Optimizing Plant-Level Material Handling with Automation

Business Challenge
A manufacturing plant faced inefficiencies in material handling due to manual processes, leading to:
- Ineffective utilization of storage space.
- Increased time and effort required for material movement.
- High material handling costs due to suboptimal resource allocation.
- Frequent errors in material placement and tracking, impacting production efficiency.
Solution Implemented
To overcome these challenges, an automated material handling system was developed and integrated with the plant’s ERP system. The key features of the solution included:
1. Automated Location Identification
- The system automatically identifies available storage locations for material placement.
- Ensures optimal utilization of storage capacity.
2. Intelligent Task Allocation
- Assigns material movement tasks to the nearest available material handling vehicle.
- Reduces idle time and enhances operational efficiency.
3. Guided and Optimized Routing
- Generates the most efficient route for material movement, minimizing effort and time.
- Reduces congestion and improves workflow within the plant.
4. Seamless ERP Integration
- Real-time updates of material movement data in the ERP system.
- Ensures accurate inventory tracking and planning.
Business Impact
The implementation of the automated material handling system led to:
40% Reduction in Material Handling Costs
Optimized resource allocation and minimized unnecessary movements.
95% Reduction in Erroneous Material Handling
Improved accuracy in material placement and tracking.
Enhanced Operational Efficiency:
Faster, streamlined material movement with minimal manual intervention.
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Technology Stack
The cloud-based application was built using:
Backend:
Node.js for efficient server-side processing.
Backend:
Node.js for efficient server-side processing.
Cloud Deployment:
Hosted on AWS for scalability, reliability, and security.
Enhanced Sales Team Efficiency:
Enabled quick access to real-time insights within the CRM, streamlining decision-making.
Conclusion
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