6DOF Robot Arm Optimization for Harsh Manufacturing Environments

Building on my previous experience at Ford, I grew a passion to learn more about robotics and their application in manufacturing applications. Industrial robots have been the backbone of modern manufacturing for decades, but they face significant challenges in harsh environments like high-pressure cleaning systems. My work at Mercedes-Benz provided valuable insights into developing innovative solutions for improving robot reliability and performance.

Mercedes-Benz: High-Pressure Cleaning System Optimization

At Mercedes-Benz, I worked on optimizing the OP-150 HD high-pressure cleaning system used in engine block manufacturing. The system employed ABB robots to handle engine blocks through a cleaning process using 600-bar water pressure at 60-70°C temperatures.

The Problem

The robots were experiencing frequent failures and reduced operational availability. Through systematic analysis using Six Sigma methodologies, I identified that the robots were being directly exposed to high-pressure water jets, leading to:

• Accelerated wear on mechanical components
• Electrical system failures due to moisture ingress
• Reduced service life and increased maintenance costs
• Production line stoppages affecting overall efficiency

Root Cause Analysis

I conducted a comprehensive analysis of the wear mechanisms affecting the robots:

1. Direct Water Impact: The robots were regularly positioned in the direct path of 600-bar water jets, causing abrasive mechanical wear on arms, motors, and joints.

2. Moisture Ingress: The humid environment combined with water spray led to electrical system failures and corrosion.

3. High Temperature Exposure: Operating temperatures of 60-70°C accelerated material degradation.

4. Chemical Exposure: Neutral cleaning agents, while necessary for the process, contributed to material wear over time.

Solution Development

I designed additional protective coverings for the robots using materials that could withstand the harsh environment while maintaining operational flexibility. This included developing protective solutions for vulnerable cable systems and other critical components to further reduce failure rates. I also designed improvements to the robotic cage system, creating a hybrid approach that kept robots for positioning but isolated them from direct water exposure through physical barriers and improved cell design. This approach maintained the flexibility of robotic positioning while protecting the robots from the harsh cleaning environment.

Key Learnings

This experience taught me several critical lessons about industrial robot optimization:

1. Systematic Approach: Using structured methodologies like Six Sigma helps identify root causes and develop effective solutions.

2. Alternative Solutions: Sometimes the best solution involves rethinking the entire system architecture rather than just improving existing components.

Conclusion

My experience at Mercedes-Benz provided deep insights into robot arms working in harsh environments. I learned extensively about how these systems work and how they can be optimized to withstand harsh environments. The work demonstrated that with proper analysis, innovative design, and systematic implementation, even the most challenging manufacturing environments can be optimized for reliable robotic operation.

This experience, combined with my earlier work at Ford, formed the foundation of my understanding of industrial automation challenges and solutions. The systematic approach to problem-solving and the development of alternative system architectures provided valuable lessons that would inform my later work in robotics and automation.