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Real-Time Machinery Monitoring and Decision Support System for Manufacturing

osedea.com

Manufacturing

Information technology

Operational Challenges in Machinery Monitoring

Machinery misalignment causes quality defects and costly repairs. Operators and performance teams require real-time data visualization and decision support tools to optimize machine responsiveness, maintain quality control, and reduce downtime.

About the Client

Leading tissue manufacturer investing in digital transformation for supply chain optimization

Digital Transformation Goals

Revamp legacy Setpoint Tuning Tool with enhanced real-time data visualization
Enable seamless communication between operators and performance teams
Implement interactive machinery monitoring interface with precision metrics
Develop AI-powered troubleshooting guidance for operators
Establish exception handling system for parameter deviations

Core System Capabilities

Interactive line map for visualizing machine status
Trend analysis graphs with historical run data
Exception status management for parameter deviations
Collaborative comment system for operational justifications
AI-enhanced troubleshooting guide with keyword tagging

Technology Stack

React Native

Node.js

Python

SQL Server

Azure

Computer Vision

System Integrations

Existing backend systems (BCG-developed infrastructure)
IoT sensor networks for real-time data collection
Quality control databases

Performance Requirements

Global scalability for multi-plant deployment
Real-time data processing with <500ms latency
Role-based access control for sensitive data
High-availability architecture (99.99% uptime)

Business Value

Expected outcomes include 30% reduction in downtime, improved product quality consistency, 40% faster operator training through intuitive interface, and $2M+ annual savings from preventive maintenance. The solution enables global scalability across Kruger's manufacturing network with potential for AI-driven predictive maintenance expansion.