Overview:
A small metal fabrication company was experiencing frequent unplanned downtime due to machine failures, which severely impacted production timelines and operational costs.
Solution:
The company implemented an AI-based predictive maintenance system, fine-tuned to monitor machine data in real-time. By analyzing patterns and anomalies in equipment performance, the system could predict when machines would likely fail, allowing for proactive maintenance.
Impact:
- Downtime Reduction: The company reduced machine downtime by 40%, leading to increased productivity.
- Cost Savings: Maintenance costs dropped by 15% due to timely interventions.
Case Study-2 Automotive Supplier: AI for Quality Control
Overview:
A Tier 2 automotive supplier used AI to enhance quality control on their production lines. Their goal was to reduce defects in products such as engine components, which were affecting delivery times and customer satisfaction.
Solution:
They fine-tuned a machine learning model to analyze sensor and camera data, identifying product defects in real time. The model was trained using historical defect data and was capable of identifying even subtle flaws that human inspectors could miss.
Impact:
Defect Reduction: The rate of defective products decreased by 20%, improving overall product quality.
Productivity Increase: The automated quality control process sped up production times by 10%, as fewer interruptions occurred for manual inspections.
Case Study-3 . Robotics and AI for Custom Furniture Assembly
Overview:
A medium-sized furniture manufacturing company introduced robotic systems with AI capabilities to improve the efficiency of its custom furniture assembly line.
Solution:
AI was used to fine-tune robotic arms, allowing them to handle various materials and adjust to different assembly processes based on the type of furniture being produced. The system used machine learning models to adapt and learn new configurations over time.
Impact:
- Efficiency Gains: Assembly times were reduced by 25%, allowing the company to handle more orders in less time.
- Custom Order Capacity: The company increased its capacity for custom orders by 40%, leading to higher customer satisfaction.
