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The Perspective of Sensor Integration and Automated Decision Making in Roll Forming

机译:传感器集成与自动化决策的视角

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The ongoing trend towards shorter product life cycles, smaller batch sizes and the desire for individual products challenges established manufacturing processes such as roll forming. To meet recent market requirements, process setup and troubleshooting must be accelerated. So far, these activities have been strongly based on the experience of employees. At the same time, both developing and developed countries tend to have a shortage of skilled workers for different reasons. While demographic change is responsible for this development in developed countries, the lack of vocational training is the reason for this challenge in developing countries. To solve this problem, new paths have to be taken to support machine operators to accelerate and safeguard their actions. The integration of sensor systems into manufacturing processes combined with an automatic evaluation of sensor data might help to create operator assistance systems serving this purpose. This paper draws a perspective for sensor integration and automated signal processing in roll forming. For this reason, load sensors are implemented into an industrial roll forming process and disturbances frequently observed in manufacturing processes are intendedly set into the process. Simultaneously, a framework for an automated signal evaluation within an operator assistance system evaluating and analyzing the current process states based on sensor signals and providing recommendations for process improvements is introduced. The results demonstrate that force measurements can contribute to error diagnosis.
机译:更短的产品寿命周期,较小批量尺寸和对个别产品欲望的持续趋势挑战,建立了卷起的制造过程。为了满足最近的市场要求,必须加速流程设置和故障排除。到目前为止,这些活动非常基于员工的经验。与此同时,发展中国家和发达国家都往往出于不同的原因对技术工人缺乏短缺。虽然人口变化负责发达国家的这种发展,但缺乏职业培训是发展中国家挑战的原因。为了解决这个问题,必须采取新的路径来支持机器运营商加速和维护其行为。传感器系统将传感器系统集成到制造过程中与传感器数据的自动评估相结合,可能有助于创建服务辅助系统。本文借鉴了滚动成形中的传感器集成和自动信号处理的视角。因此,将负载传感器实施到工业辊形成过程中,并且在制造过程中经常观察到的扰动将被设定为过程。同时,介绍了一种基于传感器信号评估和分析当前处理状态的操作员辅助系统内的自动信号评估的框架并为过程改进提供推荐。结果表明,力测量可以有助于错误诊断。

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