Development of a process model for the simulation of adaptive control concepts for metal-cutting bandsawing
Final Report Abstract
Sawing is often the first step in the machining production chain. Especially for larger workpieces, band sawing is used for this. Nevertheless, sawing processes have long had a niche existence in the research landscape. As a result of attempts to optimise manufacturing processes in terms of economic efficiency, band sawing is increasingly becoming the focus of research. Within the framework of this project, two approaches were pursued to achieve this goal. The optimisation goal of both approaches is to increase the service life or the possible cutting area of the band saw blade. The secondary goal was to reduce the lateral run of the saw band and thus the material waste. For this purpose, a simulation model was first built in Matlab/Simulink, which can predict the cutting course and the process forces. In the course of the project, the model was extended to include the various system models of the new constructions and the associated controllers. Since the simulation works on a database of analogy tests, these were built up in the course of the project and artificial intelligence (AI) approaches were developed with which the test effort can be reduced for the future, should new materials or tools become unmaintained. The first design pursues the approach of actively tilting the saw blade guide system to counteract the cutting process. With the other design, the thesis was verified that chip breaking can be positively influenced by an active vibration excitation in the feed direction. For the saw blade tilting, different concepts were designed and compared. Finally, the choice fell on a concept in which it is possible to change the proportion of translatory and rotatory movement on the saw band and thus to investigate different configurations. Single-acting cylinders were used as actuators. The active vibration superposition in the feed direction was first analyzed with analogy tests, whereby a piezo actuator was used due to the easier control behavior and the higher bandwidth. Here, the process forces and the chip formation were considered. Various parameter pairings were determined which appear to have a positive influence. However, when transferring this to real band sawing, it was found that the vibrations introduced are still clearly visible and measurable in idle operation, but are covered by other vibrations in the process and thus no influence could be determined in the parameter window investigated. On the other hand, it could be shown that a significant increase in the lifetime of the saw blades investigated can be achieved with vibration coupling compared to the conventional machining method.
Publications
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Einfluss der Sägebandspannung auf die Stabilität von Sägeprozessen. 6. WGP. Jahreskongress 2016, 05.-06. September 2016, Hamburg
Albrecht, D.
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Influence of Saw Blade Tension on the Stability of Sawing Processes. Advanced Materials Research, 1140, 189-196.
Albrecht, Daniel & Stehle, Thomas
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Measuring the Dynamic Twisting Behaviour of Saw Blades in the Kerf. In: Journal of Machine Engineering, Vol. 16 (2016) 3, S. 75 – 87
Albrecht, D. & Stehle, T.
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Neue Ansätze und Potenziale in der Schneidenpräparation beim Bandsägen – Herausforderungen bei der Optimierung von Sägewerkzeugen. In: Tagungsband. zur Stuttgarter Säge-Tagung, 14. Dezember 2016, Stuttgart
Albrecht, D.
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Potentials for the optimization of sawing processes using the example of bandsawing machines. Procedia Manufacturing, 21(2018), 567-574.
Albrecht, Daniel & Möhring, Hans-Christian
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Adaptronische Regelungskonzepte Bandsägen. 4SMART – Tagung 2022, 09-10.03.2022 Braunschweig.
Tandler, T.; Eisseler, R. & Möhring, H.-C.
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Leistungssteigerung beim Metallbandsägen durch prozessabhängige Regelung der Sägebandspannung. Dissertation. Stuttgart: Universität, 2020
Lund, D.
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A Study of Low-Frequency Vibration-Assisted Bandsawing of Metallic Parts. Journal of Machine Engineering.
Tandler, Tobias; Stehle, Thomas & Möhring, Hans-Christian
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Einsatz von KI bei der Prozessvorhersage für Bandsägen/Use of AI in process prediction for band saws – Artificial intelligence in predicting process forces in band sawing. wt Werkstattstechnik online, 113(01-02), 29-35.
Tandler, Tobias; Hirth, Thomas; Eisseler, Rocco; Stehle, Thomas & Möhring, Hans-Christian
