Fraunhofer Institute for Production Technology IPTResearch Project "CAMWear 2.0"
Tool wear is a cost driver in metal cutting manufacturing. It is often a reason for reduced quality of the product leading to extensive reworking as well as increased component scrap. Therefore, wear measurements are regularly carried out during ongoing production, which, however, extends production times.
Common systems for determining the wear condition of cutting tools are measuring microscopes and laser measuring bridges. However, both have some weak points: Microscopes are located outside the machine tool, are very expensive to purchase and require time-consuming manual operation. Laser measuring bridges can be integrated into the machine, but do not offer the possibility of identifying and measuring different types of wear. It is therefore not possible to determine causes and make recommendations for action. In addition, common wear metrics such as width of flank wear land cannot be derived.
In order to avoid the described wear-related consequences, tools are usually replaced too early rather than too late in practice. In a survey conducted in 2020 with application engineers from a research community of tool and die makers (WBA Aachener Werkzeugbau Akademie), the unused tool life was estimated at around 30 %.
Consistent quantifiability of the wear condition of cutting tools
The goal of the "CAMWear 2.0" project is to develop an AI-based "operator empowerment" system. This decision support system is intended to relieve users by automatically recording and evaluating the wear condition of cutting tools. As a result, the use of tools can be optimized, the economic efficiency of metal-cutting production can be increased, and resource consumption can be reduced.
The planned steps of the "CAMWear 2.0" project at a glance:
- Integration of a microscope protected by a housing into the machine tool.
- Programming of a measuring cycle using the machine axes and the microscope
- Setting up an AI image processing chain to detect and measure wear
- Development of a manufacturing data management system to systematically store the data
The interaction of these components leads to a consistent quantifiability of the wear condition of the cutting tools before and during the milling process. The investigations build on the results of the AiF project "CAMWear", during which a wear rate model was developed to optimize the cutting process, for example by optimizing cutting data and determining the optimum tool change point.
Determination of tool wear already during process planning
Beyond the optimization of tool life, the project team is pursuing an even greater goal in the next step: With the help of systematic processing and storage of the generated wear data including meta information, the scientists would like to determine the expected wear already during process planning in the future and thus optimize cutting data, tool change and tool utilization.
To achieve this goal, the following steps are necessary:
• Implementation of automated model generation on the basis of existing data
• Making the models usable during process planning in a CAM system