A robust set of features
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Penalty Matrices
Visualise main effects and interactions with penalty matrices. They map performance deviations to key variables, highlight optimal/avoid regions, and compare with binary interactions for deeper insights.
Generative Reasoning
AI-generated FMEA rationales explain links between causes, failures, and controls. Helps engineers connect process data with structured FMEA knowledge.
Knowledge Capture
Capture lessons learnt in FMEAs and reuse them as organisational knowledge. Ensures improvements and insights are not lost over time.
Time-Based Insights
Convert timestamps into factors such as hour, shift, weekday, or month. Reveal when process risks and deviations occur most often.
Mixed data analysis
Analyse categorical and continuous factors together in one framework, even with missing data. Provides robust correlations across diverse inputs.
Root Cause Analysis
