|Theme||Factory planning, Industry 4.0|
|Project title||Automated creation of optimized conveyor system layouts for modular conveyor systems (OptiLay)|
|Project duration||01.04.2020 – 31.03.2022|
The transition to Industry 4.0 poses new challenges for many companies. Production cycles are constantly shortening, while product variety is increasing and batch sizes are decreasing. SMEs increasingly have to compete in an international environment and are subject to growing efficiency and cost pressures. As a result, a significantly higher degree of flexibility and adaptability is required in intralogistics. The need for new, innovative concepts in intralogistics is growing in order to be able to react to the changed conditions and remain competitive in the future.
Modular conveyor systems can significantly improve the adaptability and flexibility of intralogistic systems through their changeable design. They consist of function blocks or modules that can be flexibly combined into a network via defined hardware and software interfaces. Due to the individual arrangement and alignment of the modules, the conveyor system can always be adapted to the individual case. In this way, different intralogistic functions such as sequencing, conveying, inward and outward transfer or buffering can be implemented.
Previous projects for the development of a decentrally controlled, modular funding matrix have shown how such intralogistic functions can be realized (FKZ: BMBF 02PJ2685 | netkoPs). Despite potential advantages in terms of flexibility, degree of automation, space utilization and the resulting savings potential, modular conveyor technology is currently hardly used in SMEs. One of the reasons for this is the higher complexity, which makes both the evaluation and the design of modular conveyor system layouts more difficult. In order to reduce these obstacles and to give SMEs better access to modular conveyor technology, the research project aims to develop and provide suitable methods for the evaluation and optimisation of plant layouts.
Publications about the project
The machine learning based method for layout optimization of smallscale modular conveyor systems, which is developed within a research project at IPH – Institut für Integrierte Produktion Hannover gGmbH, provides SMEs a decision support, which enables them to execute complex layout planning independently. In addition, the machine learning method is intended to reduce the cost and time required for planning and to improve the quality of the solution compared to manual layout design.
Small-scale modular conveyors, conveyor systems, machine learning, artificial intelligence