Bioreactor Control: Computer Vision for Non-Invasive Foam Management

Learn how A4BEE used Computer Vision & Python to automate foam management in bioreactors, reducing risk and chemical use.

Solution

Digital CDMO

Industry

Life Sciences / Biotech

Scope

Computer Vision / Python / Closed-Loop Control / Industrial Automation / AI

Timeframe

3 months

Control Modes – (Interval, Vector, PWM) developed for different foam types.

100%

Non-Invasive – No contact with the biological product.

The client

A Global Life Sciences leader focused on optimizing upstream bioprocessing. The client sought to eliminate manual interventions in bioreactor management to reduce contamination risks and improve process consistency across their R&D facilities.

Business needs

Foam formation in bioreactors is a critical process risk that can lead to filter blockage and batch loss. The client needed an automated, non-invasive solution to detect and mitigate foam in real-time, replacing the reliance on manual operator checks and reducing the excessive use of antifoam chemicals which can affect cell growth.

The challenge

01

Subjective Monitoring — Reliance on operators to visually check bioreactors meant slow reaction times and "safety margins" leading to chemical overdose.
02

Hardware Constraints — Traditional internal probes suffer from fouling; the solution required a non-invasive (external) approach.
03

Complex Physics — Foam behavior varies (slow-rising vs. "flash foam"), requiring adaptable control logic rather than simple on/off switching.

Our solution

Computer Vision Detection

Utilized external cameras and Python-based image processing algorithms to detect foam levels and density in real-time without physical contact with the medium.
Adaptive Control Logic

Implemented advanced dosing algorithms (PWM Logic & Vector Control) that adjust pump activity based on foam behavior—delivering precise pulses for slow foam or rapid intervention for "flash foam."
Hardware-Agnostic Retrofit

Designed the system to integrate with existing bioreactors and pumps, acting as a smart "brain" between the sensor and the actuator.

Python (OpenCV)
Computer Vision
PWM Control
IoT Sensors
Custom Control Algorithms

The outcome

The prototype successfully demonstrated that external visual monitoring can effectively close the control loop for foam management. The project resulted in a robust system that fundamentally transformed the client's operational capabilities, ensuring 24/7 autonomous monitoring and non-invasive safety protocols.

Risk Reduction — 24/7 autonomous monitoring eliminates the risk of human error or missed foam events.
Chemical Savings — Adaptive dosing logic ensures the minimal effective volume of antifoam agent, significantly reducing chemical overhead while preserving the biological environment.
Non-Invasive Safety — Zero risk of contamination as the sensor system remains outside the sterile boundary.

What we implemented

3 Control Modes — Interval, Vector, and PWM modes developed specifically for different foam types and behaviors.
Real-time Response — System response time from detection to pump activation reduced to less than X seconds.
100% Non-Invasive — Absolutely no contact with the biological product, maintaining perfect sterility.