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Eliminate unplanned downtime in AC motors & rotating assets

We measure electrical waveforms, apply AI-based predictive analytics and personally communicate failure alerts.

Who benefits from SAM4 predictive maintenance?

maintenance

Maintenance professionals

  • Deploy your scarce maintenance resources to assets that actually need help
  • Act faster using real-time fault diagnosis
  • Succeed where previous pilots with predictive maintenance failed

Innovation leaders

  • Pitch truly innovative technology
  • Appeal to popular business trends such as sustainability
  • Implement ROI-positive change
operations

Operations specialists

  • Reach production targets by eliminating unplanned downtime
  • Reduce operating costs by only conducting maintenance when faults are detected
  • Avoid safety issues due to equipment failure
general management

General managers

  • Rely on a high-performing production process that helps the organization meet market demand
  • Accelerate digital transformation through implementation of AI into daily business
  • Execute upon sustainability strategy by reducing industrial electricity consumption

Our stories

See all customer stories

Preventing downtime at industry leaders worldwide

ArcelorMittal

Hear from ArcelorMittal on how SAM4 predictive maintenance enables the detection of developing asset faults from inside the motor control cabinet.

Schiphol Airport

SAM4 detected 100% of developing faults on a baggage handling system over a 12-month period, eliminating unplanned downtime.

Monitor. Detect. Act. Electrical waveform analysis

Install inside MCC

The MCC is a cheap, safe and convenient place for sensor installation, which can be done within 30 minutes per sensor by your own team.

Traditional predictive maintenance requires on-asset sensor installation, which is complicated if the asset is located in a hazardous environment, an ATEX zone or a hard-to-reach place.

Detect over 9 out of 10 failures

SAM4 uses machine learning, motor current signature analysis and voltage measurements to detect more than 90% of developing faults. Traditional vibration-based predictive maintenance can predict roughly 70% of developing faults.

Failure warnings up to 5 months in advance

SAM4 can detect a developing mechanical or electrical fault as soon as it begins, well before it starts to endanger production or safety. That gives maintenance engineers the time they need to fix the fault during a period of scheduled downtime.

maintenance

Increase electrical efficiency

Because SAM4 measures both current and voltage, it can detect developing faults that cause motors to run less efficiently, motors that need to be rightsized for their processes, and processes that are inefficient by design.

Your company can use these insights to reduce energy consumption.

ai technology

Implementation

Proven results in weeks, not years

Installation

30–90 min per asset

SAM4 installs inside the motor control cabinet.

Learning phase

2–6 weeks

Once installed, SAM4 starts to learn the specific patterns of your assets.

Go live!

Forever

After the learning phase, SAM4 monitors your assets 24 / 7 and sends an alarm when it detects potential failures.

The business case for predictive maintenance

This white paper will shed light on the main value drivers for predictive maintenance and provide guidance to help you compute the business case for your own predictive maintenance efforts.

  • White papers
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Nouryon to use digital technology from Semiotic Labs to boost plant reliability

Nouryon has signed a framework agreement to implement self-learning technology developed by Semiotic Labs that helps predict when to maintain and replace pumps and other rotating equipment.

  • Blogs
  • News
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The condition monitoring comparison guide

This guide will compare the most popular forms of condition monitoring, and will help you determine the technology that will make your predictive maintenance most effective.

  • e-books
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