The operation and configuration of woodworking machines has always been a challenge, especially due to the high proportion of manual production steps. This situation is currently exacerbated by the increase in product variants and more complex logistics chains. AI-based assistance systems and machine learning offer a way out. These approaches make it possible to offer user-specific support, to adapt system configurations automatically and to detect errors at an early stage.
The assistance system platform supports the entire work process at individual production workstations as required. In addition, the platform enables the implementation of flexible production approaches via an intelligent control system, so that the employees can be deployed flexibly according to their skills and the workload. The project aims to pursue the target parameters productivity while taking into account the skills of the employees.
For example, as part of the planning of new assembly tasks, the assistance system indicates which tools and consumables are required on site based on the product, resource and process models. When carrying out the assembly task, the employee receives information on the correct assembly of the units or machines. While inexperienced employees can request step-by-step instructions, experienced employees receive support according to their requirements. On the basis of individual behavior, the AI is used to predict the extent to which the employee needs informational support in a certain assembly step or in a certain situation. In principle, the software works on the principle that users always control the cognitive assistance system. For example, you can request additional information on the current assembly step or generally change the scope of support via your user profile. In addition, the software also supports the communication between design, industrial engineering and assembly, for example to be able to quickly address assembly-related problems. Furthermore, the technical documentation takes place via the assistance system, so that proof of proper assembly can be provided at any time. At the same time, the software should enable the implementation of intelligent and flexible process planning models in order, for example, to avoid waiting times at individual workstations and to be able to deploy employees optimally according to their qualifications.
Duration: November 1, 2020 to December 31, 2024
The project is funded by the Federal Ministry of Defense (BMVg) in the DTEC funding program.
Letzte Änderung: 24. February 2021