Manufacturing12 months

Manufacturing IoT & Predictive Maintenance

Client

Global Manufacturing Conglomerate

Overview

A global manufacturer operating 50+ facilities was experiencing frequent equipment failures causing production downtime and maintenance costs. We implemented IoT sensors and ML-based predictive maintenance.

The Challenge

The manufacturer faced operational challenges: • Unplanned equipment downtime cost $2M monthly • Maintenance costs consuming 15% of operating budget • Reactive maintenance approach (fix when broken) • No visibility into equipment health across facilities • Maintenance technicians working reactively • Data silos preventing cross-facility optimization

Our Solution

We deployed comprehensive IoT and AI solution: • Installed 5000+ IoT sensors across 50 facilities • Built real-time data ingestion using MQTT and Apache Kafka • Developed ML models predicting equipment failure 2-4 weeks in advance • Created mobile apps for maintenance teams with failure predictions • Implemented centralized monitoring dashboard • Built optimization algorithms to schedule maintenance efficiently • Integrated with existing ERP systems for spare parts planning

Tech Stack

IoTMQTTApache KafkaPythonTensorFlowReact Native

Key Results

downtime

73% reduction in unplanned downtime

maintenance Costs

45% reduction in maintenance expenses

production Efficiency

38% improvement in OEE

maintenance Accuracy

91% accuracy in failure prediction

cost Savings

$8.5M annually in avoided downtime

Predictive maintenance prevents critical failures before they occur

Unplanned downtime reduced from 5% to 1.3% of operational time

Maintenance costs optimized through predictive scheduling

Cross-facility insights enable best practice sharing

ROI achieved in less than 14 months

Ready to achieve similar results?

Kaycore Technologies - Core Tech Clear Vision