Subscribe Find out first about new and important news
  • Share via email
  • Subscribe to blog alert

Monitoring a mixed fleet of lifts in the business park

The Lift Manager solution brings transparency to lift operations and maintenance at JTC one-north



Running a fleet of lifts of various brands and models distributed across the business park was a resource-consuming exercise. It involved regular manual checks and generated excessive paperwork. Breakdowns disrupted daily life.


117 lifts of five different brands across 11 buildings were retrofitted with sensors feeding data to a graphic dashboard. The solution monitors their physical condition, tracks utilization, and predicts malfunctions.


The Lift Manager solution provided much-needed digitalization. It delivered a centralized interface to monitor all the lifts, ensured easy access to data, and helped reduce downtime and costs through predictive maintenance.

"Every morning, facility managers spent up to 20 minutes inspecting each lift. Remote checks via the Lift Manager dashboard save up to 14,000 man-hours per year – time that can be redirected to other tasks."

Customer profile

The system is implemented at one-north, a large business, research, and development park in Singapore. Master-planned and master-developed by JTC, one-north serves as a fertile ground for research, innovation, and test-bedding. The park houses buildings dedicated to various purposes, including science, technology, and engineering research facilities, offices, lifestyle options, and educational institutions. It is home to a vibrant community of corporate innovators and start-ups. The park operates a large fleet of lifts and was looking to digitize the process of lift monitoring.

The challenge of operating a diverse fleet of lifts

Ensuring smooth and safe functioning of lifts is not an easy task. Having a mixed fleet comprising 117 lifts of five different brands spread across 11 buildings in a business park makes this task even more challenging.

Every morning, facility management staff had to make rounds to check if lifts were in good working order for the day. Given the long walking distances, it could take up to 20 minutes per lift.

The park owners interacted with five separate lift OEMs for maintenance services. The workflow around it was complicated and involved extensive paperwork. Understandably, keeping track of maintenance activities or performance of certain lifts was quite an ordeal as necessary information was scattered across different documents and stakeholders. For the same reason, the decision-making process had to rely on intuition rather than actual data.

All these difficulties made the upkeep of lifts a complex, time- and resource-consuming exercise, not to mention the high costs involved. Lapses occurred, and came at a dear cost to both the landlord and tenants.

On one occasion, a logistics company got a consignment of goods stuck in a cargo lift on the way to the seaport. This resulted in a shipment delay and incurred a significant fine, for which the tenant later claimed a compensation from the landlord.

Other breakdowns affected daily lives of office workers and disrupted important meetings and events.

In search of a solution for lift monitoring

In order to optimize the process, the business park owners were looking to create a centralized lift monitoring system that would provide transparency on lift operations and maintenance, help to minimize downtime, ease the workload of property managers, and reduce maintenance costs.

Large lift OEMs offer proprietary monitoring systems; however, they are of little help if you need to simultaneously manage lifts from different manufacturers. Besides, OEM systems have a clear limitation – they either need to be pre-installed with new lifts or they require a complex, invasive installation. Moreover, only few of them offer predictive maintenance capabilities – and that is a main prerequisite for the eventual reduction of maintenance costs and lift downtime.

The Lift Manager puts a puzzle together

In order to address these challenges, the business park owners selected the Lift Manager by Bosch.IO. From 2018 onwards, the solution has been rolled out on all lifts across the business park, making it one of the largest implementations of a retrofit lift monitoring system in Singapore.


Lift Manager in short

The Lift Manager solution is developed by Bosch.IO in collaboration with lift domain expert TÜV SÜD. It can pull data from any lifts – regardless of brand or model – onto a single dashboard that tracks physical condition, utilization, and ride comfort and sends alerts if anomalies are detected. Noninvasive installation of sensors on top of the lift cabin provides an easy way to retrofit the installed base. Predictive analytics enables the system to forecast the remaining time to downtime and recommend a specific maintenance activity to prevent a breakdown.

Thanks to the deployment of the Lift Manager, the customer now has a centralized system to monitor all the lifts via a single point of control. Its operators can track the current status of lifts on the dashboard and pull historical reports when required. No more daily inspection rounds, no more browsing paper documents – necessary data is just a click away.

Through the system, operators can also keep track of all maintenance occurrences and the time spent by maintenance crews on site.

With operation and maintenance trends close at hand and easy performance benchmarking of lift models and service providers, decision-making has become more data-driven and savvy.

Predictive maintenance for smoother operation

What is of particular importance to the customer is that the Lift Manager can facilitate transition from a traditional maintenance model to maintenance on demand. The latter is based on actual lift condition – wear and tear of specific parts as identified by the system.

The Lift Manager collects operational data on site and cross-references it against a vast data pool accumulated on the performance of similar lift models. According to the customer, predictive analytics applied to that combined data gives the Lift Manager a breakdown prediction accuracy of more than 80 percent. The system keeps fine-tuning its prediction with new data gathered, and the accuracy is steadily increasing over time – take a look at this white paper to learn how it works.

This further simplifies the work of park managers, as they can now plan for targeted maintenance activities ahead of a breakdown. In addition, maintenance technicians don’t have to spend a long time on site to identify the cause of a malfunction – they receive this information in advance and can address the issue straightaway. Thus, predictive maintenance results in a significant reduction of both unplanned and planned lift downtime and savings on maintenance costs.

Lifts are a fundamental asset in a modern high-rise business park, where life relies on uninterrupted transportation of goods and movement of people. Improved maintenance practice leads to smoother daily operation of the business park and a better user experience for its tenants.

Also of interest