No abstract
In the manufacturing industry, spray painting is often an important part of the manufacturing process. Especially in the automotive industry, the perceived quality of the final product is closely linked to the exactness and smoothness of the painting process. For complex products or low batch size production, manual spray painting is often used. But in large scale production with a high degree of automation, the painting is usually performed by industrial robots. There is a need to improve and simplify the generation of robot trajectories used in industrial paint booths. A novel method for spray paint optimization is presented, which can be used to smooth out a generated initial trajectory and minimize paint thickness deviations from a target thickness. The smoothed out trajectory is found by solving, using an interior point solver, a continuous non-linear optimization problem. A two-dimensional reference function of the applied paint thickness is selected by fitting a spline function to experimental data. This applicator footprint profile is then projected to the geometry and used as a paint deposition model. After generating an initial trajectory, the position and duration of each trajectory segment are used as optimization variables. The primary goal of the optimization is to obtain a paint applicator trajectory, which would closely match a target paint thickness when executed. The algorithm has been shown to produce satisfactory results on both a simple 2-dimensional test example, and a non-trivial industrial case of
The increasing diversity of products and variants requires a flexible and fast path generation in robot-based painting processes. In the state of the art, path generation in the painting industry is a time consuming and cost-intensive iteration process in which the generated paths are evaluated and optimized via painting trials. In this paper, we present a novel concept for a self-programming painting cell, which is based on the key technologies 3D-scanning, multi-physics painting simulations, and a contactless film thickness measurement using terahertz technology. The core element of this cyber-physical painting system is a unique combination of numerical painting simulations with a gradientbased multi-objective optimization method, to virtually compute painting paths that produce a homogeneous thickness on the painted object. In order to drastically reduce the time and computationally intensive numerical fluid dynamic simulations, a step-by-step coupling of an offline and online simulation was implemented. In a final step, a collision free robot motion without singularities is generated automatically from the computed painting path. The concept was validated under pilot plant conditions by the painting of a fender using an electrostatically assisted high-speed rotary bell atomizer. The paint film thickness, measured with terahertz technology was used as the target and validation criterion, as it shows a strong correlation to other quality values. The results show that the achieved film thickness was within the process specification, although deviations between simulated and measured film thicknesses were found in the edge zones of the workpiece.
Heat transfer modeling of large industrial ovens such as those used in automotive paintshops is difficult due to the large and multiple scales, and long curing times. The flow inside a convective oven is turbulent and the process includes large temperature gradients. An efficient simulation requires a simplified and localized model of the heat transfer coupling. We present a novel method with three ingredients: localization using local Nusselt numbers of the oven nozzles, projection of Nusselt number profiles onto the target, and efficient conduction modeling on a coarse background mesh. The approach, which was developed in a research project together with the Swedish automotive industry, makes it possible to accurately simulate a curing oven with close to real time performance. The simulation results are demonstrated to be in close agreement with measurements from automotive production.
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