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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.

Industry

Life Sciences / Biotech

Scope

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

Timeframe

3 months

Technology

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

3

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

We engineered a retrofit "Computer Vision Watchdog"—an external camera system paired with intelligent control algorithms that autonomously manages antifoam dosing. The solution entailed:

  1. 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.

  2. 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."

  3. Hardware-Agnostic Retrofit

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

Technology used

  • 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
  • Chemical Savings
  • Non-Invasive Safety

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.
Krystian Maskulanis
The transition from manual oversight to computer vision provided bioreactors with autonomous „eyes,” enabling real-time detection and response. This system manages foam with a level of precision and consistency unattainable by human operators, significantly reducing both chemical consumption and overall process risk.
Krystian Maskulanis — Industrial Systems Engineering Lead

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