Oil, Gas & Heavy ManufacturingEnterprise Knowledge (RAG & Y-Ray Data)VPC / On-Premise

Daily Yield Optimization

Automate the daily retraining of refinery production models using the latest 24-hour yield data to continuously adapt to raw material fluctuations and maximize chemical output.

The Baseline

Problem

Refinery production models degrade quickly if they do not account for micro-changes in daily raw material quality, ambient temperatures, and equipment wear. Relying on static AI models leads to sub-optimal machine setpoints, wasting energy and reducing overall chemical or fuel yield.

Solution

The Data Wheel automates a nightly pipeline that securely ingests the previous 24 hours of refinery yield data, sanitizes it, and fine-tunes the local production optimization model.

Result

Maximizes daily chemical and fuel output by continuously adapting to real-world variables. Process engineers maintain peak operational efficiency with zero manual data engineering required.

Architecture Flow

1

Data Ingestion (End of Shift)

At the end of the daily production cycle, the plant's data historian and SCADA systems securely push the last 24 hours of raw telemetry (temperatures, flow rates, feed compositions) into the AVELIN storage layer.

2

Automated Sanitization (Data Wheel)

The Data Wheel instantly cleans, normalizes, and structures the incoming time-series data and lab assays, automatically filtering out sensor anomalies or maintenance noise.

3

Nightly Fine-Tuning Trigger

The Model Engine allocates local GPU compute to execute an automated fine-tuning job on the refinery's proprietary optimization model, embedding the latest yield correlations directly into the model weights.

4

Zero-Downtime Deployment (Blue-Green)

The newly updated model is benchmarked against baseline efficiency metrics. Once verified, the Model Engine uses Blue-Green Deployments to seamlessly push the updated optimization model to the control room dashboard before the morning shift begins.

Core Infrastructure

ComponentRole
Data WheelManages the automated data lifecycle, moving raw historian data through sanitization and directly into the model retraining pipeline without human intervention.
Model EngineHandles the localized fine-tuning process and executes the Blue-Green deployment to ensure zero downtime for the plant's active optimization dashboards.
Orchestration EngineCoordinates the scheduled workflows, pulling data from legacy industrial control systems and triggering the compute allocation for nightly retraining.

Technical Specifications

Encryption

AES-256 for data at rest; TLS 1.3 for data in transit

Compliance

ISO 50001 (Energy Management), API operational standards, and strict Operational Technology (OT) cybersecurity frameworks

Infrastructure

Deploys natively inside your existing AWS/Azure VPC or entirely on-premise on local plant servers

Build this architecture

Map this workflow to your internal data models. Deploy AVELIN AI to gain sovereign control over your enterprise intelligence.

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