Aaria Process Intelligence
AI for root cause analysis and bottleneck detection for manufacturing teams. Connect your existing production systems and surface the insights your engineers need — in hours, not weeks.
Root Cause Analysis
Bottleneck Detection
Quality Intelligence
System Integration
Automatically correlates defects with process parameters, machine states, and material lots.
Live value stream mapping that flags where throughput is constrained — and quantifies the cost.
Unified QA dashboard with SPC, Cpk, and CAPA tracking for operations leaders.
Pre-built connectors. Ready to Use
Core Capabilities
Everything your quality and operations teams need.
Each module is built for real shop-floor workflows — explainable outputs, not black boxes.
Root Casue Analysis
When a defect event occurs, Aaria automatically correlates it against hundreds of process parameters across stations, shifts, and material lots — ranking hypotheses by statistical confidence.
Cross-parameter correlation matrix built in seconds
Ranked hypotheses with supporting evidence trails
Ishikawa diagrams generated automatically
Pareto analysis across defect categories over time
One-click CAPA draft creation from findings
Bottleneck detection
Aaria maps your production flow dynamically using real throughput data. Bottleneck markers shift in real time as conditions change — no manual re-mapping, no guesswork about where OEE is being lost. Cross-parameter correlation matrix built in seconds
Live value stream map with queue depth visibility
Constraint identification ranked by throughput impact
Shift-level and machine-level performance breakdown
WIP accumulation alerts before queues become critical
OEE decomposition: availability, performance, quality
QA Dashboard
A single operations view for quality leaders — combining statistical process control, defect trends, capability indices, and corrective action status, updated in real time.
Live Cpk / Ppk for all monitored characteristics
SPC control charts with automatic out-of-control signals
CAPA lifecycle tracking from creation to closure
Supplier and lot-level quality scorecards
Reports in German and English
Context-aware alerts ranked by severity and business impact. Aaria separates statistical noise from real process drift — so your team only acts on signals that matter.
Severity scoring based on defect type and downstream risk
Role-based routing: operator, shift lead, head of QA
Email, Teams, and Slack integration
Escalation rules with configurable response windows
Alert fatigue prevention via intelligent grouping
Smart Signal Routing
How Process Intelligence works under the hood
01
Data Ingestion & Normalisation
Pre-built connectors pull from your existing data system. Aaria handles timestamping, resampling, schema normalization, as well as data quality check automatically.
Contextual Production Model
All streams unify into a shared time-series production model — linking machine states, quality measurements, material traceability, and operator data.
02
AI Engine
Multivariate correlation, anomaly detection, and causal inference models run continuously. Results are ranked by confidence and are explainable in plain language.
Engineers validate or dismiss hypotheses. Every decision feeds back into the model — improving accuracy and building a plant-specific quality knowledge base.
Feedback & Continuous Learning
03
04
Use Case
Real problems.
Measured outcomes.
See what Aaria finds
in your own data.
Book a 30-minute demo. We'll connect to a sample of your production data and show you real findings — before you commit to anything.