Predictive maintenance for the semiconductors industry

Improve fab uptime, reduce unnecessary maintenance activities, and increase Overall Equipment Effectiveness (OEE) with predictive maintenance designed for semiconductor operations.

Talk to our experts

Predict issues before they impact fab performance

Semiconductor manufacturers are under pressure to maximize equipment availability while reducing maintenance costs and overcoming workforce constraints. Predictive maintenance helps identify potential issues before failures occur, enabling more efficient maintenance strategies that improve uptime and increase Overall Equipment Effectiveness (OEE).

Improve maintenance performance across the fab

Reduce downtime

Identify potential equipment issues before failures impact production and fab performance.

Increase OEE

Improve equipment availability and operational performance while supporting more stable production operations.

Improve maintenance efficiency

Move from reactive and preventive over-maintenance to a more targeted, condition-based approach.

Shift from maintaining more to maintaining smarter

Person viewed from behind working at a computer dashboard beside a server rack on a dark blue background.

Many semiconductor manufacturers perform maintenance based on fixed schedules to protect uptime. However, over-maintenance can increase costs and consume valuable resources without delivering better operational outcomes.

Predictive maintenance enables a more targeted, needs-based approach by helping maintenance teams identify potential issues before failures occur. This allows manufacturers to reduce unplanned downtime, improve maintenance efficiency, and increase Overall Equipment Effectiveness (OEE) while making better use of available resources.

Five steps to successful predictive maintenance

Scope your predictive maintenance strategy

Define business objectives, identify maintenance challenges, assess current capabilities, and establish a roadmap for improving uptime, maintenance efficiency, and OEE.

Design the right approach

Identify critical fab assets, prioritize failure modes, and determine the operational and condition-monitoring data needed to support predictive maintenance.

Deploy with existing data and systems

Leverage available operational data, connect relevant systems, and establish the data foundation needed to support predictive maintenance across semiconductor operations.

Operate and optimize maintenance activities

Use predictive insights to identify potential issues earlier, reduce over-maintenance, avoid unplanned downtime, and support more effective maintenance decisions.

Refine and scale across operations

Continuously improve data quality, measure business impact, increase adoption, and expand predictive maintenance across assets, teams, and sites.

Explore predictive maintenance resources for fabs

Engineering manager and mechanic worker doing routine check up in industrial factory

White paper

Use AI to improve maintenance decisions

Discover how generative AI helps maintenance teams detect issues earlier, access operational knowledge faster, reduce unplanned downtime, and make more informed maintenance decisions across complex industrial environments.

Close-up of a green microchip on a blue circuit board with interconnected electronic pathways.

White paper

Address cybersecurity with confidence

Learn how to securely implement predictive maintenance while protecting sensitive operational data. Explore key cybersecurity considerations, cloud security measures, compliance standards, and best practices.

Gloved hand holding a semiconductor wafer, with a digital wafer graphic on a split dark and light background.

On-demand webinar

Predictive maintenance: less downtime, more efficiency

Unplanned downtime keeps semiconductor fabs on edge. Discover how Siemens experts turn operational data into predictive insights, cutting downtime, and driving overall equipment effectiveness with AI. Watch the webinar now!

Robotic arm holding a wafer on a split background beside a semiconductor manufacturing facility.

On-demand webinar

Turn fab data into actionable maintenance insights

Fabs sit on vast operational data, yet struggle to act on it. See how AI and edge data processing spot equipment degradation early, enabling predictive maintenance. Watch now a live demo of those workflows.

Semiconductor manufacturing equipment beside a blue digital wireframe overlay extending through the production line.

Report

Data maturity and culture: Keys to maintenance success

Discover why so many initiatives stall, even though most fabs have already gathered the data for predictive maintenance. Dive into how data maturity and organizational culture determine success, and how to scale with confidence.

Demo

Senseye: Predictive maintenance in the cloud

Maintenance teams need more than dashboards. Take a guided tour of Senseye Predictive Maintenance and discover how AI turns data into clear, actionable maintenance recommendations.

Person holding a tablet beside a server rack display, with teal data squares on a dark purple background.

Podcast

The champion behind predictive maintenance success

Predictive maintenance often stalls without a clear owner. Hear from Todd Martin why a dedicated Champion is the key to lasting success through building trust, proving measurable impact, and driving adoption.

Dark corrugated metal wall with text: “Steel Intelligence: BlueScope’s Predictive Leap with Senseye.”

Podcast

Inside BlueScope Steel's predictive maintenance journey

Listen now how BlueScope Steel scaled a single pilot into a global rollout through training, cross-site knowledge sharing, and a shift to predictive maintenance that cut downtime.