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Intelligent Oil Blend Optimization Platform

Client
Large Scale Oil Refinery
Industry
Energy
Services
Engineering
Case Study Cover

The Challenge

The client had trouble with old methods for making oil blends, which led to a lot of guesswork and wasted time and resources. The quality of their products was often uneven, and managing reports and data was slow and frustrating. They needed a digital solution to simplify the process.

Client Overview

A major oil refinery producing a wide range of fuels, including gasoline, diesel, and aviation fuel. Their traditional blending methods were manual, prone to error, and inefficient, leading to wasted resources and inconsistent product quality.

•Large-scale production of diverse fuels
•Legacy manual blending processes
•Issues with product consistency
•Inefficient lab resource management

Solution Components

Smart Blending Engine

An AI algorithm that suggests optimal mixture ratios to achieve desired fuel specifications while minimizing cost and waste.

Lab Management Web App

A centralized platform for tracking oil samples, managing inventory, and scheduling lab resources.

Predictive Quality Analytics

Forecasting how different blends will perform under testing, allowing for adjustments before physical mixing begins.

Challenges & Risks

1

Operational Inefficiency

Old methods involving guesswork led to time-consuming trial and error in the lab.

2

Quality Consistency

Difficulty in maintaining strict specification standards across batches due to manual variability.

3

Data Silos

Lab data and reporting were often disconnected from production planning, slowing down the feedback loop.

Key Impact

Reduced
mistakes and waste in blending process
Significant
time savings in lab operations
Improved
product quality and consistency
Dependable,
digitized reporting workflow

The Solution

We built a web app that uses AI to simplify oil blending and streamline lab work. The app lets users enter samples, create custom blends, and predict performance. It also manages lab inventory and generates reports. This solution helped the client reduce mistakes, save time, and improve product quality.

Tech Stack

ReactPythonNode.jsPostgreSQLAWS
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