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Focus on SMEs experiments: Real time monitoring for control and detection of production



Under the AI REDGIO 5.0 project, SCAMM spearheads an experiment focused on real-time monitoring for the control and detection of production nonconformances within a reconfigurable pressing line. The experiment aims to develop a predictive model capable of foreseeing variations in final product quality based on process parameters. 
The experiment aims to harness the power of predictive AI algorithms and real-time monitoring tools to optimize both efficiency and product quality. For SCAMM, the end-user and provider of the technology, several benefits are anticipated. Firstly, as an end-user, SCAMM envisions a significant increase in productivity and a reduction in operating costs. By minimizing waste, reworking, and energy consumption, the experiment strives to enhance SCAMM's manufacturing capacity, thereby positioning it for greater competitiveness in the market. 

Moreover, as a provider of integrated automation solutions, SCAMM anticipates an improvement in its value proposition. Additional services such as monitoring, anomaly detection, process parameter optimization, and predictive maintenance are expected to augment SCAMM's offerings, thereby bolstering its market presence and competitiveness. 



The experiment envisions the creation of self-adaptive production processes enabled by real-time monitoring and predictive AI algorithms. By uncovering nonlinear relationships between process parameters and product quality, the experiment aims to facilitate continuous adaptation of production systems, optimizing both efficiency and product quality in real time. Through these advancements, SCAMM and its partners strive to drive innovation and excellence in manufacturing processes, contributing to the broader objectives of the AI REDGIO 5.0 project. 

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