A large Automotive Tier-1 manufacturer required a machine monitoring solution to improve the reliability of a pneumatic piston controlling PCB entry into a soldering chamber. The objective was to move from reactive to predictive maintenance through continuous monitoring, anomaly detection and early identification of equipment degradation.

The project spanned six months and was delivered by a dedicated ALTEN team of six engineers in India. The engagement focused on developing a predictive analytics platform to analyse sensor data, estimate Remaining Useful Life (RUL) and detect anomalies, integrating it with Manufacturing Execution Systems (MES), and creating a scalable foundation for plant-wide machine monitoring.

The scope included:

• Sensor data acquisition and machine monitoring
• Anomaly detection and predictive analytics
• Remaining Useful Life (RUL) estimation
• Machine learning model development
• Historical data analysis
• Big data platform implementation
• MES and IT/OT integration
• Backend microservices development
• Dashboard and analytics visualization
• System integration and validation

Challenge:

Limited Machine Health Visibility

• Maintenance was largely triggered after degradation or failure had already occurred
• Limited monitoring made early identification of anomalies and degradation trends difficult

Remaining Useful Life Prediction

• Estimating piston life required analysis of large volumes of historical and real-time sensor data
• Rule-based approaches could not capture complex degradation patterns across varying operating conditions

Data and System Integration

• Machine and sensor data had to flow across multiple operational and enterprise systems
• Connecting production assets, analytics platforms and MES required coordinated IT/OT integration

Scalable Analytics Architecture

• Supporting continuous acquisition, processing, analytics and visualization while remaining extensible to additional assets

Actionable Maintenance Insights

•  Operations teams needed meaningful insights at machine and production level rather than raw sensor data

ALTEN Solutions

Sensor Data Acquisition and Monitoring

• Centralised framework for collecting machine and sensor data, enabling continuous monitoring of piston operating parameters and performance trends

Anomaly Detection and RUL Estimation

•  Machine learning models to estimate RUL from historical and operational data, using unsupervised techniques to identify trends and deviations without fixed conditional logic

Big Data and AI/ML Architecture

• End-to-end architecture combining Hadoop-based data management, AI/ML analytics and business application integration, scalable to further monitoring use cases

IT/OT and MES Integration

•  Integration with MES, connecting machine data, predictive analytics and production workflows within a unified environment

Microservices and Visualization

• Backend microservices linking analytics outputs to enterprise systems, with web dashboards for anomaly visualization, machine health and production-level insights

Business Benefits

Early Anomaly Detection

•  Early identification of abnormal machine behaviour helped prevent PCB wastage caused by equipment degradation

Reduced Production Downtime

•  Degrading pistons could be isolated and serviced before failure, reducing production interruptions

Improved Maintenance Planning

•  RUL predictions gave greater visibility into equipment condition, supporting proactive maintenance scheduling

Lower Spare Stock Requirements

• Better understanding of machine health reduced spare-part inventory and improved asset management

Foundation for Plant-Wide Expansion

• Scalable architecture enabled predictive maintenance to be extended to similar assets across the factory

Tools, Technologies & Expertise

Engineering & Development Tools

• Python
• JavaScript (Node.js)
• ReactJS
• HTML
• CSS
• Hadoop
• Impala
• RabbitMQ
• Kerberos
• LDAP

Engineering Capabilities

• Predictive Analytics Development
• Machine Learning Model Development
• RUL Prediction
• Anomaly Detection
• Big Data Processing
• Backend Microservices Development
• Dashboard and Visualization Development
• MES and IT/OT Integration

Domain Expertise

• Smart Factory Solutions
• Automotive Manufacturing
• Predictive Maintenance Systems
• Machine Monitoring Applications
• Industrial Analytics
• Manufacturing Data Integration

Where ALTEN Adds Value

• Predictive maintenance solutions combining machine monitoring, anomaly detection and RUL prediction
• Unified architecture integrating big data, AI/ML and business applications
• Seamless IT/OT and MES integration for operational visibility and decision support

Why ALTEN
ALTEN combines industrial analytics, machine learning and manufacturing system integration to turn machine data into actionable maintenance intelligence that reduces downtime and improves equipment reliability.