CLEVER: Data Analysis Module

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These developments are designed to add advanced industrial-data-analysis capabilities that support the implementation of Lean Six Sigma strategies on the factory floor. The solution manages analytical tasks on time series previously captured in production environments, enabling operational information to be used to improve processes, reduce variability and anticipate incidents.
Analyses can include predictive models, anomaly detection, deviation identification and assessment of critical-variable behaviour. Its approach transforms industrial data into actionable knowledge to optimise quality, efficiency and continuous improvement.

Industrial analytics for continuous improvement
The main application is to provide an analytical layer over factory-floor time-series data that supports the deployment of Lean Six Sigma methods in industrial environments. The platform configures, manages and executes analytical tasks on variables collected from production processes, identifying relevant patterns, anomalies and trends. This supports monitoring of process stability, early detection of deviations and initiatives to reduce defects, optimise cycle times and improve operational efficiency.

Less variability and more precise decisions
The main benefit is enabling continuous improvement based on real factory-floor data. By applying predictive analytics and anomaly detection to industrial time series, the solution helps anticipate problems, reduce variability and prioritise corrective action. This improves process quality, reduces downtime and deviations, and supports operational decisions with quantifiable evidence. It also helps already digitalised industrial environments evolve towards more intelligent, preventive and efficient models.

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