the dimensions of the sensors it is necessary to decrease the power consumption in order to scale down the size of the energy source.
The project focuses on the development of a sensor platform, which can be located wirelessly. The platform is able to acquire measurements of its environment and to efficiently transmit them. The development of methods to decrease the energy consumption on the mobile platform is a central project topic. Competences in sensor platform development, indoor localization and data analysis are being combined to reach this goal.
Distributed Production Planning by using heuristic multi-objective optimization algorithms
A capable industry is vital for every modern economy. This means, that the ongoing increase of challenges must be met, to ensure a top position in the global market. Therefore, every business has to increase their ability to create its goods and services more individual for each customer, with fewer resources and increased reliability. For example, there are solutions to be invented, that are capable of directing production sequences more efficiently. This doctorate program addresses a part of production planning and aims to develop new measures to calculate a production order for discrete processes. In the end, these methods shall enable enterprises to determine an optimal production order, using fast and cost-effective planning procedures. Additionally, there are multiple target criteria to consider, like; processing times, distribution of work, overall tardiness and energy consumption. All these have to be optimized in some kind. But in most cases, these targets stand in conflict with each other, so a trade-up has to be made. Especially if energy-related objectives are concerned, there is an opportunity to make a contribution to an ecological and sustainable production. This project tackles this problem by using heuristic multi-objective optimization algorithms.
Multi-objective parallel methods are used to calculate a valid production plan, which is considering different optimization targets. These methods are used to achieve a higher solution quality than traditional approaches. Additionally, the time to achieve a solution can be shortened by using this technique. The aim is using the existing scientific groundwork and extend it to suit the problem at hand. This includes an emphasis on scientific methods for quality insurance, such as validation and verification and a strong focus on ongoing documentation and publication. Moreover, a constant engagement with new achievements in the field is taking place. Reusable, comprehensible and qualitative results can be assured through these measures. To suit these goals, a metaheuristic in form of a parallel multi-objective evolutionary algorithm will be the result of the doctorate program. It shall be capable of producing better results than the current state of the art in less time. Furthermore, it will be adaptable to different problem cases and the method shall be easy to use, tested and documented. There are plans to make the results available under an open-source license, to make it easy for enterprises to use them. In addition to that, there will be a strict division between the simulation and optimization. That makes it possible to exchange either subsystem. The communication between the computing instances will be designed as efficient as possible to reach a good speedup value. The dependencies of the algorithm will be chosen accordingly to make it usable on many different hardware platforms. To make the results reusable beyond that, there will be publications in form of contributions to international journals and conferences. Furthermore, the findings will be presented early to businesses in Saxony. For example, this can be done by presentations in the meetings of the Silicon Saxony group. It is planned to continue the efforts of the project at the professorship of Prof. Reichelt at the University of Applied Sciences Dresden. That concerns the maintenance and extension of the software and further subsequent research projects in the field.