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Eingeladener Vortrag
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An approach to develop an arc sensor for gap width estimation during automated NG-GMAW with a weaving electrode motion is introduced by combining arc sensor readings with optical measurements of the groove shape to allow precise analyses of the process. The two test specimen welded for this study were designed to feature a variable groove geometry in order to maximize efficiency of the conducted experimental efforts, resulting in 1696 individual weaving cycle records with associated arc sensor measurements, process parameters and groove shape information. Gap width was varied from 18 mm to 25 mm and wire feed rates in the range of 9 m/min to 13 m/min were used in the course of this study. Artificial neural networks were applied as a modelling tool to derive an arc sensor for estimation of gap width suitable for online process control that can adapt to changes in process parameters as well as changes in the weaving motion of the electrode. Wire feed rate, weaving current, sidewall dwell currents and angles were defined as inputs to calculate the gap width. The evaluation of the proposed arc sensor model shows very good estimation capabilities for parameters sufficiently covered during the experiments.
The development within the offshore wind energy sector towards
more powerful turbines combined with increasing water depth
for new wind parks is challenging both, the designer as well as
the manufacturer of support structures. Besides XL-monopiles
the jacket support structure is a reasonable alternative due to the
high rigidity combined with low material consumption. However,
the effort for manufacturing of the hollow section joints reduces
the economic potential of jacket structures significantly. Therefore,
a changeover from an individual towards a serial production
based on automated manufactured tubular joints combined with
standardized pipes has to be achieved. Hence, this paper addresses
the welding process chain of automated manufactured
tubular joints including digitization of the relevant manufacturing parameters such as laser scanning of the weld seam geometry.
Offshore wind energy plays an important role for the desired transition towards a carbon dioxide free industry within the next decades. However, the grounding of the offshore wind plants governs the overall installation process besides bureaucratic bottlenecks.
The application of lightweight principles in steel construction, e.g. the usage dissolved load-bearing structures, so called Jackets foundations, offer great potential in reducing the resource consumption, especially with respect to the needed amount of steel.
In this context this paper focuses on a fully digitalization of the welding manufacturing and as well as testing chain to enable a fully automated manufacturing as well as quality assessment of tubular nodes as key element of Jackets foundation structures. Furthermore, the relationship between the seam shape geometry and resulting fatigue strength is evaluated by numerical methods incorporating bionic principles. It is shown that tubular nodes can be welded fully automatically taking geometry tolerances into account. Moreover, the seam shape could be manufactured as requested by the numerical models which offers great potential for an extended lifetime. Subsequently, the improvements in resource efficiency and reduction of carbon dioxide emissions are evaluated by a life-cycle-assessment.
The digitalization of industrial processes is the most discussed topic in society these days. New business models have been developed to benefit from the opportunities offered by a digitally connected world. However, the focus in on the smart factory consisting of autonomous acting cyber physical systems (CPS). The efficient implementation of such CPS within an industrial environment requires the digitalization of the corresponding production processes. The digital twin of the process under investigation enables to develop sophisticated monitoring and control strategies which are necessary to fulfil the requirements of individual product design.
The need for a digitalization of the welding process is a logical consequence especially with regards to its industrial importance. The theoretical investigations and derived mathematical models of the welding process are well known since many decades. Anyhow, there is still a lack of industrial applicability of such models for an efficient and safe design of welded components. With respect to structural welding simulation that targets the heat effects of welding in terms of global quantities like temperature, solid phase distribution and residual stresses as well as distortions, the limited predictability of these quantities for arbitrary process parameters hinders its usability.
This presentation aims to give an overview of the current state of the art in structural welding simulation to predict the evolution of welding induced temperatures, stresses and distortions. Emphasis is given to industrial applicability of such models by reduction of the calculation times for large real-world structures and improved prediction of optimal process parameters. Furthermore, the role of such models within a weld data management system is demonstrated. The accumulation and relational storage of simulation and measuring data improves the overall process knowledge. This enables virtual cause and effect analyses of new process parameters as basis for a control system design.