Case Study: Implementing Industry 4.0 Solutions for an Automotive Parts Manufacturer
The Client
A tier-1 automotive parts supplier with 3 production plants in the US.
The Challenge
The client was facing increasing competition and needed to improve operational efficiency, reduce downtime, and enhance product quality while reducing costs. Their Overall Equipment Effectiveness (OEE) was at 65%, below the industry standard of 85%. Unplanned downtime was averaging 12% of production time, and defect rates were at 2.8%, impacting customer satisfaction and profitability.
Solution
Over an 24-month period, we:
- Implemented IoT sensors across 85 critical machines in 3 production lines.
- Developed a predictive maintenance system using machine learning, analyzing data from 50,000 machine-hours.
- Created a digital twin of the manufacturing process for one key product line.
- Introduced collaborative robots for 15% of assembly tasks.
- Established a real-time data analytics dashboard for management, integrating data from 12 different systems.
- Trained 250 shop floor workers and 50 managers on the new technologies and data-driven decision making.
Results
After 36 months:
• Reduced unplanned downtime from 12% to 7% of production time.
• Improved Overall Equipment Effectiveness (OEE) from 65% to 78%.
• Decreased defect rates from 2.8% to 1.6%.
• Achieved 9% reduction in production costs.
• Increased production capacity by 14% without additional capital investment.
• Reduced energy consumption by 11% through optimized processes.
• Improved on-time delivery rate from 92% to 97%.
• Worker safety incidents decreased by 23%.