Lift manager

TÜV SÜD Lift Manager

Ensure lift reliability through predictive maintenance and condition monitoring

Ensure lift reliability through predictive maintenance and condition monitoring

TÜV SÜD Lift Manager is an independent predictive maintenance and condition monitoring service that leverages on IoT know-how and TÜV SÜD's lift domain to support your lift operation and maintenance.

The predictive maintenance service can be used with lifts of any age, brand and model, including existing lift in service. It can also be used with a group of lifts with different brands and installation locations. The lifts’ data will be sent to a single platform and analysis will be done to detect anomalies, interpret defects and recommend actions to be taken based on Remaining Time to Downtime (RTD).

By having a predictive maintenance regime to anticipate the failure point of the lift components and replace these components before they fail, you can minimise the lift downtime and maximise the lifetime of the lift components. This will also greatly reduce the need for routine manual lift inspection and maintenance. Therefore, reducing the labour and maintenance costs in the long run. Using data collected over 80 years during lift inspection and certification, the predictive model can detect patterns and failure points with high accuracy.

 

How does TÜV SÜD Lift Manager work?

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Lift sensors are installed to monitor lift health

Our expertise in functional safety for lift operation and maintenance ensure that the locations of the lift sensors are carefully selected and safely integrated.

Our high accuracy predictive model algorithms analyses lift data to avoid possible lift failures

The high accuracy predictive lift model is based on more than 80 years of lift inspection and certification experience, with more than 300,000 inspection performed each year.

Monitor lift condition by anomalies detection, defects interpretation and recommended actions

Lift operation data is collected by the lift sensors and analysed in real time. TÜV SÜD Lift Manager’s predictive maintenance module prompts an alert to the dashboard according to Remaining Time to Downtime (RTD) when a potentially abnormal process is detected. This results in a more efficient lift maintenance regime, reduced lift failure rate and downtime.

visual representation of alert in red, yellow and green 

 

Read the TÜV SÜD Lift Manager whitepaper to get an in-depth understanding of how data analytics can elevate your lift business to the next level of effective efficiency using predictive maintenance.

Download whitepaper

 

The benefits of using TÜV SÜD Lift Manager

  • Save on your lift operation and maintenance cost
  • Potentially reduce lift maintenance visits. Hence, reducing labour cost for maintenance
  • Increase lift reliability and the safety of lift passengers
  • Easy integration as TÜV SÜD Lift Manager works with all brands and models of lifts, regardless of age, on a single platform
  • Better visibility on lift operating and maintenance cost as the transparency and control over lift operation and maintenance increase
  • Fully digitise the lift lifecycle as part of your smart building

Download the brochure to get a comprehensive overview on how TÜV SÜD Lift Manager can value-add to your lift operation.

Download brochure 

 

TÜV SÜD Lift Manager in action

TÜV SÜD Lift Manager is a proven solution to your problems faced during existing lift operation and maintenance regime. It has been installed in TÜV SÜD @ IBP, our new ASEAN Headquarter in Singapore and retrofitted into the lift system of a research and business park in Singapore.

 

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White paper

Algorithm-based data analytics for lifts

How data analytics elevate your lift business to the next level of effective efficiency

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Lift manager @ IBP

Find out how Lift Manager provides the highest lift safety and reduces lift maintenance and repair costs in TUV SUD’s new ASEAN Headquarter

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lift manager

Lift manager @JTC

Read how Lift Manager is retrofitted into the lift system of a research and business park in Singapore.

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