<p> </p><p>The increasing demands for precision and efficiency in machining call for new control strategies for machining systems based on the identification of static and dynamic characteristics under operational conditions. By considering the machining system as a closed-loop system consisting of a machine tool structure and a machining process, the join system characteristics can be analyzed. The capability of a machining system is mainly determined by its static and dynamic stiffness.</p><p>The goal of this thesis is to introduce some concepts and methods regarding the identification of machining system stability. Two methods are discussed, one for the static behaviour analysis of a machine tool, and one for dynamic stability of a machining system. Preliminary results are indicating unambiguous identification of capabilities of machining systems static and dynamic characteristics.</p><p>The static behaviour of a machine tool is evaluated by use of a loaded double ball bar (LDBB) device. The device reproduces the real interaction between the join system, the machine tool elastic structure and the cutting process. This load is not equivalent to real cutting forces, but it does have a similar effect on the structure. This has been investigated both trough simulation and experimental work.</p><p>It is possible to capture the process – ­machine interaction in a machining system by use of the model-based identification approach. The identification approach takes into consideration this interaction and can therefore be used to characterize the machining system under operational conditions. The approach provides realistic prerequisites for in-process machining system testing. The model parameters can be further employed for control and optimization of the cutting process. Using different classification schemes, the model-based identification method is promising for the detection of instability.</p><p>Furthermore, it is the author’s belief that a model-based stability analysis approach is needed to exploit the full potential of a model driven parts manufacturing approach.</p>

The increasing demands for precision and efficiency in machining call for new control strategies for machining systems based on the identification of static and dynamic characteristics under operational conditions. By considering the machining system as a closed-loop system consisting of a machine tool structure and a machining process, the join system characteristics can be analyzed. The capability of a machining system is mainly determined by its static and dynamic stiffness. The goal of this thesis is to introduce some concepts and methods regarding the identification of machining system stability. Two methods are discussed, one for the static behaviour analysis of a machine tool, and one for dynamic stability of a machining system. Preliminary results are indicating unambiguous identification of capabilities of machining systems static and dynamic characteristics. The static behaviour of a machine tool is evaluated by use of a loaded double ball bar (LDBB) device. The device reproduces the real interaction between the join system, the machine tool elastic structure and the cutting process. This load is not equivalent to real cutting forces, but it does have a similar effect on the structure. This has been investigated both trough simulation and experimental work. It is possible to capture the process – ­machine interaction in a machining system by use of the model-based identification approach. The identification approach takes into consideration this interaction and can therefore be used to characterize the machining system under operational conditions. The approach provides realistic prerequisites for in-process machining system testing. The model parameters can be further employed for control and optimization of the cutting process. Using different classification schemes, the model-based identification method is promising for the detection of instability. Furthermore, it is the author’s belief that a model-based stability analysis approach is needed to exploit the full potential of a model driven parts manufacturing approach. / QC 20101103

Purpose: This thesis aims to support the transition from dedicated to a changeable machining system ensuring long-term adaptability. To fulfill this purpose three research questions are developed.  Methodology: Literature studies are conducted to create the theoretical framework for this thesis and answer the research questions. The literature search is structured to focus on selected subjects of machining systems, changeability, fixtures &amp; tools, reconfigurability, and flexibility. A single case study in the tier-1 automotive was conducted to gather empirical data through interviews which are backed up by document studies, and observations along with a theoretical framework. The data gathered is analyzed through a thematic analysis.  Results: The empirical results are presented on a thematic pyramid model consisting of three levels: machining level, production level, and organizational level. The findings are related to the case study.  Analysis: The three research questions are analyzed using a thematic process digging deeper into each pyramid level by comparing the answers from the interviews, document studies, and observations to the theoretical framework. For research question three a conceptual support map is developed using a holistic perspective providing support for the tier 1 automotive industry when transitioning.  Discussion&amp; Conclusion: The industrial contribution of this thesis shows the gap in the changeable thinking approach for tier-1 automotive manufacturers. The presented transition from DMS to CMS is supported through a conceptual map based on the case study findings. The academic contribution includes emphasizing the importance of changeability for long-term planning through the theoretical findings of flexibility and reconfigurability.  Delimitations: This thesis is limited to the challenges found in the case study done in the tier-1 automotive manufacturer. However, a holistic perspective is provided with the conceptual map to provide a starting point for transitioning to CMS, making the map adaptable to other industrial or academic needs.