%0 Journal Article %1 noauthororeditor %A Möhring, H.-C. %A Eschelbacher, Sarah %A Kimmelmann, Martin %D 2018 %J Procedia CIRP %K CFRP Monitoring ifw myown %P 387-390 %T Material failure detection for intelligent process control in CFRP machining %U https://www.sciencedirect.com/science/article/pii/S2212827118311983 %V 77 %X In machining operations like drilling or milling of carbon fiber reinforced composites (CFRP), error influences on the workpiece material affect the productivity and reliability of part manufacturing. Process errors and material failures such as delamination, fiber pull-out and fringes are inacceptable regarding the part quality and safety requirements in many applications. In order to avoid critical damages of the workpiece material, an appropriate tool design incorporating the macro and micro geometry of the cutting edges as well as sophisticated coatings is necessary. In addition, the selection of adjusted process parameters, such as feed velocity and spindle speed, is essential for an optimization of the performance and stability of machining. Due to the abrasive impact of the fibers, severe tool wear occurs during machining which also has an effect on the formation of process errors and material defects. In order to enable reliable machining operations and stable part manufacturing, process monitoring approaches are investigated. The aim of monitoring is to detect critical process conditions as soon as they occur and to initiate appropriate measures for the avoidance of workpiece damages. These measures often entail an interruption of the running process and an exchange of the used tool. A process control, on the other hand, means an adjustment of the process parameters during machining that allows the continuation of the operation with the currently applied tool but without a damage of the workpiece. The fundamental question with respect to process control strategies is, how to adjust the process parameters adequately. Besides information about the actual process conditions which can be gathered from the monitoring signals, a knowledge-base including the interrelations between process parameters, tool wear and process error effects has to be available. In this paper, experimental investigations regarding the dependencies between tool state, process quality criteria and process parameters are presented and discussed. Furthermore, several process monitoring strategies are analyzed and assessed with respect to the implementation of process control strategies. In addition, the concept of an intelligent process control system incorporating the above mentioned dependencies is introduced.

@article{noauthororeditor, abstract = {In machining operations like drilling or milling of carbon fiber reinforced composites (CFRP), error influences on the workpiece material affect the productivity and reliability of part manufacturing. Process errors and material failures such as delamination, fiber pull-out and fringes are inacceptable regarding the part quality and safety requirements in many applications. In order to avoid critical damages of the workpiece material, an appropriate tool design incorporating the macro and micro geometry of the cutting edges as well as sophisticated coatings is necessary. In addition, the selection of adjusted process parameters, such as feed velocity and spindle speed, is essential for an optimization of the performance and stability of machining. Due to the abrasive impact of the fibers, severe tool wear occurs during machining which also has an effect on the formation of process errors and material defects. In order to enable reliable machining operations and stable part manufacturing, process monitoring approaches are investigated. The aim of monitoring is to detect critical process conditions as soon as they occur and to initiate appropriate measures for the avoidance of workpiece damages. These measures often entail an interruption of the running process and an exchange of the used tool. A process control, on the other hand, means an adjustment of the process parameters during machining that allows the continuation of the operation with the currently applied tool but without a damage of the workpiece. The fundamental question with respect to process control strategies is, how to adjust the process parameters adequately. Besides information about the actual process conditions which can be gathered from the monitoring signals, a knowledge-base including the interrelations between process parameters, tool wear and process error effects has to be available. In this paper, experimental investigations regarding the dependencies between tool state, process quality criteria and process parameters are presented and discussed. Furthermore, several process monitoring strategies are analyzed and assessed with respect to the implementation of process control strategies. In addition, the concept of an intelligent process control system incorporating the above mentioned dependencies is introduced.}, added-at = {2018-09-28T08:04:59.000+0200}, author = {Möhring, H.-C. and Eschelbacher, Sarah and Kimmelmann, Martin}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28b45958458ccb5455648f895ee6c731d/eschelbacher}, interhash = {3a76dbc0eacaf219f2ccf7d322188d5d}, intrahash = {8b45958458ccb5455648f895ee6c731d}, journal = {Procedia CIRP}, keywords = {CFRP Monitoring ifw myown}, pages = {387-390}, timestamp = {2018-09-28T06:13:47.000+0200}, title = {Material failure detection for intelligent process control in CFRP machining}, url = {https://www.sciencedirect.com/science/article/pii/S2212827118311983}, volume = 77, year = 2018 }