“Ansys simulation made it possible to identify the central cost drivers in relation to the return on investment (ROI) of a robotic welding system for additive manufacturing. This opens the way for future research. In addition, the evaluation of the economic analysis could be carried out in a time- and cost- optimized way. A qualitatively equivalent manual evaluation without the support of Ansys simulation would not have been possible. With Ansys simulation, a static one-dimensional calculation model became a dynamic multidimensional model.”
— Korbinian Mühlhauser
Welding Engineer, Linde Engineering
Linde Engineering (Linde) has been developing and optimizing gas processing, separation, and liquefication technologies for 140 years. With material costs rising over time, Linde is exploring alternative development and production methods to work more efficiently. This has led to a recent economic analysis of an additive arc manufacturing process for aluminum components in plant and pressure vessel construction. Linde implemented Ansys simulation into their economic analysis to optimize data analyses, automate parameter identification, and visualize results. By integrating Ansys simulation, Linde was able to explore potential issues in a much more dynamic and multidimensional way.
While preparing the economic analysis in a spreadsheet, the Linde team realized that a static calculation could only include a very specific combination of parameters. The group needed a program that would allow team members to vary parameters automatically. By incorporating optiSLang into the analysis project, Linde was able to achieve this. Additionally, the software offered user-friendly interfaces and provided numerous possibilities for evaluating data?
First, Linde prepared a detailed economic analysis in a spreadsheet program, which contained 36 parameters of mostly variable inputs for costs (e.g., electricity, material, and labor), times (e.g., tool setup and weld path planning), and technology (e.g., melting rate and shielding gas flow). In addition, Linde wanted to observe the differences across one-, two-, and three-shift operational systems. With so many combinations and variables to explore, manually changing parameters was not practical. For this reason, Linde integrated the spreadsheet file into optiSLang to carry out a more in-depth sensitivity study and evaluate the results for both time and cost.
By illustrating their findings through advanced 3D visualizations, Linde was able to see correlations and discrepancies that are not apparent in a spreadsheet analysis. With the Ansys-powered sensitivity study, Linde identified the most important factors influencing the return on investment (ROI) of a potential robotic welding system for additive manufacturing.
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