- San Jose
- Electronics Manufacturing
- 36 weeks
- B2B
- Python, Django, PostgreSQL, React, AWS
Project Brief
A prominent electronics manufacturer aimed to adopt manufacturing software development by putting in place a platform for smart factories. Their objectives were to automate procedures, link different systems, obtain real-time production data insights, and eventually raise productivity, quality, and efficiency.
Client Background
The company was facing difficulties in a market that was changing quickly. It was well-known for its innovative electrical products and components. A more flexible and data-driven manufacturing method was required due to growing consumer demands, shorter product life cycles, and increasingly complex product lines.
Key Challenges:
Solution:
1. Discovery and Planning
We started by conducting a comprehensive evaluation of the manufacturer's current production setup, which included data flow analysis, bottleneck identification, and department-specific requirements analysis. We worked together with IT personnel, manufacturing engineers, and other relevant parties to establish precise goals for the smart factory platform. A comprehensive plan was created, detailing the data integration techniques, system architecture, and implementation schedule.
2. Development
Using Django and Python, our skilled team of manufacturing software developers created a dependable and expandable backend for the smart factory platform. The frontend development employed React to provide a user-friendly and responsive experience for manufacturing floor workers and management. In order to connect and manage a sizable network of sensors and devices and gather production data in real time, we used AWS IoT Core. Scalability and cost-effectiveness were achieved using serverless computing by utilising AWS Lambda functions. A lot of time-series data was stored and retrieved using DynamoDB.
3. Implementation
To implement the smart factory platform throughout their production lines, we collaborated closely with the manufacturer's IT department. To achieve a consistent data flow, this required connecting the platform with already-in-use systems like ERP and SCM. To make sure managers and employees on the production floor could make the most of the platform's capabilities, we also gave them thorough training.
Tools & Technology Used
Python
Programming Language
AWS
Cloud Services
React
Frontend
PostgreSQL
Containerization
Features:
Real-Time Production Monitoring
Real-time production monitoring is made possible by dashboards and visualisations that show production output, quality parameters, and machine status in real-time.
Predictive Maintenance
Predictive maintenance reduces downtime and allows proactive maintenance by using machine learning algorithms to evaluate sensor data and forecast equipment problems.
Quality Control
By identifying flaws early in the production process, automated quality checks and real-time data analysis lower scrap rates and enhance product quality.
Resource Optimization
Optimizes costs and increases throughput by maximising equipment utilisation and scheduling output based on real-time data.
Traceability
Energy management keeps an eye on and maximises energy use throughout the production, spotting chances for sustainability and energy savings.