Procedia CIRP · 2022 · 13 citations · 24 references
EngineeringIndustrial EngineeringManufacturing EngineeringAutomotive ManufacturingManufacturing ProcessesManufacturing SystemsDefect DetectionDigital ManufacturingFactory AutomationIndustrial AutomationManufacturing AutomationManufacturing DefectsAutomotive Manufacturing ProcessesDefect ControlFramesIndustrial Vision SystemsManufacturingRemanufacturingRemanufacturing ProcessesRemanufacturing Systems
Circular economy introduction in industry is globally recognized as one of the most effective green strategies towards sustainability and resources reduction. As the automotive sector has been historically one of the biggest energy consumers, significant efforts are being constantly made to reduce the environmental impact and to increase energy efficiency at the manufacturing stage, both at production and process level. This study focuses on proposing a framework for automotive defective parts identification and remanufacturing in the main production line. In particular, the concept of an automotive microfactory is taken into consideration. To achieve this, a vision-based monitoring system performing the defect identification drives the whole procedure that is considered to be realized through a remanufacturing cell. The software tool is considered to be utilized right before the scheduling process of orders and tasks performed in the remanufacturing cell, taking into account specific performance parameters. The architecture of the software is presented along with some discussion regarding the types of control that can be enforced at both processing and line level, while the use of synthetic data is regarded to test the efficiency of the monitoring system.
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Digital twin driven prognostics and health management for complex equipment
Fei Tao, Meng Zhang, Yushan Liu et al. · CIRP Annals · 2018 · 935 citations