AI-Based Workflow Optimization for Electroplating
Summary:
Cours GmbH uses AI-driven planning to reduce overplating and resource waste in electroplating, saving materials, chemicals, energy, and €180,000/year.
Main description:
Cours GmbH & Co. KG, a family-owned SME founded in 1934 and located in Velbert, specializes in the electroplating of zinc die-cast, brass, and steel components. With 51 employees and an annual output of over 16 million parts, the company serves clients in sectors such as medical technology, automotive, and furniture manufacturing.
Until recently, production scheduling relied mainly on delivery deadlines, neglecting essential process parameters like coating thickness, part geometry, surface area per carrier, and base material type. This led to excessive resource use, frequent overplating, and increased complaints and rework.
In response, Cours developed and implemented a pioneering AI-based production planning system—the first of its kind in the electroplating industry. The AI integrates with a centralized ERP system and dynamically controls production using real-time data across the entire value chain. The solution enables precise workload distribution across all major process steps—pretreatment, coating, rinsing, drying—as well as secondary operations like demetallization.
Key elements of the implementation include:
- A centralized AI-driven planning module linked to ERP
- A smart charging system for optimized part handling
- Mobile Industrial Robots (MIRs)
- Custom-built “Cours Carts” for automated material flow
The entire workflow—from order intake to finished goods—is controlled via AI, ensuring consistency, transparency, and minimal resource use without compromising quality.
Resources needed:
Technical:
ERP-based AI software, smart robotics (MIR), automated charging and storage systems, custom transport solutions
Financial:
- Total investment: approx. €1.475 million
- Public funding: €412,000 from the NRW “Circular Economy and Resource Efficiency” program
Organizational/Human:
Staff training on AI systems, restructuring of production and logistics workflows, cooperation with automation and IT partners
Environmental benefits:
Material savings per year:
- Zinc, Brass, Steel: 3 tons/year
- Copper, Nickel: 500 kg/year
- Process chemicals: 600 kg/year
Reduction in CO₂ equivalents:
- 23.8 tons CO₂/year
Environmental benefits:
- Cost savings: Approximately €180,000 annually due to reduced raw material and chemical use, lower scrap rates, and fewer complaints/reworks
- Improved production efficiency and quality assurance
- Increased competitiveness through innovation and digital leadership
