In order to make free-form bending a process of choice for the manufacturing of structural components, a robust strategy for process monitoring is required. Although the technology is particularly suitable for the production of bending components with variable and complex geometry, fluctuations in the process conditions, as well as in the quality of the semi-finished products can results in geometrical deviations from the target geometry. Currently, the quality assessment of the bent components can be done only offline by random sampling, with a considerable time and cost effort. In this contribution, a real-time process monitoring is realised and applied to free-form bending for the first time. First of all, an inline strategy based on single-point tracking for the assessment of the geometry is investigated through an extensive numerical sensitivity analysis. Successively, the method is implemented experimentally and validated with real tests. Finally, a small-batch series of deviating components is produced, and the developed strategy is adopted to perform a real-time process monitoring. The study highlights the potential of an inline measurement strategy for the process monitoring in free-form bending, and its advantages compared to the current offline methods.
The powder bed fusion of metals using a laser beam enables the tool-free fabrication of complex part geometries with merging areas and rapid cross-sectional changes. Together, these geometry features represent a structural transition leading to the formation of shrink lines. These notches on the surface of the part reduce the dimensional accuracy and the fatigue resistance. Shrink lines arise in various materials, with the dimensions of the shrink line depending on the geometric design. The formation mechanisms and influencing parameters of shrink lines have not been investigated yet. This paper demonstrates the extent of influence of the part geometry on the shrink line formation, which was quantified by varying the design of a representative structural transition. In addition, the positions of the specimens on the build platform and the scanning strategy were varied for deriving a cause-effect relationship using process monitoring. The results demonstrated that the shrink line formation was mainly caused by a local overheating at the structural transition and the global cooling behavior. The radius at the structural transition indicated the most significant impact among the investigated geometric parameters. The shrink line dimensions depended significantly on the orientation of the specimens on the build platform and the local scanning strategy applied at the height of the structural transition. The results can be used to reduce shrink lines by re-designing the part and to adjust the manufacturing strategy for structural transitions.
This paper presents an innovative ‘strain acceleration method’ for determining the onset of diffuse necking in sheet forming tests using data obtained from digital image correlation (DIC). The method identifies the onset time of diffuse necking and provides the corresponding in-plane principal strain values by detecting a local extreme in the second derivative of the minor principal in-plane strain with respect to time at the edges of the sheet surface region where diffuse necking occurs. Results obtained from applying the method to tensile testing on two different materials and comparisons with available methods based on force-time or principal strain rate evolutions confirm its accuracy and validity. The new method was implemented in a computer software to be used for research and education that also enables determination of localized necking and fracture and plotting the strain loading paths in principal strain space.
Retrofitting is a sustainable approach to improving the capabilities and extending the life of aging machine tools. Reusing the mechanical construction and replacing only the control electronics and software is a viable option to upgrade an aging machine tool to a cutting-edge level. During the last decades, the evolution of machine tools has focused on developing computer numerical control (CNC) rather than on mechanical construction. Retrofitting the CNC enables Industry 4.0 connectivity and improved usability sustainably, preserving finite raw material resources and reducing carbon emissions created during the casting process of heavy blank parts for physically large machine tools.
This publication presents methods to retrofit machine tools using open-source CNC software and a feasibility study after seven years of operation. Our study highlights retrofitting as more profitable than repairing an aging CNC and compares the sustainability of retrofitting or replacing the aging machine tool with a new unit. In conclusion, retrofitting enables sustainability, connectivity, and accuracy comparable to modern machine tools. Retrofitting also paves the way for using artificial intelligence to monitor and adapt to tool wear, chatter, and surface roughness.
This study investigates a complex hybrid flow shop scheduling problem prevalent in the industrial sector, characterized by dedicated machines, availability dates, and delivery times. The primary objective is to minimize the total completion time (makespan) in a two-stage workshop setting. We conducted a comprehensive literature review, revealing a scarcity of research on this specific configuration, and employed the Simulated Annealing metaheuristic as our main resolution method. Special emphasis was placed on the meticulous parameterization and configuration of this metaheuristic, crucial for navigating the complexity of the problem.
Our findings demonstrate the remarkable effectiveness of the Simulated Annealing method, particularly in achieving low deviation from the lower bound in larger problem sizes and specific instance classes. This consistency highlights the method’s robustness and suitability for complex scheduling scenarios. The study also reveals varying degrees of problem solvability across different instance classes, with computation times generally reasonable except in more challenging scenarios.