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Use Cases

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Prevent unplanned downtime

In most industries, between 7% and 15% of rotating assets fail each year, resulting in costs associated with production loss, quality issues and contractual obligations. 
SAM4 monitors equipment 24/7 and detects upcoming failures up to months in advance. You'll receive an alert when failures are detected, allowing you to schedule maintenance before breakdowns occur.

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Prioritise Maintenance Tasks

Generic, time-based maintenance schedules introduce inefficiencies. In most industries and locations, between 20% and 40% of maintenance technicians retiring in the next 5 years. You will need to improve efficiency and productivity to keep up with the demands of the business.
SAM4 allows you to prioritise maintenance tasks and introduce a Condition-Based Maintenance regime based on data-driven insights into the health and performance of your assets.

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Reduce Energy Waste

Rotating assets consume 28% of the global electricity production. Unfortunately, a sizeable portion of that energy is wasted on inefficient drivetrains, improper use, and process-related issues. 
SAM4 monitors energy consumption metrics and provides insights that allow you to optimize energy efficiency, lower energy costs, and eliminate energy waste. 

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Improve Overall Equipment Efficiency

Time-based maintenance introduces excessive planned downtime. Inspections and premature repairs or replacements have a negative effect on the Overall Equipment Efficiency.
SAM4 allows you to introduce a Condition-Based Maintenance approach, which mandates that maintenance is performed before failures happen or when performance decreases - but not before, eliminating unnecessary planned downtime in the process. 

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Offer "Power by the Hour" contracts

Assets are increasingly offered based on Power by the Hour-models. This creates both an upside for OEM's but also introduces shared risks associated with unplanned downtime.
SAM4 is used by OEM's to remotely monitor assets, providing an efficient way to both lower maintenance costs and improve uptime at scale - leading to higher customer satisfaction levels and improved financial performance. 

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Hardware

SAM4's hardware consists of sensors, a datalogger, switches and a gateway. It as a fully integrated solution that is easy to install, requires no maintenance and reliably generates data from inside the Motor Control Cabinet. 

SAM4's hardware consists of sensors, a datalogger, switches and a gateway. It as a fully integrated solution that is easy to install, requires no maintenance and reliable generates data from inside the Motor Control Cabinet. 

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Devices

sensors

Sensors measure current and voltage from inside the Motor Control Cabinet. Several options are available for both Current and Voltage.

 

daq

The Data Acquisition device (DAQ) turns the analog sensor signal into a digital one. Up to 10 DAQ's are supported by a single Gateway. 

gateway

Gateway

The gateway stores data, performs local processing tasks and sends data to the SAM4 platform.

power unit

Switches, cabling and power unit

The components are connected via switches, ethernet cables and powered by a 24v or 48v power unit. 

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Intelligence

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Intelligence

SAM4 monitors assets at scale, by automating analysis based on concepts borrowed from Motor Current Signature Analysis. Collectively, the algorithms allow SAM4 to process large amounts of data and provide accurate analysis across a wide variety of motors, assets and circumstances without editing a single line of code. 

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Classification

Classification algorithms detect patterns in data that are associated with specific failure mechanisms. The principle is straightforward: The patterns that emerge when a pump is cavitating are markedly different from the patterns associated with - for instance - a soft foot. And a soft foot will show a different pattern from a clogged pump. We call these patterns "fingerprints of failure".

Execution is not straightforward: A host of variables influence the shape of these patterns, such as the make and type of motor, the load and speed of the motor at the time of measurement, and the driven equipment as well frequencies introduced by the inverter. When classifying, SAM4 takes all these variables into account.

Misalignment.001

Misalignment can be identified by an increase in energy at the rotational frequency modulated on the main frequency of the current

Broken Rotor Bar

Broken rotor bar can typically be identified by an increase in energy at twice the slip frequency modulated on the main frequency of the current Phase swaps are fairly easy to identify

Anomaly Detection

Anomaly detection algorithms detect irregularities in patterns. A higher anomaly score means that the observed patterns deviate from the expected, healthy patterns and represents a heightened risk of failure, triggering targeted inspections. Conversely, a low anomaly score means that the asset is behaving as expected, and represent a very low risk of failure. This allows maintenance technicians to prioritise maintenance tasks, focussing on assets at risk. 


The anomaly score tracks specific frequencies. In this example, increasing energy at XX Hz is reflected in a rising anomaly score.

Explore Dashboard 

The online dashboard presents real-time health, performance and energy metrics. It is available for desktops, tablets and smartphones - and can be integrated into your existing monitoring solution and asset management tools via an API. 

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Performance metrics

  • Running hours
  • Starts
  • Load
  • ...and more
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Energy metrics

  • Energy
  • Power 
  • Power factor
  • ...and more
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Compare assets

Compare various metrics across a subsection of your assets. 

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Easy to use

SAM4 includes user training and an online manual

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Explore Applications

SAM4 detects mechanical and electrical failures of both the motor and the application.

SAM4 detects mechanical and electrical failures of both the motor and the application it drives, detecting mechanical failures of pumps, compressors, conveyors, blowers & fans, and more.

SAM4 detects mechanical and electrical failures of both the motor and the application it drives, detecting mechanical failures of pumps, compressors, conveyors, blowers & fans, and more.

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AC induction motors
  • Low-voltage
  • VFD-driven
  • Direct Online
  • 0 - 1.000 Ampères
SAM4 detects
  • Bearing degradation
  • Misalignment
  • Soft foot
  • Mechanical unbalance
  • Rotor unbalance
  • Stator eccentricity
  • Stator shorts
  • ... and more.
Metrics:
  • Running time
  • Start-stops
  • Energy
  • Power
  • Power factor
  • Current
  • Voltage
  • ... and more.
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Pumps

Pumps

Pumps

  • Cavitation
  • Dry running
  • Low flow
  • Clogging
  • Impeller damage
  • Cavitation
  • Dry running
  • Low flow
  • Clogging
  • Impeller damage
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Compressors

  • Dirty coils
  • Blocked suction line
  • Bearing degradation
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Conveyors

  • Coupling issues
  • Misalignment
  • Fouling 
  • Bearing degradation
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Blowers & Fans

  • Impeller damage
  • Misalignment
  • Mechanical unbalance
  • Bearing degradation

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