Industry500+ (Mid-market)Vertical: Industry

Production parameter optimization

Automatically adjust machine parameters (temperature, pressure, speed) to maximize yield and quality.

ROI ★★★★★Complexity ●●●●○9-18 months500+ (Mid-market)

The problem

No reliable steering on production parameter optimization.

The current process is manual or inconsistent.

Decisions come too late due to weak signals.

Industrial performance is inconsistent.

Prerequisites: required data & tools

Required data

  • Sensor data
  • paramètres machines
  • qualité produit

Compatible tools

  • MATLAB
  • Python (Bayesian optimization)
  • Sight Machine

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What we implement in 9-18 months

In 9-18 months: Automatically adjust machine parameters (temperature, pressure, speed) to maximize yield and quality. with measured impact on yield increase.

Weeks 1-2

Diagnosis

Weeks 3-6

Build

Week 7+

Delivery

Concrete deliverables

Business framing and decision rules for production parameter optimization

Operational engine for production parameter optimization

Steering dashboard with alerts

Action playbook and governance

Expert insight

Yield gains of 2–8% = major financial impact. Requires domain expertise + data.

— Datasive, expertise terrain

Tech maturity

High

Mature solutions, fast deployment

Medium

Maturing tech, requires customization

Emerging

Cutting-edge innovation, R&D approach

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