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In-process monitoring of inhomogeneous material characteristics based on machine learning for future application in additive manufacturing

Jaquemod Andre, Palalic Marijana, Güzel Kamil, Möhring Hans-Christian

Journal of Machine Engineering

2024

Vol. 24, No. 2

83--93

Additively manufactured components often show insufficient component quality due to the formation of different defects. Defects such as porosity result in material inhomogeneity and structural integrity issues. The integration of in-process monitoring in machining processes facilitates the identification of inhomogeneity characteristics in manufacturing, which is crucial for process adaptation. The incorporation of artificial defects in components has the potential to mimic and study the behaviour of real-world defects in a more controlled way. This study highlights the potential benefits of cutting force and vibration monitoring during machining operations with the goal of providing insights into the machining behaviours and the effects of the artificially introduced defects on the process. Detection of anomalies relies on identifying changes in force profiles or vibration patterns that might indicate the interaction between the tool and the defect. Machine learning algorithms were used to process and interpret the collected data. The algorithms are trained to recognize patterns, anomalies, or deviations from expected behaviours, which can aid in evaluating the effect of detected defects on the machining process and the resultant component quality. The main objective of this study is to contribute to enhancing quality control of machining processes for inhomogeneous materials.

En route to intelligent wood machining – current situation and future perspectives

Möhring H.-Christian, Eschelbacher Sarah, Güzel Kamil, Kimmelmann Martin, Schneider Matthias, Zizelmann Christoph, Häusler Andreas, Menze Christian

Journal of Machine Engineering

2019

Vol. 19, No. 4

5--26

Wood materials are an important part of our daily life. Besides furniture, doors and window elements, parquet floors, veneering, ply wood, chip- and fibreboards, also structural elements for buildings are typical products. Due to the specific properties, variety and complexity of natural wood, wood materials and wood composites, the machining of parts made out of these materials exhibits specific challenges. In order to further improve productivity, quality and efficiency in wood machining, innovative solutions with respect to tool technology, process planning, machinery, process monitoring and intelligent control are necessary. This keynote paper reviews and summarizes scientific developments in wood machining in recent years. Furthermore, exemplary current an ongoing research activities are introduced. Finally, the paper presents and discusses future potentials regarding new approaches for intelligent process control in wood machining.